The Peter Attia Drive - #133 - Vinay Prasad, M.D., M.P.H： Hallmarks of successful cancer policy

00:00:00.000 Hey everyone, welcome to the drive podcast. I'm your host, Peter Atiyah. This podcast,

00:00:15.480 my website and my weekly newsletter all focus on the goal of translating the science of longevity

00:00:19.800 into something accessible for everyone. Our goal is to provide the best content in health

00:00:24.600 and wellness full stop. And we've assembled a great team of analysts to make this happen.

00:00:28.880 If you enjoy this podcast, we've created a membership program that brings you far more

00:00:33.280 in-depth content. If you want to take your knowledge of the space to the next level at

00:00:37.320 the end of this episode, I'll explain what those benefits are. Or if you want to learn more now,

00:00:41.720 head over to peteratiyahmd.com forward slash subscribe. Now, without further delay,

00:00:47.740 here's today's episode. My guest this week is Vinay Prasad. Vinay is a practicing

00:00:54.800 hematologist and oncologist and associate professor of medicine at UC San Francisco,

00:00:59.640 where he focuses on not just the treatment of patients, but also health policy, clinical trials

00:01:05.820 and decision-making. He's what some might call a meta researcher. He studies the quality of medical

00:01:11.680 evidence and lately has focused most of his energy on oncology. Of course, he's the author of over 250

00:01:18.360 academic articles, along with two books, ending medical reversal, which was published about five

00:01:23.100 years ago and published this year, the book malignant, which we spend a lot of time discussing.

00:01:28.620 He also hosts the oncology podcast, which is called a plenary session. I recommend you check it up.

00:01:34.240 And he runs a YouTube channel along with his various activities on social media. He's primarily

00:01:40.380 active on Twitter at V Prasad. That's P-R-A-S-A-D-M-D-M-P-H, where he writes some really great

00:01:52.260 tutorials related to clinical trials, critical thinking, decision-making, et cetera. In this episode,

00:01:58.040 we talk a little bit about his beginnings, how he got into medicine, and really how things that he saw

00:02:03.740 during his medical training kind of woke him up to some of the issues in clinical medicine,

00:02:09.660 probably the first thing that he observed was some of the limitations in cardiology and how there was

00:02:14.960 a disconnect between clinical practice and research. But really that kind of took off once

00:02:20.200 he chose the profession of oncology, which is a field that is really rife with some of these

00:02:24.900 inconsistencies. Now, this is a podcast that sort of builds on a lot of the stuff that we discussed

00:02:28.980 in a previous podcast with Azra Raza, but we go a little bit deeper into some of the structural

00:02:34.620 failures. This one goes by quick, and yet somehow at the end of it, I looked and realized we'd been

00:02:39.320 talking for two hours. I could have spoken with Vinay for another two hours. We close this by

00:02:45.340 doing kind of a deep dive on what he describes as his six hallmarks of cancer policy. And I think this

00:02:53.060 is a really great discussion. I was just constantly impressed by the way that Vinay was able to kind of

00:02:59.620 articulate things in ways that I even made the comment at one point, if you gave me two hours to explain

00:03:04.500 what you just explained in five minutes, I wouldn't have been able to. So I hope you enjoy this. And

00:03:09.500 without further delay, please enjoy my discussion with Vinay.

00:03:17.520 Hey Vinay, thank you so much for joining me. Where are you physically today?

00:03:22.380 I'm physically located in the Bay Area in one of the distant suburbs, just a temporary place I'm

00:03:27.780 staying here, but hope to be settled in soon. I started at UC San Francisco pretty recently.

00:03:33.440 Yeah, I noticed that and I was going to ask you about that. That's a soon to be your new permanent

00:03:38.440 gig, huh? Yeah, I mean, I started the job, but I do not yet have a permanent place to stay. So I'm

00:03:43.800 just kind of hanging out for now, but I'm going to work on that. And right now, you know, we're in

00:03:47.520 the midst of forest fires and COVID. And so it wasn't a terrific time to move in retrospect.

00:03:53.900 UCSF has a dear place in my heart. When I was in medical school, which was at Stanford,

00:03:58.540 we still spent a lot of time at UCSF. We had the option to spend time electively. And Stanford was not

00:04:04.460 a great place to get a lot of trauma experience for a budding wannabe surgeon. But of course,

00:04:09.260 San Francisco general was. And then many years later, when I returned, my wife was an ICU nurse

00:04:14.940 at UCSF before later moving over to run the Coumadin Clinic, which was run by just a solo NP and one

00:04:22.280 hematologist. So up on Parnassus there, it's some of the most beautiful views of the entire city. So

00:04:28.380 one thing I remember her saying was there was this gym up on the Parnassus campus where she would go

00:04:33.880 and work out at like 530 before clinic starts and you'd sort of get to kind of just watch the city

00:04:40.480 as the sun was coming up. Oh, that's gorgeous. That sounds terrific. I'm actually based in San

00:04:46.140 Francisco General Hospital for my clinic. So that's where I do my clinical time.

00:04:49.500 Ah, fantastic. So you and I were scheduled to speak, I think initially, God, probably around the

00:04:55.980 time of the COVID outbreak. And then obviously everything kind of got derailed a little bit.

00:05:01.060 So I appreciate your patience. There's a lot to talk about here and I almost don't know where to

00:05:05.340 begin, but I do think it probably helps the listener to understand your background a little

00:05:09.460 bit because it's a lot of times people who come to medicine through the not so obvious routes that

00:05:16.760 maybe bring in a little bit of a different perspective. So I know you weren't a pre-med

00:05:20.880 student. It's not like you grew up thinking, I can't wait to be a doctor. If I recall from reading

00:05:26.580 something, you were actually like a philosophy major in college. Is that right? Yeah, I guess

00:05:30.700 I kind of might've done a little bit of both. I genuinely felt undecided at the time. I graduated

00:05:36.220 high school and I thought I'm good in science. I like science. Maybe I'll major in science. And so

00:05:41.700 when I started college at Michigan State University, I think my original major was in the sciences.

00:05:47.020 Early on in my second year, I took a philosophy class and it really kind of struck a chord. The professor

00:05:52.560 was very kind and reached out to me. And very quickly, I added that on as a major. And so I

00:05:57.240 ended up doing a little bit of both. I can't say when exactly I started thinking about medical school,

00:06:01.340 but I remember feeling really sort of uncertain if that was the right path for me. I certainly wasn't

00:06:05.640 somebody who in high school always knew they wanted to be a doctor or anything like that.

00:06:10.440 It came to me sort of on the back end of college, really.

00:06:13.300 You went to University of Chicago, is that correct?

00:06:14.880 That's right. For medical school, yeah.

00:06:16.380 What was that like? I mean, I know that different medical schools had different environments.

00:06:19.720 Stanford, for what it's worth, was a very relaxed medical school. My guess is University of Chicago,

00:06:24.960 being one of the top 10 schools in the country, was not relaxed. It didn't strike me as relaxed.

00:06:30.380 It's so funny you say that. When I was a medical student at University of Chicago,

00:06:33.240 I once visited a friend who was doing his doctorate work at Stanford. And I toured the hospital,

00:06:37.880 and the windows were open, and the smell of jasmine kind of wafted in. And I was like,

00:06:41.660 wow, this is a place of healing. And it was really markedly different than University of Chicago,

00:06:47.400 which is a really gritty city hospital feel. A lot of the faculty had trained on the East Coast,

00:06:53.080 and I think it really had that East Coast mentality. It was an intense place. I remember

00:06:57.720 yelling in the operating room was common. Throwing things was common. People getting chewed out was

00:07:03.260 common. So it had all that sort of East Coast feel, which these days might be a bygone era. But I kind

00:07:09.200 of caught the tail of it, at least maybe second generation. But I caught the tail of, I think,

00:07:12.760 that sort of tough East Coast mentality, which was present in Chicago. Yeah.

00:07:16.700 There's a book that I've spoken about before on the podcast called Forgive and Remember. I don't

00:07:21.120 know if you ever read it. It was written by a sociologist from Pennsylvania University,

00:07:27.300 Charles Bosk. And in the book, he spends 18 months with a group of surgical residents

00:07:33.480 to understand the culture of surgical training. In the book, he never mentions,

00:07:39.960 to my knowledge, I don't think he ever mentions where it was. But for some reason,

00:07:44.100 either I spoke with Bosk and asked him or somehow inferred, but I believe it actually was the

00:07:49.800 University of Chicago where it was. And you have to imagine, you take the environment you saw

00:07:54.080 and go back a couple of decades. This was sort of late 70s, early 80s. And you want to talk about

00:07:59.740 toxicity, but you're absolutely right. There's a real East Coast, West Coast divide in medical

00:08:05.260 education. And I think, put it this way, when I applied to my residency on the East Coast at

00:08:12.220 Hopkins, there was a real view that no one from Stanford could go there and do general surgery.

00:08:18.360 Because the last guy, I think, who had gone and done general surgery, who had come from Stanford,

00:08:23.340 had committed suicide. I see. They thought you were too soft.

00:08:26.060 Yeah. The view was, it was just a little too soft to come from there. Of course, that's such a

00:08:31.200 silly thing to say that this person's suicide had anything to do with that. I mean,

00:08:36.540 the distinction between one versus the other. But it was really viewed as, no, no, no, no. Like,

00:08:40.520 if you went to Chicago, you could go to Hopkins. If you went to Penn or Michigan or something,

00:08:45.380 you couldn't. But anyway, that was my view, having friends that went to medical school in Chicago,

00:08:49.460 is I was academically just a tough school in a tough environment. So how did you like medical school?

00:08:56.360 Well, I guess I probably would be honest with you. I mean, I think I was in the fraction of people

00:09:00.800 that didn't really care for it a lot of the time. To be more specific, when you started medical

00:09:05.900 school, especially in the years in which I trained, you had two just full years of classroom,

00:09:10.820 almost 40 hours a week of just memorize this kid, memorize this, memorize this, memorize this.

00:09:15.660 You didn't really get into sort of the decision making of medicine. You didn't get much exposure

00:09:19.280 to patients. You didn't get that side of medicine. What is actually medicine? Those first two years are,

00:09:23.920 I found it really demoralizing. I mean, I wasn't somebody who was used to memorizing lots of things

00:09:29.780 in sort of a disconnected way. I was somebody who liked to think about things and think about them

00:09:34.160 rigorously. And so I really felt, I would say, very frustrated in the first two years. Step one,

00:09:39.180 studying was a very anxious time in my life, and I didn't quite care for it. And it was only when

00:09:44.260 third year started, and I was there on the wards, and I was on internal medicine first as my clerkship.

00:09:49.200 And I had some really great and influential practitioners of medicine who would kind of teach me how

00:09:55.240 they think about cases. That was when I started to feel like, okay, that's the first moment,

00:09:59.780 that this felt like the right choice for me. So it wasn't until my third year. So I was pretty

00:10:03.520 frustrated in the beginning. And then from third year to fourth year, fourth year is really sort

00:10:07.180 of an expensive vacation, but there were ups and downs in that process too.

00:10:10.960 Remind me where you did your residency.

00:10:12.760 Northwestern University. I stayed in the city.

00:10:14.380 You stayed in Chicago.

00:10:15.080 My folks at that time were living in Northwest Indiana, not too far. And so my undergrad, medical

00:10:20.560 school, residency, was all pretty close to where my family was.

00:10:23.700 Okay. So when is it, like if we look at the work that you are now basically defining your career

00:10:31.700 by, right? I mean, and we're going to get into this in some detail. Where do you think those seeds

00:10:35.720 were sown?

00:10:36.700 I guess I'd say I was somebody who probably said what I needed to say to get into medical school

00:10:41.980 and get into residency. But the truth is in my heart, I was probably somebody who was thinking

00:10:45.900 about medical school as a route to private practice and that I saw myself as a practitioner.

00:10:50.680 I didn't know exactly what field or what specialty, but I thought I would primarily be taking care

00:10:54.980 of patients in a private practice setting. I think that was true even when I graduated medical

00:10:59.900 school and even in sort of the beginning of the first year of my internship. It only kind

00:11:03.900 of changed for me in the middle of residency. And what made a change for me was I had consistently

00:11:09.600 been put in clinical situations where what I saw we were doing and then what I would read

00:11:15.440 about in the evening, there was a disconnect. There were things we were doing that were not

00:11:19.360 supported by strong evidence. There were some things that appeared to run counter to the best

00:11:22.760 evidence. It didn't make a lot of sense to me. And so I started just on the margins of

00:11:27.000 that problem doing a few studies to kind of make sense of what were these things that had

00:11:31.380 become a part of medical culture that ultimately proved not to work. We ended up calling that

00:11:36.060 medical reversal. We wrote a few papers about it, but that was really kind of how I got into

00:11:39.860 it. I got into it from the point of view of a clinician who was struggling to make sense

00:11:43.580 of what was going on around me. And that was really how I fell into research. And I didn't

00:11:48.800 know that research would become my career. But the funny thing about life is you do something

00:11:53.500 long enough and it starts to define you. And so after maybe 15 or 20 papers in this space,

00:11:58.320 people started to say, this is a guy who's doing health policy research in that space.

00:12:01.860 And eventually it kind of just keeps yourself so busy. You're just doing the next thing,

00:12:05.380 doing the next thing. And eventually it kind of starts to turn into a career.

00:12:08.660 So I think in your book, you write a story about a woman who had a stent placed and had a bad

00:12:16.160 outcome. And maybe tell folks a little bit about A, what a stent is, B, what her situation was

00:12:24.300 specifically, and perhaps C, and we can probably both elaborate on part C, which is what in the

00:12:31.780 hell was going on with stents? So I guess I would say, I appreciate you looking through my book and

00:12:37.320 reading it. I guess I would say that we try to use composite patients. We try not to base it on

00:12:41.460 any one particular person, but the situation you're talking about, somebody who gets a stent placed for

00:12:46.560 an indication that is kind of questionable, who suffers a complication. Oh, there are many people

00:12:51.240 that come to my mind about that. I have very clear images in my mind of people in that situation.

00:12:56.960 And I guess I would say, I guess there's two parts to this. So the first part is like,

00:13:00.300 what is a stent? So a stent is a little flexible metallic tube that expands. And it's often placed in a

00:13:06.660 coronary artery when there is a blockage. And for people who come in with a heart attack,

00:13:11.160 an ST elevation marked heart infarction, a total blockage of the artery, a stent is a

00:13:15.400 transformative, life-saving intervention. It's one of those amazing medical miracles that we

00:13:20.560 proudly celebrate in medicine. But it's also something like so many medical technologies that

00:13:25.000 can be used more broadly. It works really well in a critical situation. Maybe it works well for

00:13:30.960 somebody who just has a little bit of narrowing of the arteries, and maybe just a touch of

00:13:34.660 angina. That's that kind of reproducible chest pain that comes on when you shovel your driveway

00:13:39.140 in the winter or go for a long walk. So people would extrapolate from the critical situation to

00:13:44.040 less severe situations in medicine. And of course, there's a lot more less severe situations than

00:13:48.700 there are severe situations. So it becomes a big driver of market share. So it turns out stents

00:13:52.860 became very popular for chronic stable angina. And I knew in the years in which I was a resident,

00:13:58.600 that we had just had a large mega randomized control trial called COURAGE that asked whether

00:14:04.440 or not stents lower the rate of heart attack or improve longevity. And the answer was for people

00:14:09.560 with chronic stable angina, not that acute heart attack, but this sort of chest pain that comes on

00:14:14.120 when you shovel your driveway, there was no improvement in survival and no reduction in

00:14:18.660 subsequent myocardial infarction or heart attack. Yet survey after survey of patients showed that when

00:14:23.860 they were consented to the procedure, when they had it done, they believed it was being done

00:14:27.740 with that purpose in mind. So there was a disconnect between what patients felt it was for

00:14:31.800 and what doctors knew it could do. This disconnect always played a role in the lives of residents.

00:14:37.500 We're not the people who place the stent. We're the people who manage the patient in the days

00:14:40.840 afterwards. And every so often you place a stent, something bad happens. There can be a cardiac arrest

00:14:45.280 on the table. There can be an occlusion of the stent, a thrombus that forms within this foreign body

00:14:49.860 that's being placed in the artery. And we witnessed several of these sort of complications. These are known

00:14:54.160 complications. All things in medicine have some complications. But the question that kind of

00:14:58.680 plagued me was, it's okay to accept the risk of a complication if the procedure has a net benefit.

00:15:04.400 But if the procedure is questionable as it's being done and the benefit is questionable,

00:15:09.500 you're just taking risk without any upside. So cases like that that we talk about in the book

00:15:15.140 were a powerful, I think, motivator for me personally to kind of look deeper into this issue,

00:15:20.300 to really understand why we do what we do. And that led to a lot of work in this space.

00:15:26.000 And I think part of it is, this gets to how we deal with policy, especially on the procedural side,

00:15:31.400 which I think we'll get to is, because I remember seeing this very tangentially as a resident as well,

00:15:37.540 you couldn't ignore the conflict of interest that existed there, which was when interventional

00:15:43.960 cardiologists were being compensated for the number of stents being placed. And I say that to be

00:15:49.460 clear, not being critical of them, but acknowledging that if I were in their situation,

00:15:53.080 I'm not sure how I would self-police. That's the real issue. It's not that they're necessarily bad

00:15:57.980 people, but... They're people. They're just good people. They're just normal people.

00:16:01.380 Yeah, they're good people. And we all suffer from our own cognitive biases. So what was the next step

00:16:06.740 on that rabbit hole? I just want to kind of build on what you're saying, which I think is really

00:16:10.520 astute, which is that these are just people, interventional cardiologists are just people like

00:16:14.340 we're all people. And they suffer from the same sort of psychological trappings that we all suffer

00:16:19.800 from. And in this case, I think there's two parts to the equation that make stents so seductive. So

00:16:25.300 part one is you place this stent and the patient comes back in your office nine times out of 10,

00:16:31.400 and they're happy that you did it. They believe you have saved their life or extended their life.

00:16:35.500 They may even believe they feel better. And in fact, we could talk about Orbita and whether or not

00:16:39.720 that's a real effect or a placebo effect. We can come to that. But they believe they feel better.

00:16:43.580 They believe you saved their life. So you do this procedure. The patient comes to your office.

00:16:47.220 They say, thank you so much, doctor. You saved my life. And you know what? It doesn't hurt so much

00:16:50.960 when I shovel the driveway anymore. Thank you. So you pair that incredibly powerful feeling of

00:16:55.740 gratitude. You pair that with one other thing, which is you get a little bit of money and you get more

00:17:00.600 money the more you do. So when you combine that powerful psychological stimulus of gratitude

00:17:05.900 with a little bit of financial remuneration, I think that's the methamphetamine of being a doctor.

00:17:11.180 That's a highly addictive substance that whatever we do in medicine, particularly procedures,

00:17:16.440 because that's what pays, we become addicted to that. And then a couple years later, some

00:17:21.360 investigators say, you know what? The patient didn't feel better. Actually, when we randomized

00:17:25.440 them to stenting or we made them wear headphones and we told them we put a stent, but we didn't put

00:17:29.780 the stent, we kind of deceived them into thinking they had a stent. They actually both had the same

00:17:34.020 exercise tolerance improvement on a treadmill test. So that's the Orbita study. So when somebody comes at you

00:17:38.960 and they tell you that, you know, it actually, it's just a placebo effect, it doesn't actually

00:17:42.240 improve symptoms. It's psychologically unacceptable. How can that be? It doesn't fit with my experience

00:17:49.260 and it doesn't fit with the way I've been rewarded. And I think that's in part why many of these medical

00:17:54.040 practices that have evidence, I think that goes the other way are very difficult to dispel. We have

00:17:59.200 become addicted to doing them.

00:18:00.580 So you're chugging along through your residency, which means you're basically getting to rotate

00:18:06.460 through all the different subspecialties within medicine. Obviously you're taking care of the

00:18:12.420 critical cardiac patients. Presumably at some points you're taking care of GI patients, oncology

00:18:18.340 patients. What is this journey like for you now that you've got bit by this bug of, hey, wait a minute.

00:18:25.380 But if the stent thing is a little bit off the rails, is there anything else in medicine that's

00:18:30.820 similarly off the rails?

00:18:32.520 No, it's like being a kid in a candy store, Peter. You're onto something. I mean, it's kind of a

00:18:36.820 privilege really now that I look back on it. As a student, I got to spend a month with neurosurgeons

00:18:41.880 watching what they do. Then the next month I got to spend it with a breast surgeon. The next month I

00:18:45.740 spend it with a radonc specialist. As a resident, it's a GI doctor for two weeks. Then it's a

00:18:51.420 hematologist and then it's an allergist. I mean, it's really a privilege. I get to be a fly on the

00:18:55.980 wall of so many different situations and see so much of medical practice. And the moment you start

00:19:01.180 to recognize some of the classic, I think, research pitfalls, the evidence pitfalls, you do, as you

00:19:07.140 exactly say, you start to see it everywhere. You start to see it in how decisions are made in one

00:19:12.140 clinic. Decisions are made in another clinic. There's a theme that emerges. So one theme might be

00:19:17.120 for mechanical interventions done to alleviate a subjective symptom, whether it's angina or pain

00:19:23.880 or dyspnea, which is how you catch your breath or back pain or any sort of discomfort. If you do

00:19:29.160 a mechanical intervention for that, a number of studies show that it is no better than a sham

00:19:33.020 intervention. And that's different than if you compare it to a medical pill where the person

00:19:36.640 doesn't get that sort of psychological benefit that you're doing something for them. So you start

00:19:40.760 to see this theme emerge when you go shadow many places. Explain to folks what a sham intervention

00:19:45.200 is because I think we don't do them much anymore, but there was a day when actual sham surgical

00:19:51.760 procedures were done. Yeah. Well, you might know a little bit more about that surgical history than

00:19:56.000 I do, but I guess I would say when I think about a sham intervention, I say, let's just start with

00:20:00.400 arthroscopic knee surgery. So, you know, a lot of people have pain and discomfort and degenerative

00:20:05.340 osteoarthritis of the knee, and they get a orthopedist to go in with a scope and actually debride

00:20:11.380 some of the cartilage, clean up the joint, make it look a little nicer. So hopefully they have less

00:20:15.420 pain and discomfort. And lo and behold, if you have that done, people feel better afterwards than

00:20:19.720 they did before. And if you compare that to physical therapy or maybe taking ibuprofen, it might even

00:20:25.480 work better. But when you compare it against a sham intervention, that's where the orthopod goes in

00:20:30.500 with the scope. They fiddle with it a little bit, but they don't actually do anything inside. And they take

00:20:35.240 out the scope and they tell you they did something. There is no difference in outcomes. They both feel

00:20:39.620 better. And what that shows you, it's not the debridement per se, it's the psychological

00:20:44.540 stimulus of having that done. And this is true for injecting polyacrylamide cement into osteoporotic

00:20:52.060 fractures of the vertebra. It's true for a couple of shoulder procedures. It's true for, I believe,

00:20:57.840 stenting chronic stable angina. That's what the Orbiter trial shows. That's they did it or they made the

00:21:02.340 person believe they did it. And this is called a sham intervention. And it's a really useful, I think,

00:21:06.960 method to separate what is the benefit from doing that final step that you think matters

00:21:11.840 versus from all the other things we do in medicine, which is reassuring the patient,

00:21:16.540 telling them I'm going to fix it, telling them that I fixed it, and telling them that they should feel

00:21:20.040 better. What's the added benefit of actually doing the thing? In Orbita, did they actually

00:21:25.280 cannulate the femoral artery? Yeah, they did. Yeah, they cannulated the artery. And I believe they

00:21:29.300 performed a diagnostic angiogram. They have all the pictures of it. And they made the patient wear

00:21:33.840 headphones. And they didn't inform them whether or not they had the stent placed. And then the

00:21:37.440 primary outcome that they're looking at is the modified Bruce protocol exercise treadmill. So

00:21:42.200 they put people on treadmills and see how long they can go. And we knew from prior stenting trials

00:21:46.980 that when you stent someone and you tell them you stent them, they're going for another minute,

00:21:51.380 two minutes. And in Orbita study, they're going for a difference of 16 seconds. And it's not

00:21:56.560 statistically significant. And it's not clinically meaningful. So they really do call into question

00:22:01.500 that the benefit of that procedure on this sort of standardized endpoint of subjective symptoms

00:22:06.520 is really sort of what the patient believes it to be. And so that's what a sham study is. And so

00:22:11.620 to your point, which is, you see the theme emerge across many spaces in medicine when you have the

00:22:16.860 privilege of getting to shadow in many spaces. And now, five years into my faculty career, I don't

00:22:22.000 have that privilege too often. I'm in my own bubble. I'm in my own clinic. I'm in oncology and

00:22:25.980 hematology. But in the last year, a friend did an orthopedic surgeon who I really like. I have a

00:22:31.480 great deal of respect for her. She's terrific. And she let me shadow on a couple of surgeries that I

00:22:36.000 hadn't seen. So I got to feel like a medical student again, maybe someday it'll lead to a

00:22:39.880 project that we're working on. But to answer your question, I mean, I think you're right,

00:22:43.420 which is that you do get a sense of sort of the broad lay of the land in medicine when you are a

00:22:47.900 trainee and you can see things with fresh eyes and in many places. So how did you choose oncology

00:22:52.620 as your fellowship? I guess the first jump in becoming an oncologist is you decide to go into

00:22:57.600 internal medicine. I went into internal medicine because I'd had so many positive experiences in

00:23:02.780 internal medicine. I guess the other options for listeners who may not know are you could do general

00:23:06.520 surgery residency. There are a few subspecialties of surgery you can go into right off the bat,

00:23:11.200 like urology or ear, nose and throat or neurosurgery. You could also be a radiation oncologist. You can be

00:23:15.580 an OB-GYN. You can be a pediatrician. For me, general internal medicine was sort of a very broad

00:23:20.100 category. UFC sent the most kids each year into internal medicine. We had really good mentors in

00:23:25.440 internal medicine. So I knew I wanted to be an internist of some sort. I wanted to kind of

00:23:28.760 have a broad look at the body and think of things very broadly. I thought for a while I might be a

00:23:33.780 cardiologist, not just because that's a stereotype, but because I actually was a little bit interested

00:23:37.920 in cardiology. I thought I might be an intensivist, a critical care doctor along the way. And finally,

00:23:42.800 I had some really positive experiences with a couple of oncologists in Northwestern,

00:23:47.380 one of which is Dr. Munchie, who's still there on faculty, but really terrific experiences with sort of

00:23:52.400 consummate doctors, people who balanced. They knew a little bit about the basic science. They really

00:23:56.740 knew about clinical trials. They knew about evidence, and they were really good with patients

00:24:00.460 and great bedside manner. And they made decisions I felt were substantive and important. And so

00:24:05.200 because of that, it's so funny how so much of life is shaped by just the people you meet.

00:24:09.800 I decided to go into oncology. And so I made that decision early on in my internal medicine training.

00:24:15.400 Talk to me about your first days as a medical oncology fellow. Now you're basically

00:24:22.100 also going through comparable stuff. Presumably, you're doing rotations on GI oncology,

00:24:27.160 going through the liquid cancers. I mean, you're running the gamut again, correct?

00:24:32.340 Yeah, you have a great sense of it. Yeah. The first time I left the Midwest, I went to

00:24:36.100 Washington DC and the National Cancer Institute. They have a very unique and fascinating program,

00:24:42.120 and you get to see a lot of stuff. And it's just as you say, one month, you're with a couple of GI

00:24:46.160 oncologists. You spend a few days at the NCI, a couple days at Georgetown, and maybe you go to

00:24:50.440 Washington Hospital Center, one of the other flagship hospitals in the city. One month,

00:24:54.880 you may go to Hopkins and do leukemia. Another month, you may be at the NCI on their clinics,

00:24:59.360 which are really highly specialized, often rare disease. Every patient on a clinical trial or

00:25:04.280 protocol, just a different experience. And so you get a huge, I think, exposure in oncology.

00:25:09.420 You get exposure to so many different diseases, many of which before that time, you know very little of.

00:25:15.320 I think the sad reality of internal medicine training is it trains you a lot in things like

00:25:19.540 cardiology and pulmonary disease. But oncology is one of the things that you don't get into that much

00:25:23.600 until you commit to being an oncologist. And so the learning curve is steep. You got to learn

00:25:27.300 a lot of drugs. There are more new drugs every day, which I think we're going to talk about.

00:25:31.000 And you got to learn a lot of new diseases and a lot of genetics and a lot of things you didn't

00:25:35.420 know before. And so the learning curve is steep. But to be honest, I probably think that's one of my

00:25:39.860 favorite years of training. My first year as an oncology fellow, I had a really great cohort of people

00:25:44.540 training with. We always went for the drink on Friday evenings to have some camaraderie. And we

00:25:49.560 had a great exposure to faculty and we were learning 20 new things every day. I mean, I thought it was

00:25:54.940 really sort of a terrific and transformational year for me. It's also a special place. I was at NCI

00:26:00.140 in medical school and then for two years after and lived just outside of Bethesda in Silver Spring.

00:26:05.940 And I still think of it as some of the fondest memories, which is a very special place. I know we're

00:26:10.520 going to come back and talk about NIH. And I think the NIH in particular, how it funds research is,

00:26:16.580 I certainly have some issues with it and maybe we can get into that. But there's really, it's not

00:26:21.360 hyperbolic to say there's no place like it on earth. And I still remember that first day I stepped

00:26:26.580 foot on that campus as a third year medical student, just thinking, how can this place exist? It is so

00:26:32.740 marvelous. Yeah, it's a marvelous set of buildings there in Bethesda, this huge campus, a lot of greenery,

00:26:39.000 so many different buildings. And the building that predominantly where clinical operations have

00:26:42.900 is building 10, the sort of centerpiece building, this massive federal building that's just been

00:26:46.920 constantly expanded over the years. So much of history occurred in that building. People pioneered

00:26:51.960 the cure for Hodgkin's lymphoma, at least the chemotherapeutic cure for Hodgkin's lymphoma.

00:26:56.160 People did some fundamental work on chemotherapy and breast cancer. So many great laboratory scientists

00:27:01.580 come from that place. And it's a place that certainly gives you a feeling of awe and reverence when

00:27:06.340 you're actually physically there. And I think many of us really are appreciative of the time we spent

00:27:11.200 training there. I think it's a great experience for anyone who listens, who's a trainee, or they're

00:27:15.200 thinking about going into medicine. If you can spend a year there, spend a summer there or do a

00:27:19.600 fellowship there, you'll be richer for it. Now, coming back to oncology, I mean, I think,

00:27:24.260 again, maybe I'm biased because I know enough about cancer relative to other disciplines of medicine.

00:27:30.680 But one of the things that strikes me as challenging about doing a fellowship in medical oncology,

00:27:34.860 as you did, is that there's not a lot that's consistent or similar between acute lymphocytic

00:27:42.480 leukemia or lymphoblastic leukemia and breast cancer. And even though they're both quote unquote

00:27:47.280 cancer, for all intents and purposes, they're totally different diseases. And now multiply that

00:27:53.160 by all the cancers you just rattled off, right? You've got these patients with lymphomas and some

00:27:58.400 of them are Hodgkin's and some of them are not Hodgkin's. And then you've got the leukemias and then

00:28:02.120 you've got the pancreatic cancer and you've got the colon cancer and the breast cancer and the head

00:28:06.860 and neck cancers. That is a lot of different diseases. How did you sort of navigate your way

00:28:13.940 through that as a trainee? And then how do you decide as you're going through that, what does this

00:28:21.040 mean for me in my career? I mean, I agree with your observation that cancer is a category term.

00:28:27.120 It's not a single monolith. It's so many things. And even within cancers, I mean, even within

00:28:33.020 something as small as non-small cell lung cancer, which itself is a category of lung cancer. Now we

00:28:38.480 have EGFR, mutation-driven non-small cell lung cancer. We have ALKRI-arranged non-small cell lung

00:28:43.060 cancer, RET, and then ROS1. We have all these molecular categories. We have RAS, this undruggable

00:28:47.460 target. We have superimposed with that sort of the role of immunotherapy. I mean, it's a lot. And I guess

00:28:52.860 the only way to kind of do it is just to do it piecemeal, a little bit at a time, just reading

00:28:58.240 as you go. Every night you read an article or two, you read up to date, you start there, eventually

00:29:03.240 start to dig into the references. I don't pretend to know everything about every cancer, even to this

00:29:08.260 date. I don't think, and I once heard somebody say, 1963 was the last time a scientist died who

00:29:13.560 knew everything. I mean, it's just impossible to know it all. You can't know all the basic science.

00:29:17.860 You can't know all the clinical medicine. I pick a certain spot. And I think that spot is

00:29:22.480 the spot of a clinician. I mean, my primary sort of interest, and still to this day,

00:29:26.360 what I do with about half my time, hour-wise, is see patients and think about patient care.

00:29:31.900 So I start with that vantage, and then I go outward from there. And so what trials do I need

00:29:35.380 to know? What clinical evidence do I need to know? What heuristics do I need to know to guide

00:29:39.400 patient care? How can I work on my bedside manner? And then beyond that, what policy determines

00:29:44.880 these things, and what basic science is relevant to that. But yeah, I don't know everything about

00:29:48.900 cancer basic science. I don't pretend to. That's beyond what I can know. That's what most people

00:29:53.560 do in oncology. They start with the patient, they work their way outward, and they try to learn as

00:29:57.880 much as possible. And you're always going to be learning new things, even four, five, six years

00:30:02.480 into practice, as I am now. You've brought up bedside manner indirectly twice. So I want to touch on

00:30:07.720 that. It obviously means a lot to you. You mentioned it in the first setting with respect to

00:30:11.660 a mentor you had. And again, you referenced it now in a way that I think is quite interesting,

00:30:16.420 which is it's an area of something you would think about improving upon being better. And

00:30:20.800 do you get the sense a lot of doctors feel that way? And how do you specifically think about

00:30:25.680 improving that? Because anybody who's done what you do understands two things that are simultaneously

00:30:32.080 true, yet cut at odds. The first is the practice of medicine can be exhausting. And at times,

00:30:39.620 it can sort of suck the life out of the practitioner, be it the doctor, the nurse,

00:30:44.580 the therapist, et cetera. But the flip side of that is, again, you referenced this earlier,

00:30:49.820 it's an unmistakable privilege. And that anybody gets to be that intimate with another human being

00:30:56.920 at their most vulnerable time, that's something that can't really be forgotten. And therein lies

00:31:02.520 this tension, at least for me, around what bedside manner means.

00:31:06.220 Yeah, I mean, I guess I can't profess to be the expert in bedside manner, but it is something

00:31:10.900 that I take seriously. And I'm constantly trying to do better. I'll start by saying one thing. I

00:31:15.560 think there is a misconception, I think, among many people outside of oncology, that oncology

00:31:19.400 is often doom and gloom in tough situations. And I guess I want to say that that is true. There is

00:31:25.360 a fair bit of end of life in oncology. We do have to have those hard conversations. But it's not

00:31:30.640 exclusively true. That's not all we do. We also have a lot of people who are concerned about things that,

00:31:35.040 frankly, are not going to be the thing that shortens their life. It's not going to be the

00:31:38.680 end of the world. We also have many patients in whom we cure and we have to follow for long-term

00:31:42.600 side effects. So it's really a range of medical experiences, some of which I think is that tough

00:31:46.600 stuff that people focus on. I'll just tell you one anecdote, sort of what put it all in perspective

00:31:51.460 for me. When I was at the NCI, I worked with a really senior oncologist who had been practicing

00:31:55.360 for 30 years. And we had seen a patient on several visits. And I followed this patient for many

00:32:00.080 months with this senior oncologist. And the senior oncologist had followed this patient for,

00:32:03.340 I think, over a decade. We finally reached an impasse. We reached a situation where there were

00:32:08.860 really no further therapeutic options. The tumors were growing uncontrolled. It was clearly going

00:32:13.640 to take this man's life. And we had sort of radiographic and laboratory evidence that that

00:32:17.700 was the case. We were going to go into that room. And this senior oncologist was going to have to tell

00:32:22.140 this gentleman, somebody he had known for over maybe nearly a decade at that point, that there was

00:32:26.940 nothing more he could do for him and that he was going to pass away. To me, as a trainee,

00:32:31.260 I thought that I have no idea how this guy's going to do this because this is a heartbreaking

00:32:35.880 conversation. My heart is broken and I've only known this guy for a few weeks and I'm not in his

00:32:40.360 shoes. And so I go into the room and he does what would be the stuff of legend. I mean, he's

00:32:47.220 compassionate. He's caring. He's hearing the patient. He's seeing the patient. He's keeping a

00:32:52.120 little bit of distance. He's giving the information he needs to give, but he's also giving sort of the

00:32:55.880 emotional support he needs to give as well. It's very hard for me to even describe how he did it.

00:32:59.980 It felt like magic to me as a trainee. And afterwards, this patient thanks him for the news

00:33:05.340 and is clearly upset about it, but then hugs him and says, I just want to thank you for taking care

00:33:10.060 of me for the last 10 years. I couldn't have done this without you. We come out of that room and

00:33:14.440 we're just all sort of in that shocked feeling of what we had borne witness to, which is really

00:33:19.200 sort of that rare privilege moment of being a doctor. And I remember telling this attending

00:33:23.580 physician, I've seen a bunch of people do that. I don't think I've ever seen anyone do it as

00:33:27.560 gracefully as you have done. That was really well done. How do you think about that? What's

00:33:32.300 going through your mind? How do you approach these situations? And he looked at me and he said,

00:33:36.780 I can't say that I'm good at it after doing it for 30 years, but I can say I try to be better at it

00:33:41.400 each year. And I realized that that was his secret, of course, is that he had never let himself become

00:33:47.180 complacent. He never let himself feel like he did a good job. He always aspired to be a little bit

00:33:52.440 better at delivering that news a little bit more in the moment than the year before. And that was

00:33:58.080 why he was so good at it is that he didn't take it for granted. He knew how important it was and he

00:34:02.140 worked on it. And I guess that's how the moment he told me that obviously it was sort of the moment

00:34:07.620 that that was how I was going to think about it forever because he was right. And it's so easy to

00:34:11.780 think as an oncologist that your decision is just prescribing the right chemotherapy drug.

00:34:15.440 But so much of oncology is being the person you need to be for this person who needs you to be

00:34:21.240 there for them in that moment. And I think that's in part what makes the field so rich and so

00:34:25.340 interesting. First of all, that's a absolutely beautiful story. Secondly, I find it interesting

00:34:30.920 that it's hard to actually articulate the nuances of what he said while you're still able to capture

00:34:37.940 the gestalt of it. And that actually echoes an experience I had also at the NCI with my mentor

00:34:44.860 who I remember a very similar situation. This was a very young patient, about 27 years old,

00:34:53.800 metastatic melanoma. He had progressed through, at the time, the best available immunotherapy.

00:35:00.340 So a couple of things that stood out to me. One is when we were rounding on patients,

00:35:03.760 we were never permitted to say this patient failed such and such. As you know, in oncology,

00:35:09.460 that's a very common parlance. Mr. So-and-so is a 27-year-old male. He has failed

00:35:14.420 interleukin-2. He failed GP-100 vaccine. No, it was never that. It was the therapy failed the

00:35:22.020 patient. The patient didn't fail the therapy. So we were very clear in our words. There was no

00:35:27.500 ambiguity about how we spoke about it. But when it became clear, just as you described radiographically,

00:35:34.160 that there was now no option remaining for this patient and the tumors in his lungs and liver were

00:35:41.160 exploding. Steve Rosenberg was my mentor. He said something to me that was, it's really easy at

00:35:47.000 this point to think that because we have failed, we should be ashamed and we should run away from

00:35:52.080 this patient. But he said, patients who are dying need us more than patients who are living. Which again,

00:35:58.260 sounds kind of vague, but it's that ethos that gets carried into the discussion. And if you think of

00:36:05.460 it that way, I think that's what actually contributed to the interaction. So your story is really a

00:36:11.320 beautiful example of that. We're going to end up talking quite a bit about cancer here, not only

00:36:16.140 because it's your career, but it's also potentially maybe outside of cardiology, one of the places where

00:36:23.500 we see the best of intentions gone awry with respect to how to help people. God, there's a part of me

00:36:30.620 that almost wants to jump right into your hallmarks because you close your book with, and by the way,

00:36:36.100 I'm in the process of sort of trying to write a book so I can appreciate the comedic relief in how

00:36:42.120 the appendix or slash end of your book is, oh, by the way, as I finish this book, I think I finally

00:36:47.820 figured out a succinct way to explain this now, which I loved. Yeah. Yeah. So true. But maybe we'll

00:36:54.660 save that for a moment. And cause I think that's a nice way to synthesize it unless you just want to

00:36:59.040 start with that. But do you want to kind of get into a little bit of the, how you came to appreciate

00:37:03.700 what was not working and how that sort of led you to formulate your journey through this?

00:37:10.180 Yeah. I guess I'd say, I'll talk a little bit about what are the sort of structural problems

00:37:14.620 in oncology, but I guess I'd say one of the sort of moments in my life that it all came into

00:37:19.420 crystal clear focus was there was a year at the national oncology conference that there was one

00:37:25.640 super transformational drug. And it was the drug that made the big stage and it was the drug everyone

00:37:31.240 was celebrating. And it was a drug that prior to having this drug, the median survival with this

00:37:36.100 condition was something on the order of six months. And now that we have this drug, unfortunately,

00:37:40.300 nobody was cured with this drug, but the median survival was extended to 11 months. And so that's

00:37:44.320 something like five month improvement in average median survival that a patient would experience.

00:37:49.400 And it was getting standing ovations and people were incredibly enthusiastic about it.

00:37:52.840 And I just remember, I think at the time the conference was going on in Chicago and one of

00:37:56.560 my high school friends was visiting and he asked me, he's like, you know, what's the big talk at that

00:38:00.300 conference? And I told him about this drug survival six months and now it's gone to 11 months. And he

00:38:04.920 said, six months, 11 months. And he said, Oh, he said, what are you talking about? He said, do better

00:38:09.180 than that. That's not good. I mean, 11 months, not good enough, man. He just said it. And it was just his

00:38:14.500 gut reaction. He didn't go to medical school and he didn't even complete college, but he's a terrific person.

00:38:19.060 And, and, but he was just giving his sort of just raw feeling about that. That wasn't good enough.

00:38:23.480 You all need to aspire for more and led to a lot of investigations where we and others have looked

00:38:28.600 at what's the average benefit of a new cancer drug coming to market. If you look at 71 consecutively

00:38:34.280 approved drugs for the solid cancers, as FOHO and colleagues did in a, in a famous paper a few

00:38:38.940 years ago, the average improvement was 2.1 months. So that's the average of 71 drugs. Two months can

00:38:46.020 mean a lot to somebody. I mean, those are, those could be two months where you do a lot of important

00:38:49.660 things, but two months also feels like, boy, can't we do better than that? And two months should also

00:38:56.160 come with another asterisk, which is what is the cost of these medications? They now routinely run

00:39:01.400 100,000 to $200,000 per year of treatment. And you got to take it for maybe eight, nine, 10 months to get

00:39:07.080 the two month benefits. So you're spending nearly a hundred thousand dollars of money just on the drug

00:39:11.840 itself, potentially all these other costs that come. And so many of us, myself included, started

00:39:17.040 to feel like, why are we spending so much money on these drugs that appear to offer less than what

00:39:21.960 we would want and hope for, for our patients? Why are there so many of them coming? Why aren't there

00:39:26.880 fewer but better drugs coming? What are the sort of structural problems in this space that create a

00:39:32.040 glut of often me too drugs? And by that, I mean, there's a Coca-Cola and there's a Pepsi-Cola and we're

00:39:37.780 getting lots of Pepsi-Colas. We're getting a lot of me too drugs. We're not getting as many drugs

00:39:41.720 that are as novel that really are transformative. And so that was kind of one of the core questions

00:39:47.440 that started me on this path. And Malignant is sort of a book that summarizes sort of all the

00:39:53.560 work we've done in cancer and cancer drug space and drug policy space. But it wasn't, of course,

00:39:59.220 the goal when we started doing this work. We just kind of wanted to understand a bunch of things.

00:40:02.600 And after a while, we understood a few things in a way. And we realized that, I realized that there's

00:40:07.800 a story that could be told across all these different domains and that it makes more sense

00:40:11.760 when you tell the whole story. And so that's why I decided to write that book.

00:40:15.420 So let's start with the idea of reversal. You alluded to it earlier. Let's go back and revisit that.

00:40:20.720 So that was sort of inspired by work I did as a resident. I had seen those situations that we

00:40:25.880 talked about, situations where people were getting things done that appeared to run counter to the

00:40:30.000 best available evidence. And with a colleague of mine, Adam Sifu, who's a professor at the

00:40:34.060 University of Chicago, he was a former teacher of mine, later became a mentor of mine, and later

00:40:38.320 became a friend, which is sort of how the progression of those events often is in life.

00:40:42.680 We started to ask a bunch of questions about how many medical practices are adopted based on low

00:40:48.200 levels of evidence, what drive their adoption, and what happens when years later people come along and

00:40:54.040 do really carefully done rigorous studies and find that some of them do not work as intended.

00:40:58.560 And we call those practices practices that weren't just replaced by something better,

00:41:02.680 but practices that truly were reversed. We found that not doing it was better, or whatever you

00:41:06.880 did before was better. We called those medical reversals, and we started to kind of make lists

00:41:11.120 of them, keep track of them, and try to understand how often they occur, why they occur, what the

00:41:15.480 downsides of having so many reversals are. That led to the sort of the first book that I wrote with

00:41:20.260 Adam Sifu, which is called Ending Medical Reversal, which is really about all the flip-flops that

00:41:24.200 happen in the doctor's office.

00:41:26.260 What are some of the examples that people might bring to mind when you think about that?

00:41:29.340 I mean, I guess a lot of them are actually from our talk and shop or sort of things that doctors

00:41:33.960 do, but I'll give you a few examples. So one is hormone therapy. So there was this very provocative

00:41:39.120 idea that was put out in the 1990s and supported by a couple of observational studies from the

00:41:44.020 Harvard investigators. And that was the idea that women who typically have low rates of cardiovascular

00:41:49.380 events, when they go through menopause, they have a higher rate of cardiovascular events.

00:41:53.620 Maybe estrogen was protecting them, lowering the rate of cardiovascular events. And maybe if we

00:41:58.580 supplement them with estrogen after menopause, they'll have lower rates of cardiovascular events.

00:42:02.960 A retrospective observational study from Harvard found that nurses who happened to take hormone

00:42:07.140 therapy, replacement therapy, did in fact have lower rates of cardiovascular disease.

00:42:11.660 And this led to sort of widespread promotion. There's a company called Wyeth that was really,

00:42:16.320 I think, instrumental in driving prescriptions of hormone replacement therapy. There was a lot of basic

00:42:21.400 science evidence that corroborated that estrogen has sort of favorable effects on vascular endothelium,

00:42:26.180 et cetera, et cetera. It quickly became sort of a widely used common medication, accruing dollar

00:42:32.000 amounts in the billions of dollars. And then lo and behold, in 2001, 2002, a randomized control trial

00:42:38.140 called Women's Health Initiative came out, but randomly assigned postmenopausal women to estrogen

00:42:43.120 supplementation or not. And it found, in fact, it was halted for an increase in thromboembolic and

00:42:48.540 cardiovascular events. It actually did the opposite of what investigators had thought.

00:42:51.960 That was sort of a seminal moment, I think, for many people that maybe things that are widely done

00:42:57.780 don't work as intended. I'll give you just another example. After somebody has a heart attack,

00:43:02.900 if you put them on an EKG machine and watch it, you'll see there are a bunch of aberrant beats,

00:43:07.760 premature ventricular contractions, PVCs. A number of really well-done studies have shown

00:43:13.400 that the more PVCs a patient had, the more likely they are to have sudden cardiac death.

00:43:18.220 And there was a reason why that might happen, that these aberrant electrical activity of the heart

00:43:23.040 could actually precipitate a reentrance circuit and precipitate actually cardiac arrest.

00:43:27.520 A number of drugs were made that could suppress PVCs. They suppressed PVCs rather potently. So you

00:43:32.960 could have somebody take the drug and you can watch those PVCs just drop out of the EKG tracing.

00:43:38.060 And finally, somebody came along and said, look, we know PVCs are bad. We know the drug suppresses

00:43:43.700 PVCs, but we don't know for sure the drug lowers the risk of dying. Let's test that. Let's do a

00:43:48.780 randomized trial. And they did that randomized trial. It's called CAST. And cardiologists were

00:43:53.160 really reluctant to randomize patients because they thought it was unethical not to give the drug.

00:43:57.900 And finally, through persistence, they did do the randomized study and actually found that it

00:44:01.900 increased the risk of dying. And so those studies have led to the abandonment, primarily the class 1C

00:44:06.440 agents, flecainide and the like. And I think what the takeaway message there is that, wow,

00:44:11.220 a lot of smart, well-intentioned people who really have plausible pathophysiology, who have a

00:44:17.040 compelling retrospective observational story, they can be wrong. And has this happened elsewhere?

00:44:22.640 And so we started investigating. Now we have lists of hundreds of items. They span everything from

00:44:27.920 ways in which we screen patients, ways in which we test patients, drugs we give patients, procedures

00:44:32.980 we do on patients, surgeries we do on patients. It really spans the gamut. There have been these medical

00:44:37.020 reversals across broad domains of medicine. They are quite common.

00:44:40.440 I'd like to come back to one of those because I do think the WHI is arguably the worst study that's

00:44:46.840 ever been done, which then brings up a broader question, which is how do we know if the patient

00:44:53.900 in front of us is represented by the patient in this study? But I don't want to take us off the

00:44:58.400 oncology path. Although the WHI's biggest headline, of course, was the increase in the risk of breast

00:45:04.480 cancer, which of course has since been abandoned, which actually brings up another point, which is the

00:45:08.920 difference between relative risk and absolute risk. So I think there's a lot of interesting stuff to

00:45:12.140 talk about. So let's get back to oncology and go back to what you were just sort of outlining as I

00:45:18.460 think the broad problem statement here, which is we've got a disease that I think it's safe to say

00:45:26.160 we haven't really had much success against despite a lot of propaganda. I sort of explain it to my

00:45:31.760 patients this way. I don't know if you'd agree, but I say, look, there are three broad pillars of

00:45:36.080 disease, chronic disease that are going to kill us. So you've got sort of this foundation of

00:45:40.460 metabolic disease. So that's everything from hyperinsulinemia to insulin resistance to fatty

00:45:45.700 liver disease to type 2 diabetes. That creates the foundation upon which three other disease

00:45:52.240 processes get a lot worse. Cardiovascular and cerebrovascular disease, cancer and neurodegenerative

00:45:58.540 disease. There's really only one of those three pillars we've had some success against,

00:46:03.360 and that's cardiovascular disease. Your probability of surviving a heart attack in

00:46:07.680 2020 is infinitely better than 1960. I mean, between advanced cardiac life support, better

00:46:16.480 drugs to lower cholesterol, lower blood pressure, as you pointed out earlier, stents that actually

00:46:22.220 do their job in patients who are having an MI or immediately post. And also I think we have

00:46:27.540 a greater pathophysiologic understanding of it. But if you have metastatic breast cancer in 2020

00:46:35.340 versus 1970 or 1960, if you have Alzheimer's disease in 2020 versus 1970 or 1960, you're not a hell of a

00:46:45.220 lot better off. And I think that's a hard thing for people to understand, especially when you consider

00:46:50.860 the resources that have been put at it. Have you got a ballpark of how much has been invested in cancer

00:46:57.500 research in the last 50 years, directionally since the war on cancer was declared?

00:47:02.180 The total will easily be in the hundreds of billions of dollars. So I guess I would say, I mean, I think your

00:47:07.220 assessment, although people may not like it, I think it is not inaccurate. It is accurate assessment is that

00:47:14.620 we've poured in hundreds of billions of dollars. That's probably combined with public purses and private

00:47:19.960 purses. And the returns on that, it's easy to sort of fixate on the few sort of examples where we've made

00:47:27.160 massive progress. But we can't forget the denominator, which is the average person walking in clinic who might not

00:47:32.720 have chronic myeloid leukemia or one of the rare conditions that we've made sort of transformative

00:47:36.580 leaps in. The average person, I think, is still facing a very grave prognosis and that the progress is, as my

00:47:43.400 friend said, that's not good enough. You got to do better.

00:47:45.600 Yeah, it's a great story about your friend because sometimes you just need an outsider to sort of call

00:47:49.940 your BS, which is we celebrate this drug. I remember when I was in residence, I don't remember what drug

00:47:55.480 it was, but I literally remember going to ASCO or something and someone presented a drug that increased

00:48:01.580 median survival by 0.7 months. 0.7 months, right? 20 days. And I remember doing the math. It was at a cost

00:48:11.120 of $38,000 for the extra 20 days. And I mean, I think people listening to this might be

00:48:17.940 understandable to question, well, who are we to say what $38,000 is worth? How do you think about

00:48:24.220 that question, which is the societal cost versus the individual cost? So all things equal, let's assume

00:48:31.720 there was no toxicity of the drug or let's assume that the pain and discomfort of the drug wasn't a

00:48:38.020 deciding factor. Who is to decide the cost of a life? I guess before I dive into that answer,

00:48:45.240 let me give a little bit more background that I think will even make it more sort of relevant for

00:48:49.700 the listener to really get a sense of why I'm going to answer the way I answer, which is that 0.7 months,

00:48:55.460 that's not in everybody. And what do I mean by that? So the trials that we use to identify these

00:49:01.000 numerical amounts that the drugs improve survival are not average Americans off the street with the

00:49:06.760 cancer. They're really carefully curated populations. They're often 10 years younger

00:49:11.220 than average cancer patients. They don't have the same range of comorbidities. They don't have as

00:49:15.980 much diabetes. They're not as overweight. They don't have cardiovascular disease. They don't have

00:49:19.760 renal dysfunction. They're younger, healthier. One of my colleagues describes clinical trial patients as

00:49:25.080 somebody who could run a marathon who also happens to have cancer. They're really fit individuals.

00:49:30.040 And in that person, you give them a drug that may make some of them have diarrhea eight times a day,

00:49:36.440 or make their hands and feet ache, or make them lose their hair or have bone marrow suppression,

00:49:40.900 or all of these things. But because they're so fit, they can tolerate that drug and they can take that

00:49:45.460 dose and they can handle those side effects. And in that person, even though they push the dose in

00:49:50.500 that person to handle all that side effects, the benefit is still 0.7 months. So now imagine what

00:49:55.600 happens when you give it to an older person who's frail, who can't handle the full dose because they need

00:50:00.260 a dose reduction because that side effect is massively more severe in that person. What's the benefit in

00:50:05.120 that person? And I think a number of empirical studies have looked at these cancer drugs

00:50:09.240 and find that the benefits in the average American are maybe even absent. I mean, I'll give you one

00:50:15.000 example. There's a drug seraphinib in the trial that led to its approval. This is for patients with

00:50:20.200 liver cancer that can't be treated by surgery. This is liver cancer where the horse has leapt out of

00:50:24.140 the barn and it cannot be cured with surgical resection or transplant. If you randomize them to

00:50:28.780 seraphinib or placebo, sugar pill, 11 months median survival with seraphinib and about eight months

00:50:33.840 with placebo, a difference of about three months. And this got a standing ovation at the national

00:50:37.680 meeting. People really celebrated this drug. A couple of researchers looked at Medicare data sets

00:50:43.020 here, Medicare, which is Americans over the age of 65. And they found people who took seraphinib

00:50:47.980 for this disease. And they found the median survival of somebody who took seraphinib in Medicare

00:50:53.080 was around four months. So in other words, in the real world, somebody taking the drug that

00:50:58.620 improves survival lives 50% as long as the person taking sugar pill in the trial, which just shows

00:51:04.600 you that the grand canyon of difference between real world patients and clinical trial patients.

00:51:09.620 And in the real world, they compared those people taking seraphinib who live four months to similar

00:51:14.500 people who didn't take seraphinib. And they also live four months. So I think that some of the benefits

00:51:20.120 of these drugs do evaporate when you give them in broad populations.

00:51:23.680 First of all, I'm really glad you brought that up. I interviewed Azra Raza a little while ago,

00:51:27.960 and she made the same point. I just don't think that can be overstated. So I want to make sure that

00:51:32.400 people really understand what you're getting at. When we look at nameplate clinical trials,

00:51:41.100 they aren't just best case scenario by a little bit. They are best case scenario by a log order

00:51:48.580 based on patient selection. And let's be clear. If you're in the business of trying to get your drug

00:51:54.440 approved, it is in your best interest to spoon feed and handpick the absolute healthiest people

00:52:01.660 on the planet in whom to test your drug. So again, the system is set up to make this happen. This isn't

00:52:08.780 some grand conspiracy. It's common sense. You've spent a billion dollars generating this drug. The final

00:52:17.360 hurdle for you to get this drug to market is a very large phase three trial. You're not about to blow

00:52:23.220 it by screwing up the patient selection. It's no different than being a trial lawyer who spends a

00:52:30.820 year preparing for a case only to pick the wrong jury. You've got to do your job and pick the right

00:52:36.360 patients. Your point is, hey, and Azra made the same point. Look, the likelihood that the person sitting

00:52:43.120 in your clinic in front of you is half as healthy as the patient in that clinical trial is very low.

00:52:49.980 And therefore, they're not going to be as resilient, which means A, they probably can't

00:52:55.300 tolerate the drug as well. And B, they don't have the physiologic reserve such that the delta between

00:53:03.860 them and the untreated patient is likely to be far compressed.

00:53:08.540 That's right. And I think you make another terrific point, which is that we can't blame

00:53:13.480 the tiger for being the tiger. The pharmaceutical company is doing what's rational. They're tasked

00:53:17.440 with running a trial to test their own product. If you win, you're going to earn on average $12

00:53:23.400 billion in the next 14 years. If you get a P, a 0.049, you get 12 billion. If you get a P, a 0.051,

00:53:30.780 you get minus a few hundred million dollars, your outlay on the drug. And if you have an incentive

00:53:34.880 system like that, I mean, you should not blame the industry for, I think, all of the things we see in

00:53:41.040 clinical trial design, which are sort of okay, acceptable ways to put a thumb on the scale.

00:53:45.960 One of which is you carefully curate your patient population. Another is you test your new drug against,

00:53:51.540 well, maybe not the drug doctors are actually using. Maybe you test it against the oldest,

00:53:56.080 weakest drug in the space. Maybe for patients who take the old drug, when they have progressive

00:54:01.080 disease, they don't get access to the best new drugs. They get substandard care, which often

00:54:06.400 happens in these registration studies. There are a number of ways that I think are within the realm

00:54:10.560 of what people accept that allow for gaming of the trial. And it would be irrational not to take

00:54:14.800 advantage of that because the amount of money at stake is vast. And the incentive to put a thumb on the

00:54:19.840 scale when you can is great. But I think it's worth restating, as you say, that these are drugs that

00:54:24.960 we're really talking about the best case scenario and the best case scenario is often less than

00:54:28.260 desired. Should we go to the next part, which is the cost? How do you decide who pays?

00:54:32.000 Yeah. So I'll think back to probably the first time I remember thinking about this

00:54:36.080 was when Gleevec was approved. Now Gleevec was, God, I'm trying to think. I was probably in residency

00:54:42.400 when Gleevec was approved.

00:54:43.760 Yeah. 2001.

00:54:44.360 Yeah. This was a big deal because I remember in medical school, I had read Judah Folkman's book.

00:54:50.200 Judah Folkman has since passed, but he was sort of a luminary oncologist. And he was basically one

00:54:55.960 of the first people to propose this idea that if you cut off the blood supply to a tumor,

00:55:02.380 you could stop a tumor. And again, to put this in the broader context, this was a pretty remarkable

00:55:06.880 idea because up until that point in time, you had this idea that you could cut a tumor out if it was

00:55:12.340 localized. You could give a bunch of chemicals that targeted its ability to replicate. That was

00:55:17.800 sort of the gist of chemotherapy, or you could radiate the crap out of it, which also basically

00:55:22.740 destroyed its ability to replicate. And some people like Steve Rosenberg and Jim Allison were working

00:55:28.020 on these immunotherapy ideas, but Judah comes along and says, look, there's another really obvious idea

00:55:33.740 here, which is any cancer cell that leaves its site of origin and goes to take up residence somewhere

00:55:39.480 else. Better figure out a way to get blood. And so we have these growth factors for blood,

00:55:45.040 VEGF being one of them. And so this whole new thing of anti-VEGF compounds comes along.

00:55:50.240 And so Gleevec becomes the first drug approved for this. And if my memory serves me correctly,

00:55:53.700 it was for colon cancer was the first indication. You probably think of a bevacizumab and Avastin.

00:55:58.640 Oh, that's right. I'm sorry, sorry, sorry, sorry, sorry. You're absolutely right. I'm thinking of

00:56:01.440 Avastin. Of course, Gleevec is for GI stromal tumors. Yeah, yeah, yeah. I'm absolutely thinking of

00:56:05.940 Avastin. Yes. Okay. Same time period though. Avastin was about 2000, 2001, maybe 2002. And was

00:56:11.280 it colon cancer for Avastin? Yeah, it was the first one. Yeah. And I sort of remember directionally

00:56:17.520 it being about a hundred thousand bucks for a year. And do you remember what the improvement

00:56:23.740 in survival was with all the noted caveats that we just gave? Was it like eight versus 12 months or

00:56:28.240 something to that effect? I think it was less than that. I think the original paper that led to

00:56:33.040 approval was the Hurwitz paper. And I think it was on the order of a couple of months,

00:56:36.360 but I guess I would say that if you look at Avastin across all the different cancers, I mean,

00:56:41.260 you're, you look at where it works and where it doesn't work, where it works. We're talking about

00:56:44.360 a month and a half, two months. I mean, that's about the average. The point of my very unfortunate,

00:56:48.980 long-winded story was certain countries. And I think the UK was on the list just said, no,

00:56:55.440 we're not paying for this drug because it doesn't reach our threshold, which I think at the time

00:57:01.680 was about 100,000 pounds per quality adjusted life year per quali. And the United States of course

00:57:09.700 took a different position, which was private insurance companies will pay for this, which

00:57:13.600 basically means the government and or employer will pay for this. And I remember that being the

00:57:18.080 very first time that I thought about this and thought, huh, what is the implication of this?

00:57:23.600 How does this work? So how do you think about that? And again, this is almost asking you to put

00:57:28.600 on a policy hat on half of your head with a physician hat on the other half of your head,

00:57:33.260 right? I think you're right about one thing, which is that there are different hats. And when you're

00:57:36.940 in the room, what you do might not be the same thing as what you advise a government to do.

00:57:40.080 And maybe that's okay. That's the right way these things should happen. When you're in the room,

00:57:43.440 you do everything you can that adds anything that the patient really wants and that the toxic is

00:57:47.080 worth it to the patient. When you were in the policy hat, you ask what's best for everybody.

00:57:50.620 And I guess what I would say here is one thing that fits in this discussion

00:57:53.560 is that every dollar spent on Avastin is a dollar not spent on a lot of healthcare interventions

00:57:59.180 that may have better bang for your buck. You might take all that money that we're spending

00:58:02.920 on Avastin for a hundred people, and we might get a hundred thousand people to take their

00:58:07.360 lisinopril or their hydrochlorothiazer, their blood pressure pills more religiously. We might

00:58:11.240 get them to do something else. And the cumulative number of life years added to the world from those

00:58:16.080 people doing whatever that other thing is, that may exceed the Avastin benefit by an order of

00:58:21.100 magnitude. When societies pay for something, it is different than when you and I pay for something.

00:58:25.720 If I take my own money and buy anything, it's really nobody else's business. And if you do

00:58:29.420 whatever you want with your money, but if we all make a commitment to healthcare, what we're saying

00:58:33.360 is we're all going to pool all this money and we're going to pool this money so that we pay for

00:58:37.760 this thing that we think is a different commodity. It's something that's a human right, something

00:58:41.980 that we all deserve to have. The only rational way I think a society to spend that money is to do

00:58:47.060 what benefits the most people, what brings the most good in the world. That might mean

00:58:51.420 sometimes societies make, as the UK does, tough decisions. They decide instead of 20 people getting

00:58:57.500 access to some new cancer drug that doesn't cure the disease but may extend survival by a couple

00:59:02.340 months, let's take all that money and let's give pregnant women access to X, Y, or Z that might

00:59:07.680 improve the longevity of their children and another generation of kids in the UK. And so I think that

00:59:13.340 all nations struggle with this question, which is how do we ration limited resources? In other

00:59:18.920 countries, they are upfront and open about the discussion. They use things like cost-effectiveness

00:59:24.160 to ration products. In the US, we do ration. We just ration in a way you don't see because some

00:59:30.380 people don't get anything. They don't get beneficial medicines and they don't get really marginal

00:59:34.920 medicines either. They just don't have access at all. They're cut out of the system. And so we ration

00:59:39.400 by discriminating against people. That's a different type of rationing. It's cruel and

00:59:43.720 irrational, but it is a rationing nonetheless. I think that this is a thorny problem and no one

00:59:48.100 person has the answer. And I guess I also think that people should be free to spend their own

00:59:52.180 money as they so choose. I think the reality is if you had to spend your own money versus deciding

00:59:57.720 whether or not to leave that money for your children or for a loved one, I think a lot of people

01:00:01.780 wouldn't buy these drugs. I mean, there might be some ultra wealthy people, but I think some of us

01:00:05.660 might make different choices with our own money. If you have to spend society's money, I think the

01:00:09.380 obligation to really know that they work, that they actually are delivering benefit to people,

01:00:13.960 I think that obligation is a bit stronger. When you go back and think about your undergrad

01:00:17.820 as a philosophy major, this is probably one of those places where you probably have an insight

01:00:22.860 that someone like me doesn't have. I mean, how do you think about this through the lens of what

01:00:27.360 philosophers would have said? Yeah. I mean, I guess I would say, I don't know if that's true,

01:00:32.460 that I have an insight that you don't have. I think you have a lot of good insights

01:00:35.660 I guess I would say, obviously what I'm speaking about is a type of ethic, which is probably

01:00:40.000 called utilitarian ethics, which is this idea that ethical principles, when they are in conflict,

01:00:45.840 they prioritize the greatest good for the greatest number over a lesser good for a lesser number.

01:00:51.040 And when it comes to deciding whether or not to cover really costly cancer drugs that have small

01:00:56.640 benefits and idealized settings and have question mark benefits in real world settings versus paying

01:01:01.500 for other things that have more convincing evidence that they improve outcomes for a lot

01:01:05.880 more people, I think a utilitarian ethic would tend to side with the latter, that you got to pay for

01:01:11.000 what benefits more people. I mean, one of the constant criticisms of the UK system is that cancer

01:01:17.480 outcomes aren't as good in the UK as they are in the US. I think that fact alone has been overstated to

01:01:24.060 some degree. But that's not really the question, because the question is their life expectancy is better.

01:01:28.260 They're spending less on health care, they got better life expectancy, their medical care may be

01:01:31.700 better. I think if you're looking at somebody, if you're looking at the person just getting the

01:01:35.560 Avastin, I think the decision is different than if you're looking at everybody. There are different

01:01:39.140 conceptions of ethics. And I think some people might put a value on caring for people at the end of life,

01:01:44.320 irrespective of I think societal implications for others. And I guess I don't sort of a deontologic

01:01:49.120 perspective. And I guess I don't discount that at all. I mean, I think when people are question mark on

01:01:53.980 Avastin for colon cancer, we're not saying don't treat a person, there's still lots of treatments you'd give,

01:01:58.200 you give the same treatment except leave out the Avastin. And the difference is probably very

01:02:02.540 slight. Maybe there's no difference at all is what somebody like me might think if I haven't

01:02:06.880 reviewed all the evidence. One of the things that I just think, I'll tell you a funny story and I'll

01:02:11.880 come back to the thing. And I may have even mentioned this during the podcast before, but

01:02:15.040 I had a friend who used to live in Saudi Arabia. He's an American, lived in DC. So during the summer,

01:02:20.160 he would always come back to DC. So he would sort of spend June to September in DC before going back to

01:02:25.460 Saudi Arabia. And I was there visiting him once. And I asked him, I said, dude, what's it like when

01:02:32.840 you come back to your apartment in September? Just tell me how hot it is. Is it like, does it hit 130

01:02:38.100 degrees after you've left the apartment sitting there all summer? He goes, no, man, it's like 70

01:02:43.080 degrees. I leave the AC on the whole summer. And I'm like, what do you mean you leave the AC on the

01:02:47.880 whole summer? You have a timer set to come on an hour before you get there. He goes, no, no, no,

01:02:51.640 no. When I leave, the AC is on. When I come back, the AC is on. I can't wrap my head around this.

01:02:58.020 And I am like, how criminal is that? How much money are you spending? He goes, it cost me $4 a month.

01:03:05.660 I'm like, how is that possible? He goes, oh, our energy is totally subsidized by the government here.

01:03:10.800 We pay 19 cents a gallon for gasoline. So it's about $4 a month for me to, at the time, this was more than

01:03:16.300 10 years ago. It's about $4 a month for me to keep my apartment in Saudi Arabia, in Riyadh at 70

01:03:22.480 degrees when it's 120 degrees outside. Now you have to understand something. This is a totally

01:03:27.260 rational human being. This is a reasonable guy who would never do this in his apartment in Washington,

01:03:34.940 DC. It just gave me a great example of how, when we don't have skin in the game,

01:03:42.900 we are incapable of making rational cost decisions. You know, it's like, if I said to you,

01:03:50.000 you can have any car you want, but you only have to pay 5% of the cost of the car. I think you're

01:03:56.020 going to make a very different decision than if I say you can have any car you want, but you actually

01:03:59.940 have to pay for the whole car. Now we can lend you the money and you can do X, Y, and Z. And I guess

01:04:05.320 the thing I've always struggled with, I don't know how to solve the problem of healthcare cost of

01:04:09.520 which oncology is a huge driver. And we're going to get to that shortly. Because I don't know how

01:04:15.400 to reconcile these two points, which is on the one hand, you cannot make rational decisions if you

01:04:21.780 don't have skin in the game. And if the physician and the patient don't have skin in the game,

01:04:27.980 how is a rational decision being made? But on the other hand, with the costs of these things being

01:04:34.000 so prohibitive, how can people have meaningful skin in the game? So how do we reconcile these

01:04:39.800 two forces? Probably not going to have the perfect answer for that. I like what you're saying. And I

01:04:44.500 like your analogy. And I want to kind of expand on it a little bit. So in your analogy, I think you're

01:04:50.140 right that your friend is making the rational choice, which is doesn't cost me much more. It's

01:04:53.900 like a 50 cents. Let's keep it cool all day. Who cares? Somebody else is paying for that. In your car

01:04:58.540 analogy. Yeah. If you only pay 5% of the price of car. Yeah. I'm going to drive a McLaren.

01:05:02.680 I like your choice, by the way. Good choice. McLaren. Thank you for that.

01:05:06.700 Big fan of Top Gear and Grand Tour. But I guess I would say, but to make it really more analogous

01:05:11.340 to what we're thinking about, you pay 5% for the price of the car, but you never actually get the

01:05:16.360 car and you don't get to drive the car. You just get told how good the car is. I'm telling you how

01:05:21.920 good the car is. This is a great car. Don't you worry about how good the car is. You are not in a

01:05:26.140 position to judge how good the car is. Having the car may change what you do. What do I mean by that?

01:05:31.420 When it comes to cancer drugs, in a theoretical situation, I do think people will say,

01:05:36.440 if it adds anything, if there's any upside and somebody else is paying most of the cost,

01:05:40.620 I'm willing to accept that. I want to try it. Let's just try. That's the mantra of oncology.

01:05:45.380 But many of these drugs, that idea that it only has an upside, that is sort of a construct that's

01:05:50.340 been created through a system that is not giving you the accurate information. In fact, some of these

01:05:54.980 drugs, they may actually have a net downside. How might that be? One, they don't actually improve

01:05:59.220 survival. That's one. They have no survival benefit. Two, they may have an opportunity cost

01:06:04.220 that instead of being somebody who in their last few months of life is going to Tahiti or going to

01:06:10.700 visit a friend, I'm somebody who is tethered to the infusion suite. And I got to keep coming back

01:06:15.940 twice weekly for four weeks. I got to keep seeing this doctor. I got to spend 15% of my extra life you

01:06:21.280 gave me. Maybe 40% of that I'm spending in your lobby. You're taking it back from me. And so it makes

01:06:26.020 people make choices about what they prioritize and how they view the end of life that may actually,

01:06:31.400 I think, dissolve whatever ideal benefits that the drugs provide. I mean, your point is well taken

01:06:37.240 that there is this sort of tension between who pays for something and choices people make. And I guess

01:06:42.460 the way I try to get around that is if we could just start an oncology with the choices that probably

01:06:47.540 are not in your best interest, we probably would save a lot of money and people will be better off for

01:06:51.580 it. And then we can go to the next level of choices where there really is that trade-off that you

01:06:54.900 articulate so well.

01:06:56.240 What do you think are the no-regret moves in oncology today?

01:07:01.840 I guess I could do it tumor by tumor. I guess, I mean, if you have localized cancer, for the most

01:07:06.860 part, no-regret move is to cut it out. Surgery, you guys win a lot, no-regret moves.

01:07:11.760 Very little advanced in the last 50 years, right? I mean, where have we gotten better? Well, I think

01:07:16.640 50 years ago, Whipple procedure carried a much higher mortality than today. I think 50 years ago,

01:07:23.220 women were decimated by radical mastectomies that are, I didn't do one radical mastectomy

01:07:29.740 in my residency. So basically for 20 years, that's a procedure that's never been done. And today,

01:07:34.520 there's been a push to more and more and more localized surgeries with just as good an outcome.

01:07:39.600 So that's been a huge advent. But yeah, for the most part, we figured that one out a long time ago.

01:07:44.460 So let's keep doing it. Okay, next.

01:07:47.220 Okay, so next category. So let's get into, I mean, I'm going to make a nod to radiotherapy,

01:07:51.480 which I think is really useful in many situations. Maybe the Michael Douglas situation,

01:07:55.980 heading a cancer, localized, probably anything 4A or better. You know, you get a great shot of a

01:08:00.200 long-lasting cure with chemoradiotherapy. Okay, so I think surgery and radiotherapy are on the

01:08:03.980 table. Now let's talk about drugs. You've got Hodgkin's lymphoma. Well, good news. We've got a

01:08:09.020 four-drug combination that's curative. You've got testicle cancer and it's spread to your lung.

01:08:13.180 Good news. We can cure 95% plus of you. Including those that are non-seminomatous now?

01:08:20.300 Obviously, it depends on the exact subtype. And sometimes you require a combination of both

01:08:24.200 chemotherapy and surgical therapy. So for instance, like teratoma or something like that.

01:08:28.500 CML, chronic myeloid leukemia. This is the Gleevec story that I think is transformative.

01:08:32.960 Some will argue is not cancer, right? The way the skeptic would say, is this a cancer, right?

01:08:37.580 I mean, it's a very fair point, which is that what is CML? It is a blood-based cancer.

01:08:42.160 One of the things about blood-based cancers is you tend to see that a lot sooner than you see

01:08:45.660 other cancers because it's easy to find because it's in your blood. You can just draw the blood

01:08:48.660 and there it is. And if you had that access to every organ in the same way, maybe you would be

01:08:53.160 finding similar malignant lesions in other organs. That's a possibility. We also know it's

01:08:58.360 genomically dumb. It's driven by BCR-able fusion, a genomic event, and not a whole heck of a lot else.

01:09:03.500 That's the sole driver. And if you give a drug that inhibits that fusion event,

01:09:07.380 you can turn median life expectancy from three to four years to nearly normal life expectancy

01:09:12.400 in a Swedish data set. They're living almost a full life, maybe a year shy of normal life

01:09:16.760 expectancy. That is a tremendous advance in medicine. So those are just a few no-brainers,

01:09:21.860 but there are a lot of no-brainers, I think, that have to do with there's a benefit and the toxicity

01:09:26.360 is low, or there's a benefit, a smaller benefit, but the toxicity is reversible. So you could try it,

01:09:32.680 and if it doesn't go well, you can stop it and you don't have them lost too much. I think those are

01:09:35.680 kind of no-brainers, but some things are much more dubious, which they are caustic, toxic treatments,

01:09:43.300 long-term toxicity, toxicities that don't get better, don't go away, that at the best don't

01:09:48.340 add that much. I mean, I think there are a lot of dubious choices that people find themselves in.

01:09:52.760 And I think the other thing that's hard to express is that the person in the chair, the patient,

01:09:58.140 is in a very difficult position. I mean, they didn't spend their lives studying cancer and studying all

01:10:02.820 the data or maybe even studying how to think about cancer data, and they're in a vulnerable

01:10:06.640 position. Their life is on the line, and that's not always a great position to make choices. And

01:10:10.900 people often tend to make choices that may not be compatible with their best interest.

01:10:15.760 Some people make choices that are driven by family members who believe those choices are in

01:10:19.700 their best interest, but they might not be. There's a lot of social complexity here that makes it a

01:10:24.620 thorny problem. But yeah, there are a few no-brainer decisions. There are some real advances in the

01:10:28.960 last 20 years. And then there's a lot of fool's gold. A lot of things people say are game changers,

01:10:33.560 miracles, revolutions that are no such thing, that really don't have those substantive benefits when

01:10:37.960 you look at it critically. Give me an example of something you put in that latter category of

01:10:42.200 something that's getting a ton of attention that you're not a big believer. I mean, where do the

01:10:47.260 cell-based therapies for immunotherapy fit in or something like checkpoint inhibitors like

01:10:52.480 Keytruda, which, I mean, boy, when those things work, they're game changers. And when they don't work,

01:10:58.280 they don't work. Yeah. I mean, I guess I would say, I have a good example that comes to mind,

01:11:04.060 which I will come to, but let me just first comment about those things. I mean, I guess I

01:11:07.280 would say the cell-based therapies or things like CAR-T or tisagenlic lusel or these sort of novel

01:11:12.540 cell products, they still have a lot of promise and they have definitely shown sort of great responses

01:11:17.960 in some people. But the real question will be, are they so beneficial in every condition?

01:11:23.900 We're trying some of those cell-based therapies in multiple myeloma and a lot of people are having

01:11:27.840 remissions, but those remissions are fleeting and it looks like everyone is having relapse.

01:11:31.200 That's different than what we found with lymphoma and what we found with pediatric acute lymphoblastic

01:11:35.360 leukemia, or ALL, which you talked about earlier. With Keytruda, we have a number of randomized

01:11:39.820 control trials that show clear survival benefits in Keytruda in specific settings. We also have a

01:11:44.820 bunch of settings that have been disappointing and we've had confirmatory randomized trials that

01:11:48.180 don't show benefits. So Keytruda might be almost a case-by-case basis. What cancer? What patient?

01:11:52.380 But let me give you a good example of a drug that I think is just a classic example of really a

01:11:57.640 questionable decision. I'll talk about it in one cancer, pancreas cancer. So some people with

01:12:02.280 pancreas cancer have a germline mutation in BRCA gene or BRCA, which is a gene that confers

01:12:07.740 susceptibility to cancers, one of which is pancreas, but often breast cancers where you most think about

01:12:12.460 it. And if you have a BRCA germline mutation in pancreas cancer, they did a randomized trial where they

01:12:17.420 gave people four months of the standard of care, full Firinox therapy, and they stopped it after a

01:12:23.180 minimum of four months. You could have had a little bit more, but they stopped it after four months and

01:12:26.420 randomized you to Olaparib or sugar pill. And if you take Olaparib, you have a progression-free

01:12:31.540 survival benefit, which I can explain what it is in a second, versus sugar pill, but you don't have an

01:12:36.520 overall survival benefit. You're not living any longer. And maybe it wasn't a good idea to stop

01:12:41.980 full Firinox. I think a lot of doctors would have continued that. So the control arm shouldn't have

01:12:46.300 been sugar pill. It should have been continuing the drugs that were working. This is a trial called

01:12:51.100 POLO. This is a drug that has a cost of about $12,000 a month. And the reason the rhetoric and

01:12:58.380 the reality are so separated is that the drugs we were using in pancreas cancer were old cytotoxic

01:13:04.780 chemotherapy drugs. They were drugs that were not sexy, didn't sound so great. And this is a new

01:13:09.800 targeted drug, quote unquote targeted drug. And it's based on your genomic signature, which is unique to

01:13:14.660 just your tumor. I mean, it sounds like that should be terrific. The reality is the data suggest it

01:13:20.020 might not be as good as if you continued that old fashioned therapy. So that's an example where I

01:13:24.700 think that hype can easily outpace benefit. And then I guess I just wanted to just explain real

01:13:29.360 quick for the listener progression-free survival, which comes up just so often in cancer. It's a

01:13:33.580 unique endpoint. It's really often interpreted in the lay press as the time it takes for cancer to get

01:13:38.700 worse. That's not quite right. So progression-free survival is the time from when a patient enrolls on a

01:13:44.260 study to one of four things really happening to them. One, they could die. The first thing they

01:13:49.360 could be going along and then one day they could just die. So that's part of the endpoint. So if

01:13:53.500 you die first, that's it. You have a PFS event. Fortunately for most trials, that's not the most

01:13:58.120 common thing that counts as a PFS event. The second thing that could happen is you have a new lesion on

01:14:02.920 your CAT scan. We're scanning you along and your lungs, we didn't find anything, but now there's a

01:14:07.320 little ditzel there and I stick a needle in it and it's pancreas cancer. So you have progressed.

01:14:11.100 You got a new lesion. That's progression. The third thing that could happen is your tumor that

01:14:16.020 we measured at one centimeter, it got to 1.2 centimeters. It got 20% bigger. The moment it

01:14:22.320 gets 20% bigger, 21% bigger, it's progression. When it's 19% bigger, oh, it's stable disease.

01:14:28.180 That's what we call that. That's stable. But the 20%, 21%, that's progression. So it's an arbitrary cut

01:14:33.620 point, very arbitrary. And that's why it doesn't always track with how people feel. The fourth thing that

01:14:38.080 could happen is your tumor got smaller before it got bigger. And if your tumor got smaller before

01:14:43.000 it gets bigger, it's 20% from the smallest it ever was. So those are the four things that count as

01:14:48.780 progression. Often trials are driven by the latter two events. The tumors look 120% bigger. I like to

01:14:56.020 also tell people that when you measure a tumor on a CAT scan, if you haven't done a lot of that,

01:15:00.520 I'm sure you've done that, but if you haven't done a lot of that, people think it's like measuring

01:15:03.460 your height. It's a lot more like measuring the width of a cloud between your fingers, looking up

01:15:07.640 at the sky. People have dispute about where the tumor ends and where the normal tissue begins.

01:15:12.320 And that's been shown in many studies. So the reason I say all this is, let's go back to that

01:15:16.020 example, that drug. This is a drug when tested against sugar pill in a setting where probably

01:15:20.860 shouldn't have been tested against sugar pill, it should have been tested against a real therapy we

01:15:23.760 do. The only thing it could improve was the progression-free survival, which is an arbitrary

01:15:28.640 line in the sand for tumor growth that really doesn't measure people living longer or feeling

01:15:33.860 better. That's why I think it's really sort of a problematic drug.

01:15:37.280 Yeah, I remember. God, how many years ago? Was that five years ago or four years ago when that came

01:15:41.360 out? This trial actually is more recent than that. It was just in the last year, but they probably

01:15:45.380 started it five years ago. The enthusiasm for it was there, and they started down the path.

01:15:49.520 I think I'd followed that drug maybe back at its phase two, and I don't know why. For some reason,

01:15:54.160 I felt like that was a fool's errand, but it seems like that just sort of concludes it.

01:15:58.640 So, there are a couple things I want to come back to, but before we do that, I want to go back and

01:16:03.340 talk through your hallmarks, because this strikes me as sort of the culmination of all the work you

01:16:09.960 kind of put into this book, and you sort of, you do what everybody's doing when they're writing a

01:16:14.580 book. You're probably putting the finishing touches on it, and you have this epiphany, and you

01:16:18.660 realize, well, I could sort of go and weave it into the narrative of the book, or I could very

01:16:23.280 concisely kind of lay it out here, and I think you chose the latter, which is actually quite

01:16:26.520 elegant. So, walk us through the notion of these hallmarks, these six hallmarks, and explain what

01:16:32.960 they mean, because they're not entirely obvious just from the brief description.

01:16:37.480 Sure. Thanks for that. I guess I think one, you're really right about how it happened, which was

01:16:42.220 you write a book, and people think you write the book, but of course, there's so much back and

01:16:45.300 forth, and it goes on for years. And where you are emotionally and mentally when you finish the

01:16:49.780 book and where you started are very different places, and often you grow a lot in the process of

01:16:53.440 writing it, it changes the way you think about things. And so, I start in this chapter by saying,

01:16:57.960 here's a way I should have said things all along. I could have said things better. But at least for

01:17:01.840 my case, it's better late than never. I could still toss it in the book. And I think the other

01:17:06.000 thing the listeners should know is there is something called the hallmarks of cancer. These

01:17:09.960 are six things proposed by Hanahan and Weinberg. There's six hallmarks of cancer, like invasion,

01:17:15.100 invasion of the basement membrane, poor immune surveillance, angiogenesis, one of the ones you

01:17:18.660 mentioned. These are sort of six biological hallmarks of cancer. And that is a highly

01:17:23.300 influential paper, and it's been really extremely well cited and has shaped a lot of people thinking.

01:17:28.320 It might be one of the most cited papers in oncology, isn't it?

01:17:31.220 I think it might be. I think you're right. It might be, in fact, the most cited paper in oncology.

01:17:35.080 So anyway, so like all great things, I try to steal from them. No, I try to imitate. When I finished

01:17:41.140 this book, I realized that, well, you know, I'm not talking about biology. And in fact, I say many

01:17:45.060 times it's not a cancer biology book. This is a book about policy, our rules, our laws,

01:17:49.020 our guidelines, and how policy can make things better. And I realized that maybe policy can

01:17:54.280 be distilled like biology to six essential hallmarks, six ways in which we might make

01:17:59.520 things better. And so I guess I'll take you through the six. I guess the first of the six

01:18:03.240 was independence. What do I mean by this? So I guess one of the things in the book that

01:18:08.620 I spend a lot of time talking about are conflicts of interest, ways in which the industry gets

01:18:14.620 people who should be sort of competitors with the industry or should be stakeholders

01:18:19.100 that push back on the industry. It gets them to buy into the industry's narrative in part

01:18:22.860 because they fund those stakeholders. So talk about patient advocacy groups are often heavily

01:18:27.160 funded by the industry, how FDA employees who you think should be sort of separated from

01:18:32.020 the industry, their most common place of employment after the FDA is the industry. And so they kind

01:18:36.340 of have a unique role as regulator, but also future employee. So I call independence is we need

01:18:41.900 sort of some rules in the space to, I think, minimize conflict of interest and to allow entities

01:18:47.560 to be free to advocate for their constituents. Probably the biggest offender is expert oncologists

01:18:52.580 like me. In my case, unfortunately, I don't receive money from the pharmaceutical industry.

01:18:58.260 However, I think that's not the case for the majority of expert oncologists. They do.

01:19:01.900 And their views are often very supportive of these questionable drugs. They're almost at times

01:19:07.100 as if they're cheerleaders. And I believe that some of that is driven by those sort of financial

01:19:10.980 ties. So I guess the first one is independence. How does one do anything about that? Maybe we'll

01:19:15.840 probe each one a little bit as opposed to just going through them. So completely get your point

01:19:20.600 there. Look, I mean, when I was in residency, drug reps brought us lunches. Oh yeah. Right. And gave

01:19:27.700 us pens. Like, you know, something as silly as that, but that's a hook. Yeah. It's a little bit of a

01:19:34.720 hook. It's a little bit of a hook. It's who has the coolest pen? Because these weren't just

01:19:40.500 generic pens. These were like really cool pens. Like you want it to be there at that lunch and

01:19:44.480 get that really cool pen. It was like, I remember some of them to this day, like a pen that looked

01:19:49.260 like a needle syringe. And when you clicked it, that color changed and all these other cool things.

01:19:54.100 And, and look, all they wanted was five minutes of your time. And I remember by the end of residency,

01:19:59.080 some of those, they were starting to take us, the senior residents out for dinners.

01:20:02.880 And I got to be honest with you, I don't recall giving it any thought. Like I don't recall actually

01:20:10.900 feeling like I was doing something wrong. I remember being kind of annoyed that I had to

01:20:17.600 listen to them talk. Cause at that point in my life, I feel like the only thing that mattered

01:20:20.900 was getting a meal. And I was sort of like, Hey, why don't you just shut up and let me eat?

01:20:24.580 Let us enjoy. Yeah.

01:20:25.720 But I honestly don't think it crossed my mind, Vinay, that this is the beginning of a very

01:20:32.160 slippery slope. They're not buying me lunch, giving me pens and eventually buying me dinner

01:20:38.420 because they think I'm a nice guy. I find that a little bit disturbing that I was too stupid to

01:20:44.380 see through that. I'll, I guess I'll give myself some grace and say the sleep deprivation

01:20:48.660 may have played a role in it, but have things changed in the last 20 years? I assume that pharma

01:20:54.420 is not allowed in a hospital anymore. Well, in many, but not every place, but I guess I'd say

01:20:59.400 a couple of things about that. One, I guess I don't blame you so much. You're a resident at the

01:21:02.520 time. And to be honest, I actually don't know what you described, although it is problematic.

01:21:07.180 Those pens are collector's items. So if you have any good ones, send them my way. No, just kidding.

01:21:11.080 They really were spectacular. They really were, many people did collect them. And the next thing I

01:21:15.160 would say is that there is evidence that shows even so much as a meal that is paid for by the

01:21:19.720 industry is associated with a statistically significant, but very small increase in prescribing

01:21:23.520 patterns. So it, it is a strategy that pays dividends. I guess I would say that I see the

01:21:28.620 problems with that. And I think that they are problematic and they have largely been curtailed

01:21:32.240 through a number of sort of well-intentioned efforts. But one of the things I talk a little

01:21:36.180 bit about in the book is that we haven't yet curtailed things on the high end. So here we spend a lot of

01:21:42.040 time trying to reform on the low end, the people getting the pens and the meals. There are many senior

01:21:46.780 oncologists who receive over a hundred thousand dollars a year in consulting payments from companies,

01:21:50.700 even more. They receive millions of dollars in research funding. We have shown in some

01:21:54.860 publications that even controlling for research funding, controlling for prior publications,

01:21:59.680 but controlling for seniority, personal payments from the industry are associated with greater

01:22:03.880 publication in the future. It's likely it's a positive feedback loop. Working with the industry

01:22:07.940 helps your career, which helps you work with the industry, which helps your career. The people in

01:22:11.600 those roles, the most conflicted people, people who are earning as much from the industry in their

01:22:16.760 side hustle as the average household income in America, those people, they write the guidelines

01:22:21.560 and the guidelines by law in the US make Medicare pay for drugs for off-label purposes. So the people

01:22:28.560 who write the guideline that mandates Medicare must pay for this drug, no price negotiation. That person

01:22:34.820 is being paid by the industry, even for the exact same drug. And so those relationships, I think,

01:22:39.940 are an order of magnitude more concerning than the resident, hungry resident taking a meal. In fact,

01:22:45.020 I try not to talk too much about those sort of little things. But I think you're right that

01:22:48.300 there is a slippery slope. And part of it is to get you accustomed to the fact that this is no big

01:22:52.480 deal. So I think you're absolutely right. I guess I would say the way I would sort of structure the

01:22:56.980 solution is the way I sort of structure lots of solutions, which is I don't want to be the person

01:23:00.740 setting rules and hard rules with punishments, because I don't think that that's really what gets

01:23:05.380 people to change behavior. I want to create a different set of incentives that get people to maybe do

01:23:10.040 something differently. And so some incentives, I think, are we still need guidelines to help decide

01:23:15.180 what to cover off-label. Why don't we incentivize people who don't have conflict to join those

01:23:20.200 guidelines? And what if we had rules and policies that favored faculty members who didn't take money

01:23:25.720 from the industry to be on the guidelines? Suddenly, career incentives look very different. I mean,

01:23:29.920 right now, if I'm a junior faculty member and Eli Lilly offers me sort of an ad board consulting

01:23:34.360 opportunity, I might jump at it and I can still have open the opportunity of sitting on a

01:23:39.140 guidelines committee. But maybe in exchange for one opportunity, I should lose the other

01:23:42.920 opportunity. And if I want to keep the other opportunity, it's my choice. And the more you

01:23:46.540 kind of build in those kind of structural incentives, I think people will do things that preserve different

01:23:50.660 opportunities. So I think that's sort of one way you tackle the problem of conflict of interest,

01:23:55.540 which is that you just sort of tinker with incentives, you create opportunities for academics to not take

01:24:01.580 money and still have robust and rich careers. I think in the current system, all the opportunities are tied

01:24:07.120 to taking money from the industry. And so I guess how can I blame anybody? Just like I don't blame

01:24:11.280 the industry for putting a thumb on the scale. I guess I don't really blame the faculty members

01:24:14.840 for doing it. Is there evidence that physicians are, for the most part, honestly disclosing these

01:24:22.600 things? I mean, I know there was a very famous case at Memorial Sloan Kettering where there was a

01:24:26.840 huge blow up over this. So if a system like the one you described were in place, do we believe

01:24:32.800 that we could believe people? Yeah, that's a great point. I mean, I guess I would say that

01:24:37.120 most of the available evidence suggests that disclosure is incomplete and often inaccurate.

01:24:41.340 Some of the available evidence suggests that people don't even believe that they have the

01:24:44.900 conflict. And so some of it is an honest error that they don't even see that they're being

01:24:48.100 conflicted. They may have forgotten. You cite a really sort of high profile example of Jose

01:24:52.180 Baselga, who had found to omit conflicts in dozens and dozens of articles and conflicts that

01:24:57.180 were really pertinent to what he was talking about. And he ultimately was pushed out of his role

01:25:01.780 at Memorial Sloan Kettering, which is a form of punishment. But very shortly, he became vice

01:25:06.320 president of AstraZeneca, a job that probably pays him several times as much money as he was

01:25:10.420 making earlier. So I hope someday somebody punishes me in the same way and pushes me out

01:25:14.900 of my job, but then pays me a whole lot more money to do something in the same space. I want to be

01:25:18.400 punished like that. But I mean, I think that speaks to the fact that we don't really take

01:25:23.000 disclosure seriously. I guess the other thing I would say about disclosure is disclosure has been

01:25:26.940 one of the methods that we have confronted conflict of interest with, but I'm not exactly sure it

01:25:31.020 makes the world better. There's some psychology evidence, some business evidence that suggests

01:25:34.700 that once people disclose, there may be actually greater trust placed in the discloser. And it

01:25:40.940 doesn't actually correct, I think, the bias. It just leads the patient to have more trust in their

01:25:46.000 doctor, having seen the doctor disclosed. So I think maybe divestment is a better way,

01:25:51.000 maybe sort of different rules and incentives for people is a better way to kind of separate these

01:25:55.720 things. I think that these conflicts are problematic in one respect that I'll kind of flesh out a little

01:26:00.360 bit. So in cancer medicine, so often you got a drug that costs $100,000 a year, and it changes

01:26:05.220 something like how big the tumor is on a CAT scan with all the problems of measurement. We don't know if

01:26:10.420 you live longer, we don't know if you live better, and you got to take the drug. Who decides whether or not

01:26:14.940 we should recommend that routinely or not? That guideline decision is of huge importance. It will shape how

01:26:20.020 many, many people practice. And I want people to make that decision who are oncologists who have

01:26:24.540 experience, who may know a lot about how to read studies and interpret data, but who don't have any

01:26:28.960 financial relationships with the company that makes that product. I think that leads to just sort of a

01:26:33.480 cleaner decision making process. And it's the same kind of way we set up a courtroom. Can you imagine

01:26:38.440 a courtroom where the prosecutor and the defendant are both being paid by the defendant? I mean, I think

01:26:42.760 many of us would say that's not really a balanced courtroom. And yet in medicine, we do have many

01:26:47.180 imbalanced courtrooms where almost everybody in the courtroom is getting money from the company. And so I

01:26:52.540 guess I'm just suggesting that we don't take away the industry's incentive. We keep the profit. Of course,

01:26:57.280 I think it does drive innovation, but we remove it from the people that supports to provide

01:27:01.960 opposition force and try to preserve a healthy sort of dynamic there.

01:27:06.560 What is the opposition to your idea, which is so obvious it's painful to listen to you articulate it?

01:27:12.340 The opposition is probably principally that the people who are best in the position to fix the

01:27:17.640 situation are the ones who are personally getting the most money. I mean, I guess I'd say that our

01:27:23.460 professional societies are driven by the industry payments. The professional societies, senior

01:27:27.700 leadership at universities and academic medical centers are often on the boards of directors of

01:27:32.100 companies. They're the ones getting the biggest payments. The most senior and famous oncologists are

01:27:36.260 the ones getting the most money. And so I think it's hard in any system where the people you need on your

01:27:41.280 side to change the system, the people with the power are the ones benefiting most from the system.

01:27:46.100 Doctors are smart people. We can all come up with reasons why what we're doing is not bad.

01:27:49.520 And in fact, probably I believe this, it might be true for everybody. We all believe we're all

01:27:53.280 ethical actors. I mean, I don't think anyone thinks that they are an unethical person. They

01:27:56.560 just feel that they're a product of their circumstances. And so I think the real way

01:28:00.200 to fix this problem is somebody external to the medical profession has to come in and do it.

01:28:04.580 I don't think it's ever going to happen from self-policing because the people who are in power

01:28:08.180 are the ones who are getting the most payments. And very likely the case that there's a reason why

01:28:11.820 they're the ones getting the most payments is because the industry knows that that's what it takes to keep

01:28:15.640 the system going. All right. So the second hallmark. Okay. Second hallmark. Evidence.

01:28:21.140 Yeah. What does that mean? Evidence is, I describe it as measure what matters and do it fairly.

01:28:26.440 There are a lot of technical things that I won't get into for this podcast that I talk about in the

01:28:30.360 book. But I guess basically evidence is the following, that when we give cancer drugs, we care

01:28:34.660 about two things, people living longer or living better, increased survival or health-related quality

01:28:39.140 of life. We have a system where two-thirds of cancer drugs that are being approved, one-third,

01:28:44.140 I know they shrink tumors more than 30% in a fraction of people. The other third, I know

01:28:50.040 they delay tumor growth by 20%. And then the other third, I know you live longer, live better.

01:28:55.020 That to me is a strange reorientation of you're spending so much money on costly drugs. Only

01:29:00.040 one-third do you measure what actually matters to people. The other two-thirds, you're measuring

01:29:04.200 tumor size on CAT scans. And I'll say one more thing that I think is interesting here, which is

01:29:08.800 we use this cutoff of tumor shrinkage of 30%. In writing this book, I spent a lot of time

01:29:13.980 trying to get the bottom of why it is this 30%. And I found out it goes back to a 1976

01:29:18.700 paper where this Mayo Clinic doctor got a bunch of marbles and he put them on a dining table

01:29:23.480 and he rolled out foam rubber. And he got 16 oncologists to come to his house with calipers

01:29:28.000 and measure the marbles. And he asked, at what size difference can two doctors reliably tell

01:29:33.840 the marble has gotten bigger or gotten smaller? And the answer was certain cut point. And that

01:29:38.260 cut point is the same cut point we use today. We use a cut point to measure tumor shrinkage

01:29:44.020 as a response or not response because a bunch of men in 1976 measuring marbles through foam

01:29:49.840 rubber, which was how we measured tumors in the day before imaging, that's what they could

01:29:54.560 tell apart. So these cutoffs that we have sort of confused as measures of efficacy were really

01:29:59.780 just sort of operational measures to sort of get some inter-rater reliability, get us to

01:30:04.140 agree. And so the moment you start to know that, you realize like, why am I putting so

01:30:07.940 much stock in drugs with a 10%, 20% response rate? I really don't know if the patient lives

01:30:12.080 longer, lives better. And this cutoff is really arbitrary. So that's what I mean by evidence.

01:30:16.540 Let's measure more, not always, but more what matters, living longer, living better.

01:30:21.660 And what would be the implications of that? I mean, it basically would imply that two thirds

01:30:26.300 of the treatments out there go in the waste bin.

01:30:28.720 At least they won't be approved at the same moment in time. So what might happen is that

01:30:34.320 if you really created a policy where generally the industry is obliged to show survival or

01:30:39.000 quality of life benefit, a lot of things are going to change in the industry. So one thing

01:30:43.140 is they're going to run more trials in patients who have relapsed cancer than trials in patients

01:30:48.700 with low risk, early stage cancer. They're going to go into the last line setting because

01:30:52.140 that's where the event rate is highest. They're going to be more selective. I think about drugs

01:30:55.900 that they deploy. They're not going to deploy drugs that may change tumor scans. They're really

01:31:00.900 going to try to think about drugs that improve survival or quality of life. So they might be

01:31:03.720 more picky in which drugs they advance in the process. I think it changes a number of things

01:31:07.620 in the drug development pipeline. And I guess I kind of talk about that in the book, but to your

01:31:11.260 point, which is, does it actually change the number of drugs that come to market? I guess I would say

01:31:15.120 that of those two thirds that just changed tumors on scans, maybe some of them actually do help you

01:31:19.900 live longer and live better. Those are still going to come to the market, but the ones that don't are

01:31:23.560 going to fall short and they're not going to come to the market. So we'll have probably fewer drugs

01:31:27.060 come to market, but the drugs we have will probably be better drugs. My friend who posed that dilemma

01:31:31.660 to me many years ago, he'll probably be more satisfied. All right. What's the third hallmark?

01:31:36.800 Yeah. The third hallmark is something that we've talked a lot about on this podcast. It's called

01:31:39.760 relevance. And it basically means that we should do more studies in people that look like average

01:31:43.820 Americans. And I think we kind of talked about how we're studying populations that don't reflect what

01:31:48.140 average people have and experience. Why don't we just study average people and let's find out if the drugs

01:31:52.560 work as we prescribe them. And again, that'll have the same effect, which is it's effectively going

01:31:57.760 to reduce the success rates probably due to both decreased tolerability and actual poor response.

01:32:05.760 Yes. I think that that's the case. Yeah. Okay. The next one is near and dear to my heart.

01:32:11.180 Affordability. Tell us about that. How do we fix that issue?

01:32:14.900 That's a thorny problem. We've written a number of review articles that have looked at so many different

01:32:19.320 solutions. I mean, I can't even get into all the solutions just to put them in a few buckets.

01:32:23.520 They're solutions that rely on existing legal structures to make progress here. They're solutions

01:32:29.320 that require novel legal structures. One solution, I think maybe one of the clearest solutions here is

01:32:35.640 that in the US, we have a system that anytime a cancer drug is approved, Medicare, which is perhaps

01:32:41.260 the single largest payer in this country, Medicare has to pay for the drug and they can't negotiate the

01:32:45.760 price. Not only that, they have to pay for any drug recommended at a level 2A or higher by a number

01:32:51.280 of guidelines like this National Comprehensive Cancer Network, which has got a lot of people

01:32:55.620 writing the guidelines who are funded by the industry. So I think one way we could kind of

01:32:59.080 make some headway in the affordability is to give Medicare the ability to decline to pay for drugs.

01:33:04.240 Many years ago, a couple of states went to Seema Verma and colleagues at HHS and they said,

01:33:08.640 let us at least experiment. States are the laboratory of experiment. Let us say Massachusetts doesn't

01:33:13.720 have to cover all these drugs for Medicaid, but they were denied the ability to experiment

01:33:17.820 at a state level. I think we should encourage state level experimentation and how to bring down

01:33:21.560 drug prices. And there are a number of other things that are really sort of technical solutions.

01:33:25.620 But I guess what I think is important here is just the recognition that a drug that you cannot

01:33:30.880 actually get in the hands of somebody is no better than no drug at all. And we have affordability

01:33:35.140 crisis in this country, but globally, we have a huge affordability crisis. These drugs,

01:33:39.940 for the most part, are out of reach of billions and billions of people in this world. And so it's

01:33:45.960 one thing to live in 2020 when you have access to the greatest medicines. It's really sad, I think,

01:33:51.160 when there are some drugs that are transformative and the best centers globally just really do not

01:33:57.180 have access. And in the book, I give example of trastuzumab, a drug developed in the late 1990s

01:34:01.920 for a certain type of breast cancer that is really a terrific drug. But in a study that came out of

01:34:07.280 India just five years ago, only one in 100 people who could have gotten that drug got that drug. And

01:34:12.320 this is at a referral center in sort of the one of the biggest cities in the country at a really

01:34:16.460 sort of premier center. And it's still so difficult out of reach of so many people globally. I think

01:34:20.800 that's a real tragedy. Do we have a sense of on average, how much more a drug cost in the United

01:34:27.360 States than, say, in Europe or Asia? Yeah, I mean, I guess, I mean, a couple figures are,

01:34:32.940 of course, of the pharmaceutical space. About 50% of spending in the U.S. comes from the U.S.,

01:34:37.400 even though we count for maybe 4% of the world's population. And how much of that do we know if

01:34:42.500 it's volume versus price? Like, obviously, there's an accessibility issue, which says in the United

01:34:47.460 States, you're going to, on a per capita basis, more people are going to receive the drug as well.

01:34:52.160 It just seems like, as a casual observer of oncology, that basically the United States

01:34:58.200 kind of has a sort of tacit quid pro quo with pharma, which is, here's the deal.

01:35:05.280 Do the lion's share of the R&D inside the United States. Let us have first access to the drugs.

01:35:12.700 We're going to subsidize the cost for the rest of the world. Directionally, that seems to me

01:35:17.640 what's happening. Is that about accurate? That is a fair summary of the lay of the land.

01:35:22.780 I guess I say a couple things. I mean, one of the points you made earlier was,

01:35:25.560 what about the price versus volume? I mean, I think one helpful comparison would be like two

01:35:29.300 nations with comparable GDP, U.S. and Norway, and we pay roughly double what Norway pays for

01:35:34.360 cancer drugs. The other thing I would say about subsidization is, I think people like me who are

01:35:39.720 reformers, I guess the real question I have in my mind is, why do we subsidize marginal drugs the

01:35:46.280 same way we subsidize transformative drugs? I think that's the kind of crux of the space.

01:35:50.540 You named a couple of drugs. Avastin. This is a drug that has multiple approvals in many

01:35:55.200 different tumor types. It doesn't cure a single person. Median survival about one to two months,

01:35:59.260 a tremendous price. Global lifetime earnings of that drug are close to $100 billion. I mean,

01:36:04.460 that is a massive global lifetime earnings drug. You get another drug, Gleevec. It doesn't cure

01:36:09.220 everybody, but for the cancers it works, and it works rather dramatically. Massive transformational

01:36:13.580 benefit, and I don't know off the top of my head, lifetime earnings, but it's still in the several

01:36:16.720 billions and billions of dollars. And then you get drugs that are really marginal,

01:36:20.960 toxic drugs that don't do that much and still can accrue billions of dollars. I guess what I want

01:36:26.200 to say is that one of the ways in which I think we can correct the market here is if we just

01:36:31.260 incentivize the drugs we want, which are drugs that have bigger benefits, more substantive benefits,

01:36:35.660 and if we didn't pay so much for those drugs that really don't add a lot, don't cure people,

01:36:40.600 and just prolong survival very modestly in very select cohorts. So I guess I'm not opposed to paying

01:36:46.400 for things that really do work. I guess I'm opposed to paying for things that we don't know work,

01:36:51.220 that have a lot of uncertainty, or that we know don't work. I think that's more what my criticism

01:36:54.880 is. Yeah. And it's funny. I find myself struggling with this one a lot because on the one hand,

01:37:01.220 I really do agree that pharma needs to be incentivized to innovate, and the cost of innovation

01:37:06.680 is staggering. Now, that said, I also think pharma grossly overstates the risk they're taking.

01:37:12.000 I mean, they've basically outsourced research to biotech. So if you really want to think about it,

01:37:20.440 drug discovery is now a venture capital problem, which means it's a private citizen funded risk.

01:37:26.760 So private citizens and pensions basically fund VCs that take the risk to take biotech from IND to phase

01:37:37.880 one to phase two. Pharma then says, okay, this is de-risked enough. I'll come in and on my balance

01:37:44.500 sheet, I can do phase three. So their success rate has gone way up. That seems to be a pretty

01:37:50.000 efficient model, I guess. I think pharma has basically decided we don't want to own all of

01:37:55.220 those risks. We don't want to own technical and market risk all the way through. But the flip side

01:38:00.640 of that is, do we really want CMS? And you'll have to forgive my skepticism, but I don't know that

01:38:06.620 I trust CMS to be the one negotiating price because what's the knockoff effect of that going to be in

01:38:12.780 terms of incentivizing pharma? Even though I agree, CMS shouldn't have to pay sticker price. Like,

01:38:18.860 I guess this is why I'm so glad I don't do what you do because these are some of the hardest

01:38:23.500 decisions one has to think through. If you're trying to do this through the lens of what is a policy,

01:38:28.180 what is a logical and reasonable and fair policy around the incentives? It seems obscene that CMS

01:38:34.720 doesn't have the ability to negotiate. But at the same time, I don't know that I want anybody in the

01:38:39.960 US government making a decision when it comes to healthcare because I've stopped trusting these

01:38:44.720 entities. Just using Congress as an example, right? I mean, we've got, what, 550, 600 people make up

01:38:52.420 the US Congress. Like two of these people have a degree in science. Oh, yes, it's tragic.

01:38:58.520 They're just not a group of people I want ever making scientific decisions.

01:39:02.720 Same for the Supreme Court. Yeah.

01:39:04.960 Yeah. Yeah, exactly. So how do we think about balancing that? Is your solution of let the

01:39:10.680 states do it better where there's less collateral damage? But I can also think of ways that that

01:39:16.720 goes sideways also. Yeah. I mean, I guess I would say that, I mean, one thing to acknowledge is that

01:39:21.700 no one has solved the problem. So the problem remains unsolved. I guess the next thing I would say

01:39:25.600 along these lines is that having a CMS the way we have a CMS, it is a certain type of incentive.

01:39:32.080 It's a very interesting incentive. The incentive is basically, we will pay for any drug that gets

01:39:36.880 FDA approval, whatever you charge. So companies will always keep cranking it up as much as they

01:39:41.500 can. And some of the things about how they crank it up, they'll crank it up in lockstep. So they'll

01:39:45.020 all move together upward. They won't go too much. Nobody will be an outlier because then you're

01:39:48.960 going to be on 60 minutes and that's no good for your brand. So you want to go up together slowly,

01:39:52.980 but you can keep cranking it up. You can do a 9% year over year, over year, over year. And when the

01:39:57.180 frog doesn't jump out of the pot when the water boils slowly. So that's one. Two, then the next

01:40:01.620 thing they build into CMS is once the drug is approved for one use, we're going to let CMS pay

01:40:06.420 for the drug for any other use if these expert doctors believe it should be used in that way.

01:40:11.340 And we're going to detail those expert doctors and give them a lot of money and make them come

01:40:14.160 on our side and they're going to see things from our point of view. So we're going to get all that

01:40:17.180 market share that way too. And sometimes that market share can be even more lucrative than the

01:40:20.320 initial approval market share. So I guess what I think this creates in the system is an

01:40:24.340 incentive, a powerful incentive that the hurdle for a drug is drug approval. You can charge whatever

01:40:29.440 you want. You really don't have to look too deep into like what it costs you to make the drug or

01:40:33.280 what the benefit of the drug is. You can charge what you want. As long as you're not too much of

01:40:36.580 an outlier, you're not going to stick out too much. We had that drug, the CAR T cells, they cost $300,000,

01:40:41.220 $400,000, but then they'll rationalize and say, well, it's a one-time dose. You know, it's not every

01:40:44.900 month after month. And those other drugs, they cost $200,000 a year anyway. Well, of course, that's how you got us to

01:40:49.380 where we are. So I guess what I would say about CMS negotiating is, I guess I think

01:40:53.900 I want to say that not negotiating is a decision of sorts. It's a decision to just really put a lot

01:41:00.020 of incentive here without any sort of care as to what you're incentivizing. You're incentivizing

01:41:04.800 an approval. The next piece of that puzzle is, well, how are they approving drugs? And I think

01:41:08.700 many of us who look at the FDA approval process will see that the bar for approval is getting

01:41:13.420 lower and lower. You used to be able to trip on it. Now I think you can probably go over right over

01:41:18.080 it, but it's getting lower and lower. I mean, the number of patients for approval,

01:41:21.040 not having a control arm. There's a drug, which I always forget the name. It's a drug that lowers

01:41:26.680 the rate of a blood protein, but almost everybody who takes the drug suffers ocular impairment and

01:41:31.520 some people suffer severe ocular impairment. So there's a lot of blindness going on or pre-blindness

01:41:36.120 like conditions, but I don't know if people live longer. I don't know if they live better. I know

01:41:39.360 they have to see the ophthalmologist a lot that adds more healthcare costs, costs a ton. Why is this

01:41:44.840 approved? I mean, why can't we wait for a little bit better data? So I think that's part of the puzzle.

01:41:48.340 I think that among the many ideas out there, one idea is sort of the value-based pricing model,

01:41:54.560 which a number of sort of commenters have kind of developed, which is this idea that we should pay

01:41:58.500 more for drugs that provide us more value, that have more incremental survival benefits than drugs

01:42:03.200 that are more modest or mediocre. And I think if there's some way in the system to build in greater

01:42:09.100 incentive for the drugs we want, well then that would be good. It would have a lot of good secondary

01:42:13.460 effects. But I agree with you that all policy, it's so hard because there's always unintended

01:42:18.900 consequences and people will always sort of find paths of least resistance. You couldn't

01:42:23.480 foresee. The reason I do like state-level expansions, state-level initiatives is that to

01:42:29.100 some degree, good policy is experimentation. You experiment, you see what happens, you course

01:42:34.080 correct. You run experiments in parallel, you see what works, you adopt that broadly. I think you do

01:42:38.540 need experimentation in the policy space. And in medicine, we've suffered because we have not done

01:42:42.920 enough of it in the long run. Now, if CMS makes up, I don't know, I have no idea what it is today,

01:42:48.340 but let's just say it's 25 to 35% of the payer in the world, in the United States, right? So 25 to 35%

01:42:55.240 of all insurance is CMS. What about the private payers? Why have they not banded together and say,

01:43:02.840 well, there's no law that's preventing us from negotiating with these clowns. We're going to do it.

01:43:06.740 Now, I know that part of it, of course, is that the majority of their business is probably ASO. So

01:43:11.620 they're not on the hook for risk. They don't care. I mean, they're basically administering a service

01:43:15.900 and it's the employer that's doing so. Is that why? Is it just, is there's no one big enough to

01:43:22.520 negotiate? Clearly CMS is bigger than any one entity. Yeah. I think there's probably a couple

01:43:28.040 reasons why we haven't seen more activity from private payers. One is that if they don't cover what

01:43:34.920 CMS covers, I think they will look bad and they can easily be on the nightly news where you find

01:43:40.180 a cancer patient who's angry that they didn't get some drug or the other, and that's not good for

01:43:44.040 your brand. That's not good for your reputation. And there have been some high profile situations

01:43:47.760 in the last 30 years where people went on the news and I think insurers, they may not want to take that

01:43:52.320 risk. And the next thing is some of these drugs may cost a lot, but the budgetary impact might be a

01:43:57.060 little bit lower to the insurer because it's a small population. So in those cases, it might be cheaper

01:44:00.660 for them just to pay for the drug than it is to deal with the pushback from not paying for it. I think

01:44:05.080 the worst thing is that the insurers may have a different incentive altogether. What do I mean? One of the

01:44:11.580 provisions of the Affordable Care Act was to cap the amount of profit that could come off revenue

01:44:17.000 through an insurance company, 20% profit on revenue, the medical loss ratio, the MLR. The moment that that is

01:44:23.080 inserted into a system, it's a really unique incentive. The industry, the insurance industry, now they're being

01:44:29.540 told that no matter what, you can never earn more than 20% profit on revenue. That's the most profit you can

01:44:34.580 earn. That's a law. So if I tell you, you're really hungry, and you can only eat 20% of the pizza, what size

01:44:40.760 pizza should I order? The answer is gonna be extra large. So what I think has happened in the insurance

01:44:45.340 industry is that although we hear a lot about insurers who have preauthorization requests and all these things

01:44:52.140 that are a pain in the ass for doctors, and doctors hate, although we hear a lot about insurers pushing back on

01:44:56.920 this or that, I think they do that for a couple of reasons. One, that the insurer's incentive is to

01:45:01.580 make sure year-to-year variability of costs is predictable, and that they can model that out and

01:45:06.780 make sure their premiums go where they need them to go to ensure their profit revenues. They're really

01:45:11.440 nervous about year-to-year variability, and that's why hep C drugs come along, and they can blow the

01:45:15.380 whole model because the population is massive. But I think the insurers in the long run keeping costs

01:45:20.920 down, I think that they may not have enough skin in the game. They don't have enough skin in the game

01:45:24.980 to keep costs down, so they really don't care. And so I think the narrative is, of course, that insurers are the

01:45:30.740 downward force, but I don't think they're the downward force that we think they are.

01:45:34.340 I agree with you, and I think it's the employer that has the most skin in the game, but the problem is

01:45:41.300 they're so disaggregated and so spread out that they can't speak in a unified way, and they can't fight in a

01:45:48.380 unified way. But if you were to look at the sort of, this is a loose way to think about it, but let's

01:45:54.740 just call it a handful of buckets of insured. Medicare, Medicaid, private insurance that is

01:46:02.440 administered only through the insurance company, so the ASO employer-based versus the insurer-based

01:46:09.740 insurer, private insurer. I think the biggest one has to be the employer. And even if it's not,

01:46:16.060 it's the one that would have the most sway. But yeah, it's like, how does this company of 300 people

01:46:23.220 band together with this company of 1,000 people and that company? Which, again, I think speaks to

01:46:29.260 the pain of all of this. One last thought on this space is there's also a tragedy of the commons

01:46:33.760 problem. Many years ago, when autologous stem cell transplant for breast cancer gained popularity,

01:46:38.920 there were a couple of insurers that did pay for some of the clinical trials that ultimately debunked

01:46:42.960 that procedure. But now one of the risks is, let's say there's some new drug out there and a lot of

01:46:46.960 people say like, this is not, it doesn't work so well, this trial is really contrived. An insurer

01:46:50.840 could come along and they could do the right study. They could really test how it works in a different

01:46:55.000 population. They could fund such a study. The moment they fund that study, that information is

01:46:58.420 generated, well, all their competitors will get access to that information. So there's a bit of

01:47:01.780 that challenge as well. But yeah, I mean, I think you're asking terrific questions about this space.

01:47:06.660 So let's get back to hallmarks. Number five is possibility. What does that mean?

01:47:12.200 I guess I call it the preclinical pipeline must be expanded. Possibility. So I guess I would say

01:47:17.500 we spent a lot of time talking about drug development from the point of view of the

01:47:20.840 fledgling biotech to the pharmaceutical industry. One of the things that a part of drug development

01:47:25.700 that gets forgotten about a little bit is the role of the NIH, of course, in funding basic science.

01:47:30.560 And the NIH, to some degree, does shoulder some risk in this space. They fund a lot of sort of

01:47:35.580 science for science sake, identifying novel targets that are ultimately, some of which

01:47:39.900 are clinically exploited. I guess I would say that although it feels like we spend a lot of

01:47:44.620 money on the NIH, $30 billion or so per year, I think it's not nearly enough that science is like

01:47:50.180 the greatest thing that people have ever done. And if I were in charge of anything, I would crank up

01:47:55.160 the funding for science because I think science is possibility. And that's what I mean by this

01:47:59.020 possibility. We need to increase the funding for science. We should increase it slowly and steadily.

01:48:03.980 I think there are problems that happen when you give a lot more money to people who are not used

01:48:08.140 to getting that. I think there's a lot more waste. But if you slowly grow something, we need to kind

01:48:12.260 of separate science funding from political cycles. It shouldn't be that just because the red team or

01:48:16.200 the blue team is in power that science funding is on the chopping block or getting more. We need some

01:48:21.040 sort of stability for science funding. Science needs slow, steady growth. And then the last thing I

01:48:25.380 kind of talk a lot about in this is how do you give out the money? It's fascinating to me. We've been

01:48:29.740 giving out billions of dollars in research funding. We've never really studied how do you give out the

01:48:33.940 money. If you look at the way the money is given, it's really kind of lopsided. There are a few people

01:48:38.580 who get a lot of funding. Their labs are flush with money. Some of their labs are so big. One wonders

01:48:43.880 if the boss ever meets all the people who work in the lab. There are hundreds of people who work in the

01:48:47.280 lab. They're really like financial operations run by a financial manager who's the boss and then some

01:48:52.400 scientists underneath it. And there are a lot of people on the other end of the spectrum

01:48:55.440 whose labs struggle to get money, even basic funding. And so I guess in this kind of section

01:49:00.760 of the book, I kind of explore, are there ways we can kind of bring some experiments to giving out

01:49:05.200 money, do some small, simple, randomized control trial studies, follow people and look to see

01:49:09.800 measures of equity of who gets the money, measures of research satisfaction, burnout, measures of

01:49:14.820 how translation occurs, some kind of controlled studies in grant giving. And then the last thing I

01:49:20.140 just say is blue sky science. So there's this branch of science typically called blue sky

01:49:24.640 science where it's just science for science sake. You don't come to me and say, I want to do this

01:49:29.120 experiment because I'm going to cure melanoma. You come to me and you say, I just want to know how

01:49:32.400 the cell does this. I just want to know, like, why does it do it? Why does this happen? And that type of

01:49:37.020 science, that type of inquiry that we all have as I think kids and high school kids, that inquiry is

01:49:42.400 really, really difficult when you are a academic doctor, because there's not a lot of money unless you

01:49:47.180 make promises. I'm going to cure this disease. I'm going to cure that. If you want to say, I just want to

01:49:51.680 understand how this works. It's really hard to get funding. And I think it should be the other way

01:49:55.380 around. Some of the greatest advances in science were people who pursued things purely because that

01:50:00.340 interested them and the finding and the translation was serendipitous. And so I think that's what I mean

01:50:04.320 by possibility. I couldn't agree with you more on this. I have many friends who sit on study sections

01:50:08.760 in NIH, which means they're basically the people that watch how NIH gives money. And their biggest

01:50:14.560 complaint is, look, we are really not permitted to take big risks here. I mean, we are very incremental in

01:50:22.160 how we fund, because we are on a funding cycle. They cannot fund pie in the sky, blue sky, really, really

01:50:31.980 fundamental basic questions. Because when I go back to Congress in two years and say, I need this much

01:50:37.980 money, the answer better be because I did X, Y, and Z with this. And, you know, I've seen some of this

01:50:44.780 firsthand. And again, I understand it. I mean, we don't want resources to be wasted. So it almost suggests

01:50:51.440 you want to have two arms. That would be my take. You want to have two funding arms. You want to have the

01:50:57.300 translational funding arm that is meant to be incremental, that is meant to look at basic science

01:51:05.240 and ask, is this ready to go to the next step? Is this ready to be taken to a clinical pathway?

01:51:11.980 If so, are you leaping too much? Are you not leaping enough? And then I think you have to have a totally

01:51:17.580 separate group that is responsible for funding a totally different type of science, which is all

01:51:24.300 about basic inquiry and the advancement of natural knowledge, regardless of where it takes us. Because

01:51:29.540 as you pointed out in the book, actually, there are lots of examples of some of the most exciting

01:51:34.260 discoveries in the history of the last 400 years, which is effectively the era of modern

01:51:39.920 science that came from nothing other than pure inquiry.

01:51:44.780 I think that's well said. That's a very thoughtful way to look at the problem. One of the people

01:51:48.300 that you cited, Jim Allison, whose work ultimately led to that blockbuster class of drugs, an immunotherapy

01:51:54.660 doctor. It wasn't that long ago when people, I remember people made jokes that that line of inquiry

01:51:59.860 was foolish and misguided and that was never going to succeed. Lo and behold, it turned out to be

01:52:04.240 sort of a Nobel Prize winning discovery. So I think you're right. Yeah, that's the right way to think

01:52:08.040 about it. So the final hallmark is agenda. What do you mean by that? Agenda is something that there

01:52:13.760 have been a number of researchers and including people who work with me and myself who have gotten

01:52:17.480 interested in the last couple of years, which is what happens when you take a 30,000 foot view of

01:52:22.080 cancer and look at the clinical trials agenda. And it's very interesting that some spaces in

01:52:26.900 cancer medicine, you got the same drug or similar drugs, 20 such drugs, Coke, Pepsi, and 18 other

01:52:34.220 Cokes and Pepsis. And people are running redundant and duplicative trials. They're all testing them in

01:52:39.160 the same tumors, in the same setting, with the same old controls. Sometimes they're running many

01:52:44.180 different clinical trials with drugs that have low promise. And one of the observations that we make

01:52:49.100 is, well, boy, by chance alone, aren't some of these trials going to be positive? I mean,

01:52:53.540 we're not using a very stringent nominal cutoff for significance. We're using a P of 0.05 usually.

01:52:58.180 Some are going to be positive by chance alone. How do you account for that? How do you account

01:53:01.660 for this duplication? Who's keeping track? It's like you need a Bonferroni correction factor

01:53:06.920 for the number of trials as opposed to the number of looks, right? Absolutely. In fact, we did a paper

01:53:13.280 where we corrected one with a Bonferroni. We got a lot of pushback from those peer reviewers.

01:53:16.960 It's a totally novel application of how you would use a Bonferroni correction factor.

01:53:21.640 But you instantly see what I'm getting at, which is that within a study, if you do a lot of

01:53:26.260 comparisons, you take into account the number of comparisons to some degree. We can debate what

01:53:31.220 statistical procedure to use, but we do take into account that we're looking at this data many times.

01:53:34.540 So we could fool ourselves. But when you're running many, many studies, shouldn't you also

01:53:38.480 do the same? It's a philosophical question. It's not really a statistical question. And the answer,

01:53:42.500 I believe, is yes. So that's what we talk about in this section in Agenda. We talk about what is

01:53:46.800 the mean to take that into account. And also, we forget sometimes that the most critical resource

01:53:51.920 in cancer medicine are the patients themselves, their scarce resource. In some tumor types,

01:53:56.980 there are now more trials ongoing than there are even people with that condition,

01:54:00.760 which may sound ridiculous, but it's because everybody chases the ball. Somebody recently

01:54:05.620 told me this great story about it's like three-year-olds and five-year-olds playing soccer.

01:54:08.980 They all run after the ball. Nobody plays positions. And that's what happens sometimes with the

01:54:12.060 pharmaceutical industry. They're all running after the ball. They're all running duplicative trials.

01:54:14.860 They're not enough patients with this condition anymore. We're depleting that resource. And what

01:54:19.100 do we have to show for it? And how do we interpret those studies? So I think that's what we talk about,

01:54:23.780 which is that somebody has to think about the big picture, or at least we have to look at it and

01:54:26.960 recognize what the agenda looked like across the entire field.

01:54:31.280 So coming back to oncology, is there a role anywhere for tumor genome sequencing? There are many

01:54:39.400 companies that do this commercially. If there's one email or call I hate getting, and unfortunately I

01:54:46.240 get it every two weeks, it's the friend of the friend or the friend of the family, the patient's

01:54:53.080 cousin, whatever, that has just been diagnosed with essentially an uncurable cancer. They're basically

01:55:00.300 saying, Peter, what advice do you have? And it's always heartbreaking because I don't have any.

01:55:07.440 It's by definition, if I'm getting that call, it's because their oncologist has already said there is

01:55:13.800 nothing to do here. These calls go in many different ways. I just had one a week ago. They were asking

01:55:20.220 about some supplement. And generally when I get asked, when I go down the path of, well, this person

01:55:26.400 has this hyperbaric oxygen protocol with this supplement protocol with this, this thing, and the

01:55:30.800 other, you know, the first thing I like to inquire about is the cost. My view on this, which may differ

01:55:35.720 from yours is first, we don't want to increase the harm of this person. I don't think there's

01:55:41.100 anything wrong with hope. I think there's a lot of things we don't know if they work or don't work,

01:55:44.720 but I'm certainly pretty squirrely when someone's offering a panacea treatment for $20,000 of vitamin

01:55:52.400 C, rubbing garlic on your testicles or whatever the concoction is. So we go down that whole path,

01:55:59.360 which is, you know, is there anything out there that's in the quote unquote holistic world that's

01:56:03.340 going to work? Another thing that tends to come up is, is there a role for tumor genome

01:56:08.380 sequencing? And I've certainly had within my own family and then that of friends sent people to

01:56:14.560 foundation medicine. Truthfully, I haven't really had anything come out of it. That's been a game

01:56:19.160 changer. Probably the only time in my life with this experience that I've gotten kind of lucky was

01:56:24.580 a friend that had pancreatic cancer. I mean, this was several years ago, but he had Lynch.

01:56:31.300 And I had just remembered reading a paper about how patients with Lynch were more likely to have

01:56:39.000 checkpoint mutations. This was prior to the approval of Keytruda, but it was in trials. And so we're

01:56:45.900 able to get him into a trial of Keytruda and he turned out to be a remarkable responder. And to this

01:56:51.640 day, he went from unresectable to cancer-free, which he remains about a decade later or nearly a decade

01:56:57.960 later. Long-winded preamble, talk to me about your view on tumor sequencing, off-label drug use,

01:57:05.700 targeting therapies, that sort of thing.

01:57:07.420 Just to allude to the other part of what you were saying that I thought was really right, which is,

01:57:11.860 I think we probably share the same philosophy, which is that often people come to me and they

01:57:14.800 talk about some alternative or complementary approach that they want to bring into their care.

01:57:18.300 And my view is probably maybe not dissimilar from yours, which is as long as it's not too costly,

01:57:22.220 as long as it doesn't have an opportunity cost, interfere with what we're wanting to do.

01:57:25.520 It's not a hill I want to die on because I think people should be allowed to pursue those things.

01:57:29.600 And I do think that one of the problems I get a little irritated by is there are people who want

01:57:33.140 to die on that hill and really draw a line in the sand. And I think you can poison a relationship

01:57:37.480 with somebody and it's not worth it. I mean, at the end of the day, if it doesn't cost too much,

01:57:40.720 it's not really too harmful and somebody really is motivated to do it and it's not going to interfere

01:57:44.180 with what you want to do, have at it.

01:57:46.320 And just the humility of like, what do we know? We have to be clear here. Like we don't know a lot of stuff.

01:57:52.580 Right.

01:57:52.840 And by the way, it's not like we have a track record that says we're winners.

01:57:56.240 Right. I mean, I think that all goes into it and that's also why I think that's all part of it.

01:58:01.380 Yeah, right. And then to come to your NGS question, I guess I would say next generation

01:58:05.360 sequencing, tumor genomics, I guess right off the bat, there are definitely some people who

01:58:09.040 definitely need to be tested for some mutations. So let's just talk about the ones that definitely

01:58:12.600 need to happen.

01:58:13.240 You mentioned lung cancer. It's a no brainer.

01:58:15.920 Right. Lung cancer, there are at least six or seven mutations that we now have FDA approved therapies for.

01:58:22.160 Definitely. There are different ways you could test for the same mutations,

01:58:24.780 but that's another thing to keep in mind. But you need to know about EGFR. You need to know

01:58:28.140 about ALK, particularly if the person is a younger person, non-smoker. Melanoma, you need to know

01:58:32.720 about BRAF. Colon cancer, you need to know about MSI high status. So there's a number of things we

01:58:37.220 have approved drugs and we publish some papers. There's maybe 20 or 30 things. And a good oncologist

01:58:41.080 usually knows the mutations for the tumor. The next thing is now we do have an approval for

01:58:47.020 microsatellite instability high, which is probably like your patient with the Lynch syndrome,

01:58:50.560 pancreas cancer, no matter what tumor type. You know, that's something that we have an

01:58:53.840 approved drug, very reasonable to test for. Then I think the next way that NGS can be used

01:58:58.500 is exactly as you used it. I'm a huge supporter of, which is that you're using NGS to pair your

01:59:03.020 patient with a clinical trial. I think that's a perfectly acceptable way to use NGS, to run a

01:59:07.600 broad NGS panel. And if you find a trial that fits, have at it. The next part about it, I think is

01:59:12.800 tricky, which is that the part that I think that I kind of have the most friction with some of my

01:59:17.140 colleagues is after having done all these things, you've looked at mutations, we have approved drugs,

01:59:22.240 you've tried to find somebody trial. Sometimes you do NGS on a patient and there is a mutation

01:59:27.760 that is seductive. It looks like you have a drug for it. There's no trial available. And you also have

01:59:34.300 a standard drug that we normally give. And in these situations, it is so seductive to believe that because

01:59:41.200 we found the mutation and the target, it's better to use the targeted drug than that older drug that may

01:59:45.820 have a longer track record. And I think that's where people get into a bit of trouble that sometimes

01:59:50.560 you actually end up eroding outcomes, not enhancing outcomes. You actually make worse choices in those

01:59:56.660 cases. Because the truth is that some genomic mutations are mutations that are fueling the

02:00:02.820 tumor. And that if you fix those mutations, you would improve the outcomes. But some mutations are

02:00:08.200 the product of a genome that is undergoing massive instability and damage. Some of these tumors,

02:00:13.120 when you look at the sequence, it's like a dinner plate that's been dropped on the floor.

02:00:16.480 It's in shards. It's broken all over the place. You may find that for one of those two shards,

02:00:21.020 you can put a little piece of tape on it. But are you really going to help the whole person?

02:00:24.620 And there are some studies that show sometimes if you take biopsies from a bunch of different sites

02:00:28.320 and you sequence them, you don't even have the same mutations in different sites. And one study

02:00:31.860 shows that if you sequence this part of the body,

02:00:34.140 different parts of the tumor, yeah, the tumor has spread to let's say the lung and the liver.

02:00:38.060 If you looked at the liver, you might give drug A. If you look at the lung,

02:00:40.460 you might give drug B. That's not a very precise therapy. And then the other thing that's a

02:00:44.760 complexity is some researchers have sent the exact same tumor to a couple of different companies and

02:00:49.200 they haven't always gotten the same result. That also makes one a little concerned. So I guess I

02:00:53.500 would say approved drugs, the sort of very common mutations, all good doctors are going to test for

02:00:59.540 to pair somebody with a trial as you did your friend. That's really terrific. I think particularly

02:01:04.520 people who suffer from rarer tumor types at younger ages, they should also keep an eye out for

02:01:09.420 fusion events. Those are really important to know about. They're often, a lot of researchers

02:01:12.860 are interested in studying that. There's some trials at Sloan-Kettering. The place I think

02:01:16.360 maybe you don't always have to do it is for somebody who is not doing well and they have

02:01:22.440 progressed through many lines of therapy and they have a tumor that we just don't have a lot of

02:01:27.060 mutations that we know a lot about. I mean, I don't think it's obligatory. And if you do find

02:01:30.700 something, I think sometimes you got to be careful that you don't just gravitate to what is a key in a

02:01:34.800 lock, what sounds like a key in a lock, but it may be sort of taking you away from something that has a

02:01:39.000 better track record. That has to be literally one of the most elegant and brief descriptions of the

02:01:44.300 pros and cons of that type of approach. So I'm glad I asked that question because I could have spent

02:01:49.300 two hours and said less. Are you bullish or bearish on liquid biopsies? You indirectly alluded to it,

02:01:55.380 which is look, with leukemia, we're basically doing a liquid biopsy. Correct. So now the question is

02:02:00.000 when we, a year from now, presumably have at least phase two data on liquid biopsies for solid organ

02:02:06.460 tumors and lymphomas, are you optimistic? And how do you see that changing the way we practice

02:02:10.940 potentially? I guess I'd say the interesting thing about leukemia is it was very likely one of the

02:02:16.560 first things we studied in part because we can access it so frequently and so readily, and we can

02:02:20.920 actually track its volume in an era where the doctors had to measure marbles through foam rubber

02:02:25.600 with their calipers. And so that's why leukemia has always sort of been a couple steps ahead of

02:02:29.700 everything else. About liquid biopsies, I guess I would say that, you know, we do have a number of

02:02:33.500 approved liquid biopsy tests and they're certainly going to have a role. Anytime we've already conceded

02:02:38.640 that there are some mutations that are very important in certain tumors and we have drugs

02:02:41.360 for those mutations, if you can find out that mutational information without having to stick

02:02:45.540 a needle in someone, everyone is going to be grateful for that. I guess the questions that are

02:02:49.680 always going to be kind of, and they vary probably test by test, mutation by mutation is,

02:02:54.200 is the test sensitive enough in this case? If you find you don't have the mutation on the liquid

02:02:57.980 test, are you still going to want to go get tumor tissue? Or do you need to get tumor

02:03:01.860 tissue for another reason to figure out the subtype? And in that case, you might as well,

02:03:05.400 you already have the information you need. The real role for liquid biopsy might be the serial

02:03:09.780 nature of it. You can track something over time, see how it's doing over time. And that might be

02:03:14.200 the real boon. But I guess I would say, am I bullish about it? I'd say yes. I mean, I'm not known for being

02:03:19.160 a bullish person, but I guess I would say that's something that I would definitely study more and do

02:03:23.060 sort of really good clinical trials at the end of the day to see what the role can be. But yeah,

02:03:27.000 they're already in our clinics. We use them. Yeah.

02:03:28.760 You've talked about this indirectly that, I mean, look, you're naturally a skeptic. You're

02:03:34.080 naturally critical. Those are very valuable tools. They've served you well. And more importantly,

02:03:40.420 they've served many people well, meaning your skepticism and your critical thought has sort

02:03:45.940 of made medicine better. How do we, or maybe I'll ask it more directly, how do you navigate that

02:03:51.740 balance? There are some people that are skeptical for the sake of being skeptical. They're always the

02:03:56.680 contrarian. No matter what the answer is, they're always going to take the opposite side of that.

02:04:02.260 How do you sort of, police is the wrong word, but how do you navigate that internally?

02:04:09.740 I guess I would say, I mean, there is an example of something where I was not on the side I'm usually

02:04:16.020 on and people gave me a hard time about, which was the dexamethasone in COVID, the recovery study

02:04:20.820 very recently. So, I mean, let me just put it in a little context. One of the things that happens a lot

02:04:24.940 in medicine these days is medicine by press release, which is one day Eli Lilly announces

02:04:29.180 top line results are positive for this trial and this drug, improved outcomes in these people,

02:04:33.500 and this is the hazard ratio, 0.7. But how long did they live? Did it have side effects? None of

02:04:38.380 that's in the press release. You know, it's just sort of a fragment of information. And I think they

02:04:42.320 put that out primarily for the shareholders and for their information. And some doctors may act upon

02:04:46.920 that. I mean, that might be something that people find enough to act upon. And I'm always a big

02:04:51.380 critic of that and say, let's wait for the paper. Let's wait for more information. Recently, there was

02:04:55.000 a recovery trial out of the UK and they say that dexamethasone for people who are hospitalized

02:04:58.880 requiring O2 with SAS less than 94, people who are mechanically ventilated, that they benefit from

02:05:04.360 dexamethasone, all-cause mortality benefit, whereas people who are hospitalized did not require

02:05:08.200 supplemental O2. They actually, maybe they didn't benefit. They were harmed and there's a significant

02:05:11.940 interaction coefficient. They put out that press release. And I went online and I looked and I'm like,

02:05:16.120 oh boy, you can read their protocol. Their protocol was published a month ago. It's available.

02:05:19.560 It's 35 pages. You can read it. And you can read the statistical analysis plan. That's also out

02:05:23.580 there. It tells you exactly what they were going to do, what the pre-specified endpoints are. And

02:05:27.360 we're in the midst of a pandemic where people have been trying things left, right, and center,

02:05:30.860 throwing the kitchen sink at people with COVID. And so I said, the evidence is good enough. We got to

02:05:34.700 do this right now. We got the press release. We got, you know, I like to say a press release and a

02:05:39.000 protocol. That's like a driver's license and a social security card and a paper. That's like a

02:05:43.060 passport. Do I have to show you my passport? I can show you the other two. It's another form of

02:05:46.900 identification. Okay. So anyway, so I say this and I got a lot of heat from the usual critical club

02:05:52.080 because they said, well, we got to wait for the paper. And I say there's such a thing as too much

02:05:55.680 skepticism. And that's what I think is a good example. I guess I would say that probably the

02:05:59.540 greatest way in which I can't even claim that I'm on the set point on the thermostat, but I can't say

02:06:04.840 the only way to kind of keep this in balance between skepticism, that's so bad that it's paralyzing.

02:06:09.680 You can't do anything and blind acceptance. That's so bad that you are cheerleader for everything.

02:06:14.220 The way to keep that in balance is I find going into the clinic because no matter how skeptical

02:06:19.100 you are about drugs, you have to have those conversations with real people. And there's

02:06:23.080 some people who are going to be taking drugs that you're skeptical of. And maybe I should just make

02:06:27.040 a point about what I think my clinical philosophy is. Some people sometimes ask me, it's not the

02:06:31.540 doctor's role to determine what treatment is right for someone. It's really the doctor's role in my mind

02:06:35.840 to empower the patient with what I know about the drug, what's been shown, what hasn't been shown,

02:06:40.480 what the benefit might be, what are the uncertainties, what are the known

02:06:43.600 toxicities and risks, and then to walk them through how they would decide. Is it worth it

02:06:48.260 to them to take those risks? And different people will choose differently. Some people will choose

02:06:52.660 differently than what I would choose for myself. Some people will choose differently than the next

02:06:55.880 person with the same information. I think those are all okay. The more you practice medicine,

02:06:59.940 the more you realize that this is, it's an art. You're never going to have perfect information.

02:07:03.660 You're going to have to make decisions today with less than perfect information. And I think

02:07:07.680 that's a way that one keeps skepticism in check. I actually think this is one of the biggest

02:07:13.000 challenges in this art slash science of medicine. This is very different from experimental physics,

02:07:21.080 where we could all hang around a particle collider and debate the experimental results all day long

02:07:28.240 and red team, blue team. I mean, it is really different. And I struggle with this so much.

02:07:34.560 And I think you said it exactly correctly with respect to that thermostat is if you're too much of a

02:07:40.100 skeptic, you're not doing anything. You're going to sit on your hands forever. And there's a cost of

02:07:45.940 doing nothing. And that should never be forgotten. And if you blindly accept everything, you are almost

02:07:52.700 unquestionably subjecting patients to unnecessary treatments. I feel lucky, right? Because

02:07:58.120 I have two full-time colleagues in my practice and then two part-time colleagues. So there's a group

02:08:02.800 of five of us basically can argue with each other all day, but we never lose sight of the fact that

02:08:09.680 it's not an intellectual pursuit. At the end, a decision needs to be made, even if that decision

02:08:15.040 is to do nothing. That's still a decision. And I love that. I actually find that to be some of the

02:08:19.440 most enjoyable stuff we do is just the debate. That's another nice thing that you brought out,

02:08:24.380 which is that's another way to keep skepticism in check is you go to a tumor board or you go to a

02:08:30.460 multidisciplinary meeting, or you sit around the table with a few of your colleagues and you present

02:08:34.160 some cases and you hear what other people have to say. At the end of the day, that something's got

02:08:38.060 to be done. They're either going to do it or they're not going to do it. And sometimes it is important to

02:08:41.620 know that people do things differently than we might do it. And I think it keeps us in sort of a balance.

02:08:47.320 This was a fascinating discussion. God, there's a lot of other things that we could talk about here,

02:08:50.900 but I also am wary of the fact that in a COVID environment, people have less and less time for

02:08:55.880 podcasts. So the longer this podcast goes on, the lower the probability people are going to listen

02:09:00.100 to it. And I want to make sure people hear this one. So I wish you the best as you continue with

02:09:05.280 your move into San Francisco. I'm sure we will speak again. Thanks so much, Peter. Thanks for having

02:09:11.620 me. It's a terrific discussion and great to chat with you on these topics.

02:09:15.220 Thank you for listening to this week's episode of The Drive. If you're interested in diving deeper

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The Peter Attia Drive - October 19, 2020

#133 - Vinay Prasad, M.D., M.P.H： Hallmarks of successful cancer policy

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