Improving Value in Medicine: Health Technology Assessment and Determining the Value of Treatments

Improving Value in Medicine: Health Technology Assessment and Determining the Value of Treatments

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- Good afternoon, everyone. Welcome to UCSF, Department of Medicine Grand Rounds. I'm your host for today, Lekshmi Santhosh, Director of Medical Grand Rounds, filling in for Dr. Bob Wachter, our Chair, while he's out, it is my immense pleasure to announce our two speakers today to talk us through really complex and fascinating topics regarding the intersection of healthcare policy, health, economics, and how we, as clinicians, can actually make practical decisions for our patients and how do we talk to our policy makers about this? Our two experts today are physician leaders in ICER, which you may better know as the Institute for Clinical and Economic Review. They're really aiming to challenge the current status quo of high prices in the US.

We all know that the US has the best healthcare in the world, but our costs are definitely an issue and we're gonna talk about that. So it's my honor to introduce Dr. Grace Lin and Dr. Jeff Tice, who lead work in ICER and who are gonna help us demystify drug pricing and explore how health systems can improve value.

First, we're gonna hear from Dr. Grace Lin. Dr. Grace Lin is a Professor of Medicine in the Division of General Internal Medicine at UCSF Health.

And she's also the Medical Director of Health Technology Assessment for the organization of ICER. She really focuses on primary care and she's really focused in her research on the appropriateness of medical care provided to patients. She works on shared decision-making, the quality of decision-making by both doctors and patients. She initially trained at University of Michigan Medical School and completed her residency at Barnes Jewish Hospital, where she was also a chief resident, and we were delighted to recruit her here for a general internal medicine research fellowship at UCSF.

And since coming here, she's rapidly ascended both clinically and in health policy and is now also the director of outpatient palliative telehealth program since 2019. Next, we'll hear from Dr. Jeff Tice, who's also a Professor of Medicine in the division of General Internal Medicine at UCSF Health. His health policy interests and research really focus on risk assessment tools, particularly in the field of breast cancer and how to efficiently use those tools, combine those shared decision-making tools with technology, combine all of those with preventative therapies to collectively work to decrease the burden of breast cancer in our community. He's also performing technology assessments and cost-effective modeling and research for ICER.

And so it's really our pleasure to introduce both these two speakers to help us demystify this complex problem ahead of us. Thank you so much, Dr. Lin and Dr. Tice. - Thank you for the introduction, Dr. Santhosh.

As Dr. Santhosh said, Dr. Tice and I will be talking about improving value in medicine, specifically about health technology assessment and determining the value of treatments. So our disclosures that both of us receive salary support as part of a UCSF contract with ICER. So let's begin with a question, and I'd just like you to think, to look at this list and answer the question in your head, which drugs have had price increases unrelated to new evidence or indications? And I've listed four drugs for com... three very common drugs and one not so common drug.

And I'd like you to just think about which of these you think may have had price increases. And it turns out that in fact, all of the above, all of these drugs have had price increases. Everyone's probably recognizes this person on the right here, Martin Shkreli, the Pharma Bro, he's responsible for the price increase of Pyrimethaprim, which is an antiparasitic that went from $7 a pill or to $750 a pill, but other drugs have not been excluded. Epi-pen is 100 to $600 for a dollar's worth of epinephrine.

And insulin went from $21 a vial to $255 a vial. And so what we understand here is these prices have increased, but do they have any basis for this increase? Has the value of the drug increased and in concert with that drug increase? And that's what we're gonna talk about today. So at the end of the session, we hope you'll be able to identify some inputs to drug pricing in the US. Describe the advantages and disadvantages of value-based pricing, and describe the state of health technologies assessment in the US.

We'll talk a little bit about healthcare costs, which I think most of us are familiar with. We'll talk about a framework for value. We'll go through some brief examples from both our work at ICER and then we'll be happy to have a discussion, and to answer questions.

So I don't think for most of us, this is not a surprise that healthcare expenditures per capita in the United States are much higher than comparable country averages. So you can see here on the graph, the United States is here at the bottom in green. Our healthcare costs per capita are in excess of $12,000, almost twice as much as comparable countries including Japan, the UK, Australia, and the US spends 18% of its GDP on healthcare compared to around 11% for the rest of the world. Unfortunately, despite spending more, the US doesn't necessarily have better outcomes. And so, we can ask the question is, you know, what are we spending our money on? And is it worth the money that we're spending? Now, I will note that the difference between this 12,000 plus and the 6,000 plus about a quarter of it is due to drug spending. And drug spending, a lot of drug spending is due to prescription drug costs.

Prescription drug costs are rising. These are data from California and you can see between 2017 and 2018, and 2020 and 2021, the year over year increase ranges from 4 to 6% And the cumulative increase is around 22%. So this represents an increase of 1.5 billion with a B dollars over that time to, you know, to a total of over 20 billion spent by health plans on prescription drug costs in California in 2020 and 2021.

So I think while we're glad that we have new therapies that extend life and improve quality of life and treat previously untreatable diseases, there's also the reality that we can't afford to go at the pace we're going and one of the drivers is prescription drug pricing. And so we need to solve this conundrum of, we need to spend money on prescription drugs, but are we getting good value from them? So let's step back and let's look at all this list of drugs for a variety of conditions. We have a drug for hemophilia A, one for spinal muscular atrophy, which is a gene therapy, drugs for obesity, Alzheimer's, pediatric leukemia and hyperlipidemia on this list.

And on the right hand column, you'll see the price either per year or for the one-time treatments, you'll see the price per occurrence. And you can see that there's a variety of prices. Some are, you know, less expensive in absolute terms, others are you know, others are very expensive, like the $1.6 million for Zolgensma, which is the gene therapy for spinal muscular atrophy.

And I'd like you to think about just looking at this list, do you have any idea which of these you would consider a good long-term value for the price that we're paying? And also think about what factors you consider assessing the overall benefits of a drug. And how would you go about deciding whether the price is fair? So there are a few approaches determining a fair price. In the US, we have the free market approach or supply and demand approach where the producer sets the price.

So basically, a manufacturer develops a drug, it gets approved by the FDA, and the producer just sets the price at launch and says, you know, we're selling this drug for X dollars. You know, they might consult other people, but basically, they have the power to do that. And so whether or not that price is tied to any kind of value, you know, is not clear, there's not necessarily a good correlation. Another option is to charge what the cost of development in production, plus a quote-unquote, "reasonable profit" understanding that, you know, drug makers need to make a profit to invest into future drugs.

This is a model that may be suitable for older generic drugs, but it's really hard, I think, and one of the arguments from drug makers is, well, we put a lot of money into developing drugs and not, you know, only a few drugs in our development pipeline actually make it to market. So we need to actually account for not just the cost of development and production of that one drug, but we need to account for the 10 drugs that failed on our way to that one drug. So you know that one of the arguments against this for newer drugs, even though it might be suitable for some older generic drugs, is that it doesn't actually, it's hard to calculate that cost of development. And then the third option is the kinda calculate the added value to patients in healthcare systems. This is probably the most appropriate way for new drugs, but we need a way to measure value.

And so how do we measure value in the healthcare system? One method is via health technology assessment, which is a systematic evaluation of the potential impact of a treatment in order to inform healthcare policy. So who does health technology assessment? In some countries, mostly ones with single-payer healthcare, it's a governmental agency. The NICE you might've heard of NICE, the National Institute for Clinical Excellence in the United Kingdom is probably the most prominent example. In the US though, because we don't have single-payer healthcare, there is no such governmental body. One of the more prominent organizations in this space is ICER. ICER is the Institute for Clinical and Economic Review.

It's an independent nonprofit research institute founded in 2006. And just a note, so I think what's important here is the independent part. So this is a list of ICER sources of funding. So it's mainly funded, about three quarters of its funding comes from nonprofit foundations, philanthropy, and a platform called ICER Analytics, where the models from ICER reports are posted, and payers pay to basically use this model. That's the money that funds these health technology assessments of new drugs.

There is some of the budget is made up of health plans and provider organizations and life science contributions, but that is specifically earmarked for a policy summit and non-report activity. So that is held, there's a firewall that money is held completely separate and does not at all influence the report activities. You know, although ICER works with lots of stakeholders, including manufacturers and health plans and patients, none of those have input into the decisions that ICER makes during their reports. In terms of how they assess the value.

ICER's mission is pretty simple, to move the US healthcare system for towards fair pricing, fair access while preserving future innovation. And ICER's process for determining value is threefold. First, we develop value assessment reports on medical tests, treatments, and delivery system innovations, which we'll describe in a bit. These reports use comparative effectiveness and cost effectiveness analysis to suggest value-based price benchmarks. And then this is a 10-month process that culminates in a public hearing with a regional independent appraisal committee on each report to vote on value. So in California, that's the California Technology Assessment Forum or CTAF, and it's made up a variety of stakeholders, physicians, health economists, patient advocates, bioethicists, many faculty from UCSF have served on this CTAF over the years.

And so UCSF has had a great impact on assessing value for new treatments. So before I pass it off to Dr. Tice, I'm just gonna go back to this slide that I showed earlier, which is this list of drugs. And all of these are drugs that ICER has reviewed in the recent past, in the far right hand column, I have added check marks and X's, for the green check marks are drugs that were found to be of good long-term value for the money. And the red check marks are the ones that were not found to be representative of good long-term value for the money. And so hopefully some of these, you know, aren't necessarily obvious.

And so I'm gonna hand it over to Dr. Tice who's gonna kind of explain ICER's process for determining the value of treatments. And then we're gonna talk about these last three drugs on the list, lecanemab, the CAR-T therapy and evolocumab to give you some examples.

So I'll turn it over to Dr. Tice. - Thanks, Dr. Lin. Thanks everybody for joining us today. I'm gonna talk briefly about the value assessment framework. Each of these slides, people spend entire years teaching courses on these things.

So it's a very high-level overview, but certainly happy to get into more detail as we go forward. This is a schematic of the value assessment framework that ICER uses today. We really emphasize upfront, special, social and ethical priorities, benefits beyond health.

And these are things like disparities, if an equity in health. If there are some group who has a disease that's been neglected or their group is overrepresented in a particular disease, is this therapy going to make a difference that will help them? Is there substantial unmet need? Is this a disease process where we have no therapies currently? Things like that, including delivery methods that improve access, for instance, we often think about rural communities where they don't have access to a care center like UCSF. And so sometimes new therapies aren't all that innovative other than they extend the reach of this therapy to populations who have challenges in accessing those therapies. So these are kind of some of the special social and ethical priorities and benefits that go beyond just a measure of health. The health and cost measures that we take into are sort of all costs in the systems, including hospitalizations costs, and I'll go through that in a little bit more detail.

The health benefits, it's not just longevity though, that's important. It's return of function, it's quality of life. And we've put all that together in assessing the value for a particular new therapy. And I think the first two rectangles in blue highlight that, you know, there's never any one number that says, oh, anything below this is a good value. Anything above this is bad value.

You really have to take into account the circumstances of the illness and of the people affected. And that sometimes changes our threshold, our willingness to pay threshold. Let's see if I'm doing this right.

All right. So how do we do this? We start the process, as Dr. Lin said, it's a multi-month process, we actually start talking to patients. We want to hear from them what matters to them, what are the things that impact their life? And we often also talk to their caregivers because caregiver burden is something we wanna hear about. We talk to clinical experts and it's one of the reasons we reach out to our experts here at UCSF quite frequently to hear their thoughts about the new therapies, unmet needs and so on.

And we often reach out to specialty societies to get experts as well. We speak to the manufacturers, we speak to public and private payers and really try and understand how people are thinking about the disease state and current state of therapies, and these new therapies that we're going to evaluate. Then we do a traditional systematic review of the literature when appropriate. We summarize the data for individual therapies and meta-analyses. And if we're looking at many, many therapies, we'll do a newer technique network meta-analysis.

And then when possible, we seek out real world evidence. One thing Dr. Lin didn't point out is that we oftentimes our public meetings and our reports to the FDA launch date, so we look ahead at drugs or other therapies that we think are gonna be important and potentially have important cost implications. And we start a process eight months before that. And so there're usually aren't any real world data for the drug of interest. Sometimes we go back when real world data or more mature randomized trial data are available and reassess things.

But most of the time, we don't have a lot of real world evidence, though we often use real world evidence for the comparators. And then we calculate something called the incremental cost effectiveness, incremental because we're comparing two things. We're comparing something new to whatever is the standard of care and if there is no standard of care, then what whatever sort of supportive therapy is standard.

But we're looking at the difference in both cost and effectiveness. For the cost, we usually do this from a health system perspective. So drug costs and we know drug, the wholesale costs that are listed and publicly available.

Nobody pays those or none of the insurers and other payers pay those. There's always some reduction on average, about 30%. So we build that in.

We actually try and capture the actual discounted prices, not just the list price. We measure all of the health effects, ER visits, hospitalizations, procedures, a great example as I did newer, not so new anymore, Hep-C drugs a number of years ago. And in order to fairly evaluate those therapies, we had to capture liver transplants that were averted, hospitalizations for decompensated liver failure, things like that. So we try and capture all the important economic costs associated with an illness. And when possible, particularly for therapies that have a big impact on families.

For instance, I'm reviewing a new therapy for patients with schizophrenia. And as most of us know, it has a devastating effect on family, and it takes a tremendous amount of effort from whoever is caring for this person to support them. So when, when feasible, we try and capture those data. Unfortunately in the medical literature and the larger literature around these diseases, often they aren't well-described. So it it's often challenging to fully capture the societal costs of diseases rather than just the healthcare costs. And then we look at standard health outcomes.

You know, how long does this increase longevity for patients? What kind of functional improvements are there? How does this impact quality of life? And then the most important thing is we try and put this all together and this is the challenge and controversy. We summarize it with something called a QALY, a Quality Adjusted Life Year. And you can think the way I like to think of that is, that is a year of perfect life, perfect health. So, you know, so somebody who's living with heart failure, if you know, would have a, you know, heart classification for heart failure, you know, their quality of life is much reduced because of the limitations in their activity. So they might have 0.5 or 0.4 QALYs, something like that.

So when you're talking about the QALY metric, it's sort of adjusted for all of the impacts of the disease on the patient's life. And then we try and assess the value. And you know, so here, if you have new treatment, so the x-axis here is effectiveness, essentially the QALYs, or you can think about it, a length of life, the y-axis is cost. So this dot here, it's a new treatment costs more, outcomes are worse.

We call that dominated. We wouldn't even consider that, all right? Here you have a therapy that has an increase in cost, but not a huge increase in effectiveness. So usually those are not things we say are good value, we might not pay for that. Over here is something that costs somewhat more, but you have a pretty substantial gain in health outcomes.

So this is something that's a good outcome. So generally things in the blue below this line, were willing to pay for that. And then of course, ideally, if we're in the tech field, this is what happens. Things may cost less and they're more effective, or we get a better phone for the same cost.

We rarely see that in healthcare, but that would be the ideal if we're actually gonna reduce total net healthcare costs in the US, we actually need more things in that lower quadrant, but I don't think we're gonna see too many like that. All right, but then how do you decide, all right, you get this number, some dollar per QALY, per quality adjusted life here. How do we decide what we should pay for and what we shouldn't? And there's been extensive research on this.

WHO and American College of Cardiology, when they looked at this, they said, well, it really depends on the society you live in and you ought to base it on GDP and usually societies are willing to pay 1 to 3 times the GDP per capita. In the US now, we're at about $80,000 a year per capita and that's what our GDP is. If you ask people, if you ask people in society, you're often willing to pay about two times their annual salary. And of course, that varies from Elon Musk to me, to my health assistant and that I worked with this morning in clinic.

And sometimes people use opportunity costs. This is often done. Sometimes they do these sorts of things for deciding innovative things to prevent car accidents and things like that. How much are people gonna budget for that? They look at that at a health system level, it's about one time GDP.

So you see, you get that range between one and three. ICER doesn't make a formal judgment about that. We present data at 50,000, 100,000, 150,000, sometimes 200,000 to give different healthcare organizations different, an idea of whether something meets those different willingness to pay thresholds. But it's a value judgment and it needs to take into account those initial things I highlighted in the value framework, things other than just this number. Sometimes if you've never had a therapy for this, where there's a huge unmet need for instance are novel therapies that may cure sickle cell anemia, we may be willing to pay a little bit more than $150,000 for quality adjusted life here for a therapy like that.

And then ICER presents often because there's not a cost yet. We present a range that we talk about as the value assessment price benchmark, and we present the range between 100 and $150,000 per quality adjusted life year. And we'll give you some examples, you get some sense of how those calculations are made. But it's, you know, they're complicated models and there's a lot of uncertainties.

Those models have a lot of different inputs and you know, everything has a confidence interval and uncertainties. And that's true for the clinical benefits, both short and long-term. The costs and the quality of life measures, the utilities, how we should adjust somebody's quality of life for the particular health state. And they never reflect reality. They're always a simplification. And we run them out for the lifetime to capture those long-term benefits that may not happen until 10 or 20, or 30 years after taking a pill to cure Hepatitis C.

And so in order to fairly capture those in general, we take a lifetime horizon for the models. But to capture these uncertainties, we do a lot of sensitivity analysis. There's something called a one-way sensitivity analysis. You vary an individual parameter across reasonable ranges and say, Hmm, does that change our decision about whether this represents a really good value or a terrible value? And we do that for each important input. We can see which inputs may have a big impact on that and which have a minimal impact.

And then there's a way to do that all at the same time. You sort of randomly pick something for each of the inputs, run the model, then you randomly pick again from the range of inputs to the model and do it again. And you do that thousands and thousands of times, and then you get a distribution and you can say, you know, 100% of the time this is above $150,000 per quality adjusted life year, this is not a good value. Or all the time it's less than 50,000. It's a really good value or there's a wide range, and so there's so much uncertainty, we have a hard time assessing value and everything in between. So we try and do that and present that information in the report and in the public meetings to the people who are gonna vote on whether something is a good value.

And then one of the unique things we do somewhat controversial in some spheres is we look at the potential budget impact. So sometimes something is effective, but it's gonna cost a lot. Usually these are things where there's pent up demand for the therapy and if something is gonna cost billions of dollars a year, suddenly new added to the budget of whatever healthcare organizations paying for this, they may need to stop paying for other things or they may need to ration this new therapy, slow its adoption or they may have to increase the cost to charge for their insurance the next year to sort of make up what they lost for this. A great example that I like to give is, again, the Hep-C drugs, because there were a lot of people, they're relatively expensive, turned out they were good value.

$20,000 per quality adjusted life year was our estimate. And again, all the sensitivity analysis, they still look like a good value, even at $1,200 a pill, which was what they were initially, but there were a lot of people with Hep-C who wanted to be treated with these new therapies and the VA ran through its entire pharmaceutical budget for cancer drugs, for cardiovascular drugs, everything in one month and had to go to congress for a special appropriation, all because of the Hep-C drugs. So that's why we make these affordability alerts.

It's rare that we do it, but we think it's really important. It's an important healthcare policy. Bit of information for everybody thinking about how to manage new drugs. All right, so now we're gonna give a couple of examples really simplified and Dr. Lin's gonna give the first one. - Okay, so we're gonna talk a little bit about treatments for Alzheimer's disease. You all might have been heard about Lecenemab or Leqembi, which is the newest approved drug for Alzheimer's disease.

So as you probably know, Alzheimer's disease is a terrible neurodegenerative disease, one that's increasing in prevalence to the aging population. The estimates are around 10% of people over the age of 65 have Alzheimer's disease. And up until a couple years ago, there wasn't really any potentially disease modifying drug.

Then came the development of anti-amyloid monoclonal antibodies. These target removal of amyloid from the brain. The first drug was aducanumab, you may have heard of all controversy about aducanumab. They were mixed results from the clinical trials. One of the phase three trials was positive, the other one showed no difference. And the FDA approved it, gave it accelerated approval, but there was so much controversy that essentially the drug maker pulled it from the market.

Lecanemab is sort of the next generation. It targets a different amyloid species, but it's still an anti-amyloid monoclonal antibody. And lecanemab trials were done in patients with mild cognitive impairment and mild Alzheimer's. So as we've talked about, we do the clinical and cost effectiveness analysis. So on the clinical effectiveness side, when we analyzed the data, this is from phase three studies, lecanemab was effective, very effective at removing amyloid from the brain. Substantial number of people became quote-unquote, "amyloid negative" after treatment.

But that didn't necessarily translate into a clinical benefit for everyone. So the clinical outcome was this measure called the clinical dementia rating scale sum of boxes. And what the drug did was slow down cognitive decline by 27%, which translated probably to a few months that somebody would be in a few months longer, that someone would be in mild cognitive impairment or mild Alzheimer's disease before they went on to worsen into moderate and severe Alzheimer's disease. So this drug isn't curative, it doesn't, you know, prevent the progression, it just slows it down. And then there's potential harm, this thing called ARIA, Amyloid Related Imaging Abnormalities, which is essentially brain swelling and bleeding.

And so when on balance, you know, you're thinking about, okay, so maybe this slows down cognitive decline by a few months, but it's every two-week infusion and I might have brain swelling and bleeding. So there's a lot of uncertainty about whether that benefit was really worth the potential harm. On the modeling side though, because there's a potential benefit, and because Alzheimer's is such a devastating disease, both for the patient and for caregivers, you have increases in quality adjusted life years and it prolongs years living in the community. So one of the biggest costs of Alzheimer's is, when people develop severe Alzheimer's, they're either needing 24-hour caregiving in the community or they need to be in skilled nursing facilities, memory care facilities, which are extremely expensive.

And so because there's some benefits to lecanemab, it does increase QALYs and prolonged life years in the community, but at the price of 26,500, which it was its launch price, the incremental cost effectiveness is around $250,000. And you know, Dr. Tice was telling you that typically, we think of our willingness to pay threshold is between 100,000 and 150,000, but that's just the number.

There's obviously, this concept of benefits beyond health. And when we talk to patients, the patients told us, they said, you know what? We'll pay for any slowing or stability because we think that's meaningful because it preserves our independence and our sense of self, which you can't really capture in that quality. So that's one of the things that goes into the value assessment is that context. But here's the problem. So because it was fully approved by the FDA, Medicare decided it's gonna cover the drug if you participate in a registry to collect long-term data. But there are so many people with Alzheimer's, and this drug costs $26,500 a year, not including the monitoring costs.

You need MRIs, then infusion costs, and every two-week infusion, there's an estimate that Medicare could spend between two and $5 billion annually just on lecanemab. And Medicare itself, it'd be expensive for Medicare itself, but also for individual patients because it's an infusion, it would be billed under Medicare Part B, so there's no cap. Unlike Medicare Part D, which is the prescription drug plan, there's a cap on how much patients pay, for Part B, there's no cap. So the estimated per patient co-insurance is over $6,000 per year. You can imagine that that is, could be a tremendous burden on patients that and would might cause some disparities in who can and can't afford to get lecanemab. Also the potential budget impact.

So, you know, Medicare basically, is spending $2.5 billion annually if everybody eligible, you know, had this drug. Well, if you try to take into consideration a reasonable budget for a health plan, which ICER estimates and they, you know, I believe these estimates, excuse me, every year, but at the current time it's about $777 million. And that's what a health plan might spend on its entire budget.

Less than 5% of eligible population could be treated within five years. So this is what Dr. Tice was talking about is, this would have a huge impact because there's a lot of unmet need and it's a relatively expensive drug.

So then we ask the question, well, what would a value pay based price for lecanemab look like? And here is where we go through the example of, so the annual wholesale acquisition price. So this is what the list price is, is 26,500, as I said, but when you calculate the relative clinical benefits and the harms, and the QALYs, the annual price we estimated at the $100,000 threshold is $8,900. So you know, almost one-third of the price of its list price. So we'd have to have a substantial discount if we were saying we're willing just to spend $100,000 per quality adjusted life year per patient to have this drug annual price at 150,000 is a little bit more, you know, almost $15,000, but it would still be a substantial discount. So what we learned from this is that lecanemab isn't cost effective at its current price.

And as I showed you in the value-based price benchmark estimate, it would need a substantial discount to reach value-based prices. So we presented all of this information, the clinical effectiveness, the cost effective models, the benefits beyond health to the CTAF during the public meeting. And it was a unanimous vote from CTAF that lecanemab is low long-term value for the money at its current price. The committee thought this was an area of high unmet need so that perhaps we would entertain higher benchmarks, but still, because the link between amyloid removal and clinical outcomes wasn't certain and the harms are potentially severe, they felt like that wasn't enough to overcome the high unmet need. So this is a drug that we felt and the CTAF felt, was low long-term value for the money.

So I'll turn it back over to Dr. Tice, he's gonna talk about a couple other medications. - Great, thanks Dr. Lin. So next I'm gonna talk about PCSK9 inhibitors for cardiovascular disease. Really effective therapy it turns out, but we have lots of other effective therapies to lower LDL cholesterol.

You know, statins, the annual cost is about $812. These are a little outdated, but generic statins, if you get them through Walmart or Mark Cuban's Cost Plus Drugs, you pay $10 for a three-month supply or $40 for a year supply of generic statins. So it's only $40 a year.

Where the average cost of the two PCSK9 inhibitors when we looked at them was almost $15,000. And the FOURIER trial was one of the two long-term outcome trials. Initially, when we looked at PCSK9 inhibitors, we just had data on LDL reduction and had to estimate how that LDL reduction would translate into reductions in strokes and heart attacks. But the FDA required a long-term trial to demonstrate real clinical benefit to these therapies and the FOURIER trial was one of those.

So this is based on the inclusion and exclusion criteria from the FOURIER trial. There were almost 9 million Americans who met the entry criteria and so would be eligible for PCSK9 inhibitor. And they're pretty effective therapy when you look at the number needed to treat to prevent one major cardiovascular event, it was only 37. And many people know we're often in the thousands, it's thousands people screened to prevent one breast cancer death. So this number needed to treat, even though Rita's raising her eyebrow, (chuckles) is not bad on the scale of many other therapies that we use routinely. But we said the threshold price to achieve good value needed to be much less than the $14,500 that was originally charged, so 71% discount in the price.

And so the assessment of the voting committee was that PCSK9 inhibitors are not cost-effective at conventional willingness to pay thresholds. And we needed this large reduction in the price. And you know, Dr. Lin put the price up earlier on an earlier slide, it's now down at a little under $6,000, so a 60% price decrease, but of course, nobody pays that. So they're actually paying less than this.

So they did put it on the market originally. Lots of barriers were put in place, nobody was getting it. Drug companies came down essentially to the ICER recommended price for the therapy. So it was an example of where I think we had a big impact on the cost. And again, because there were so many people, potentially, this would've cost $130 billion every year to the American healthcare system if we're paying at the original price.

But it's even at the reduced price, it's a substantial potential annual cost. So still an issue for us. So I'm being briefer. I'm gonna go on to CAR-T therapy and I'm gonna talk about when we did it, we also looked at it for adults with B-cell lymphomas as well. I'm just gonna talk about pediatric leukemia, again, just to give you an example.

So it was studied in children with relapsed and refractory or refractory ALL. That population has about a three-month median survival and CAR-T therapy represented potentially the only option for these patients. It's a novel therapy, many of you probably heard about it. You actually take somebody's T-cells out of their body, insert a gene into it, which is a hybrid of two genes, grow those cells up and then infuse them into the patients.

And the cost for an infusion or the whole process of harvesting the cells, generating the CAR-T and then infusing it back in was about half a million dollars. These patients get very, very sick with a much worse cytokine storm than COVID generates. And so many of them require ICU stays.

So the actual cost of receiving this therapy is much higher than the $500,000 and met some people, two clinical experts here were involved. And I know at UCSF, this had to go up to the highest level. The CEO basically had to approve each time we gave one of these therapies initially because of the potential impact on our healthcare system.

And there were a lot of limitations of the data. When this was approved, it was approved on single arm trials. As Rita taught me, we really want randomized trials and long enough to look at real clinical outcomes. And when you have single arm trials, you can't kinda compare them to any other therapies because you know, the populations are so unique, it's very, very hard to really do any kind of comparative effectiveness, which is usually the starting point for then cost model. So you need some sort of estimates of differences in clinical effectiveness. The trials were tiny, so the confidence intervals for whatever estimates we did use were quite wide.

So we really had a lot of uncertainty. And then these are kids, we had less than two, mostly we had less than one year of follow up in the initial studies, and yet we're projecting this out over the lifetime of these children. So tremendous amount of uncertainty on many, many levels here.

So this is that table where we calculate the incremental cost. So this gives you a little more insight into how you actually calculate an ICER. You look at the cost of the comparative therapy, clofarabine was what we looked at, the cost of one of the CAR-T therapies, Kymriah, and then you subtract one from the other. So the Kymriah costs more, so you get positive, it costs about $330,000 more. But our best estimate was that these kids would live on average 7.9 more years. And if you take into account the quality of life during that time, they weren't perfect life years.

So it was a little bit reduced, but many of these children would be cured and would live, you know, 60, 70, 80 more years. Others would die quickly. And we also do something called discounting. So over time, you know, a dollar spent today, is worth a lot less than a dollar spent or a lot more than a dollar spent 20 years from now. So we take that into account. We also do that for health outcomes.

So the life years also get discounted over time, which is why sometimes people think these numbers are really small, how can that be? But then you divide the incremental costs by the incremental life years and you get a cost per year of perfect life, a cost per QALY. And you know, these were our best estimates were less than $50,000, but again, with lots and lots of uncertainty. So the conclusions were these were likely to provide a large gains in a quality adjusted and overall survival. It seemed like the price was aligned with the value of the therapy.

So the estimate was likely to be of good value, but lots of uncertainty. So really looked forward to longer term outcomes and real world evidence to see whether what was done at the, you know, children's hospital in Pennsylvania, could be replicated in the real world as well. So with that, I'm gonna turn it back to Dr. Lin to summarize

and then we'll take questions. - All right, thanks Dr. Tice, that was, so hopefully that gave you some idea of how the process works and how we calculate value.

So again, I'm gonna go through these quickly. The ICER value of assessment framework is anchored on evidence, takes a long-term perspective and acknowledges the role of benefits beyond health and special ethical priorities when we assess value. And then as we've said, the potential impact to the budget does matter.

It's not just the the absolute cost, but how much is that gonna impact a health system's budget? Many payers use the reports that ICER produces to negotiate drug prices to ensure that prices are aligned with patient benefit and make formulary decisions to build value-based formularies. And this actually, you know, comes down to the physician and patient level, right? So if a drug is priced according to its value, then you know, for a payer might say, you know what? We're putting it on the lowest relevant tier, we're putting on the preferred tier, which means a lower out-of-pocket cost for your patient and we're not gonna make it subject to prior authorization, which for a lot of us is one of the things that we dislike most about practicing medicine is having to go through the prior authorization process. And so this could have benefits for both, not only, you know, on the health system as a whole, but also at the individual patient and physician levels.

Manufacturers are pushed to justify their prices and some have actually begun to factor in value in their initial lodge pricing. I will put the caveat in there, that industry sponsored, as you can probably imagine, industry sponsored cost effectiveness analyses tend to be higher. There's a study that looked at industry versus independent assessments and obviously industry assessments tend to be higher than the independent assessments. So it's really important to have an independent panel assessing value. Patient groups are working with ICER to approve access.

Meaning, you know, we want, not only we wanna make sure this is affordable, but we wanna make sure that, you know, a patient can get it, it's not great if it's affordable, but the insurance company puts up so many barriers that it's really hard to get. And then ICER also looks at what we start out with unsupported price increases and making sure there's fair access to fairly priced drugs. And these are also annual reports that ICER does in addition to the drug assessments. So as I mentioned earlier, UCSF has a long history with ICER, aside from Dr. Tice and I, Dr. Makam, Dr. Walsh have also served as evidence authors.

We've had several health economists from UCSF participate. And then the California Technology Assessment Forum is actually, of most often about half UCSF faculty, including Dr. Redberg who is here in the audience supporting us. And then as Dr. Tice mentioned,

a lot of clinical experts we are all reaching out to UCSF clinical experts all the time to understand the context for these treatments. So with that, I hope we've showed you that the current pricing system for drugs is high cost, but unrelated to benefits. And so value-based pricing is needed to better align price with benefits. And unlike most developed countries, we don't have a governmental body that does that.

So ICER sort of fill that role, but there are still a lot of challenges ahead. So with that, we thank you for your attention and we'll be happy to entertain questions. Thank you. (attendees applauding) - Thank you so much Dr. Lin and Dr. Tice for that fascinating talk and really the deep dive into healthcare economics and health policy. And like you said, your work is really filling a void because we don't have another agency that does that, unlike in the UK.

Some of our questions from the audience. So Dr. Komanduri, the Division Chief of UCSF Hema has also been involved with the CAR-T analyses and he asks, how might the value-based pricing be coupled with novel payment methods, for example, milestones-based pricing? And to clarify what that is for the audience, that's where you pay kinda over time for outcomes rather than in a fixed way regardless of results. So could you talk about how ICER might consider those new directions? - Can everybody hear me now? Yeah, there we go.

So, you know, CAR-T is a great example. Sometimes insurance companies and healthcare systems have negotiated deals where if the patient doesn't have a complete response by one month, you don't have to pay for the therapy for, I'm going back to Hep-C drugs. At one point they kinda had a Netflix model with some state Medicare where you pay one price and you get all you need. So we have something called a policy roundtable after the initial presentation of the evidence, hearing from the company's patients, the votes, after all that's done, our assessment of value is done, we then have another session where we just talk about the policy implications, including when appropriate innovative mechanisms for covering new therapies like this.

So really important. - And lemme just add that this is important because we're not a single-payer system and people change health insurance as frequently, so for CAR-T therapy, you might not see the benefits. You might pay the 500,000 or, you know, plus additional costs upfront as a healthcare payer insurance company, but you're not gonna see the benefits because that person then two years down the line, their parent gets a new job and they change health insurances. So this is a way to sort of, so a health insurance company might say, you know what? I don't really wanna pay for very many of these because I'm not gonna recoup the costs. And so outcomes-based contracting is also a way to help sort of make sure that it's not only based on outcomes, but then that the company might have some chance to recoup the costs even in the short term. So they're not laying out 500,000 right at the beginning.

They might, you know, say it's a hundred thousand, you know, as long as you have the patient survives and then, you know, if they survive for five years, it's another, you know, and so they take over time. So hopefully that helps clarify that. - And another question from the audience, and I'll come to you Dr. Redberg. Consider drugs that might fully eradicate a disease, you mentioned the Hep-C therapy. So how do you model out, you know, complete eradication of a disease if you had true equity and access to these medications for all who needed them? - Yeah, I mean, I think I alluded to it. I mean, you do factor in the costs of bad outcomes that are avoided.

So really important, I think that there was another point I was gonna make about that, but I think that that's the main thing. I'm sorry, I forgot what else I was gonna say. Grace, did you have anything else? - You know, I think this is becoming more of an issue because we now have gene therapy, you know? Which is often very expensive. I gave that example of the gene therapy for spinal muscular atrophy, it's $1.6 million. It seems like a huge sub, but you treat these patients, these children, you know, are very expensive and they don't live very long.

So basically, you're giving them a near normal life. And so I think, you know, we have to make decisions as a society as to how much value that has and what we're willing to pay for. And that is one of the challenges when you talk about a single therapy that's very expensive upfront, is at what point, you know, what are we willing to, how much are we willing to pay? How much, you know, should we pay for these transformative therapies? And can we afford to pay, you know, more gene therapies are coming out on the horizon. Can we afford to pay for all the gene therapies? That's a good question. - Yeah, thank you. That was actually the example. I did genes therapies for hemophilia.

One of them seems quite effective, was FDA approved, $3.1 million and yet we estimate that will actually be cost savings in part because the current management of patients with hemophilia is so expensive. And ICER itself, is thought deeply about this, they have a white paper on how do we price curative therapies? Mainly around genetic illnesses, hereditary blindness, things like that, that people live with their whole life and now we're gonna be able to cure them, how do we value that? And ICER updates its value assessment framework every three years based on input from pharmaceutical companies, other life science companies, insurers and things like that. So they're thinking about the, how to assess these special therapies every time and trying to refine the approach. - Dr. Rita Redberg, I think you had a question and comment.

- Sure, should I get a mic or? - The ceiling mics are on for you? - Oh, great. - Yes. - Okay, thanks. And great talk and I really do admire the work of ICER and as Grace and Jeff said, I think it really has changed the conversation and it was revolutionary in introducing the idea that we should include cost and the value, which it's a whole nother topic, but I did wanna just highlight, you know, the frustrations as a, you know, looking at the patient in the incredibly imperfect system that ICER has to operate in because you know, you mentioned it, but there's so much uncertainty and particularly with these newer drugs and accelerated approval pathways for drugs and for devices. I mean, I think Grace and Jeff mentioned sometimes we're looking at phase one studies for a 2 million because that means there have been a total of 20 patients that we're looking at, no control group, not blinded with kind of subjective or surrogate endpoints. And so you're trying to make the best decision, but this is not good data and particularly not when you know, when it works out, this is great, but when it doesn't work out it's a big problem.

And the other thing we don't do well in the US and Sarah and I are working on is post-market surveillance because, you know, in order to know is it gonna cure the disease or are these kids all gonna end up with cancer and dead in a few years? And you really do wanna know that you have to continue to collect the data and also act on the data. And unfortunately, we have very perverse incentives in the US so that we are not really collecting the data and we're not collecting adverse event data very well. We don't do well at reporting adverse events. It's estimate only 10% of all events get reported. I mean, for the Alzheimer's drugs there were several deaths in that drug group. It was a very insignificant clinical endpoint of great controversy.

And I mean, I will just tell one anecdote, which I think illustrates the problems when one of the CTAF meetings we were looking at metal-on-metal hips and this is probably 15 years ago, and at that time they had come out a few years before that and the orthopedic surgeon, they were all enraged and the idea was that they would last longer than what we had been using. And so there was a evidence review and there had been no randomized trials as Jeff mentioned. That is definitely the hierarchy of what we need to look at them. But people come and these people that come are generally people that have financial interests. This was an orthopedic surgeon from Southern California who was very keen on the technique and he told us, you know, it was great, it's the only thing he would use in his young patients.

And I asked him how he could be so certain when there was no randomized data and he looked at me, and he said, "Dr. Redberg, it would be unethical to do randomized trials if it's so good." Well a few months later they were off the market because there was a 40% revision rate with these so good metal-on-metal hips. And we only got that data because they actually do registries in Britain and we got their data and we got the Australian data, in the US, we didn't get that data. And we don't know that that doesn't happen with a lot of other things because we're not tracking it. So I think we definitely, ICER does the best job we can, but that's why it's so important to really demand high quality of evidence pre-market and this market.

- I'll say one of the things that often is talked about in the policy roundtable afterwards and specialty societies often step up to it, is to set up high quality registries to really follow these patients. We didn't talk about, I mean, the FDA often requires it, but of companies, but the majority of those studies never get done and never get published. They don't enroll. Well, there's a real problem and because there's no mechanism to punish companies for not doing it.

We really, I mean, sometimes ICER thinks when there's a lot of uncertainty, really what we ought to do is have a low initial price until we get better data and we have better data that the benefits outweigh the harms. And again, we're looking at both benefits and harms because, you know, many of these therapies have harms. We really get better data than the price can go up to reflect the better data. Of course, the drug companies won't hear that. - And I'll add that, you know, it is a constant struggle at ICER.

So we generally tend to review things that are just about to come on the market, as Jeff said, you time to, you know, when the drug has its approval date and that's because launch prices in the US are so important. So the initial price that a drug has, which is called we calls launch price, sort of sets the market, right? And so if you can influence that, you can have, you know, a lot of influence on how much a drug costs. On the other hand, a lot of times, as Dr. Redberg and as Jeff note, you know, we don't have the mature data. We don't. And so we're making a lot of assumptions and there's a lot of uncertainty.

And so, you know, it's this tension of when do we assess a drug and how, you know, how much data do we really need to assess value? And the truth is, this is sort of an ongoing process. And ICER often comes back years later and you know, if there's new data to reassess the value of a treatment. - That's wonderful. Well, this is a fascinating discussion. Thank you all so much.

I'm afraid we're out of time at the top of the hour. Thank you all so much for this educational talk and we'll see you all back next week.

2023-10-22 13:45

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