Trends of Cost-Effectiveness Over Time
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Trends of Cost-Effectiveness Over Time
- 1. Trends of Cost-Effectiveness Over Time Benjamin P. Geisler, M.D., M.P.H. Massachusetts General Hospital/Harvard Medical School, Boston MA; Wing Tech Inc., Menlo Park CA; Flinders University, South Australia Pre-ASCO Seminar: (Re)Defining Value in Cancer Care: Priorities for Patients, Providers, and Health Systems Panel: International Experience with Health Technology Assessment (HTA) & Lessons for the United States, Chicago IL, 5/30/2019
- 2. Outline • # of CEAs in Oncology Over Time • Effectiveness Gains Over Time • Cost Increases Over Time • Additional Costs of PD1/PDL1 and CAR-T • Audience Interaction • Incremental Costs/Effectiveness Over Time • Budget Impact Over Time • Conclusions
- 3. # of CEAs in Oncology Increases Over Time 310 345 320 307 411 480 468 644 614 727 14% 14% 17% 17% 17% 20% 19% 17% 13% 20% 0 100 200 300 400 500 600 700 800 900 1000 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 #ofStudies Cancer (% of total # of CEAs published for the year) Non-Cancer Slide courtesy of Dan Ollendorf, PhD; CEA=cost-effectiveness analysis; data from Tufts’ Cost-Effectiveness Analysis (CEA) Registry; tests for trend using absolute numbers and Cuzick’s test Test for trend: p=0.006 Test for trend: p=0.007
- 4. Effectiveness Gains Over Time • Cancer treatments have evolved Chart adapted from azimmuno-oncology.com and A Ribas et al. Clin Cancer Res. 2012 Universally Cytotoxic Chemotherapy Targeted Therapy Checkpoint Inhibitors Chimeric Antigen Receptor (CAR) T-cell Therapy
- 5. Effectiveness Gains Over Time • We are all aware that costs for cancer treatments have increased • So is the “value” (incremental cost-effectiveness ratio) generally worse now? • Not necessarily, because the effectiveness (overall survival, quality-adjusted life years) has also increased • Patients on newer therapies experience “financial toxicity” • Are cancer treatments also exceeding affordability (i.e., have a large budget impact) of payors like Medicare and private health insurance co.s • Not necessarily, because usually only a small group of patient qualifies for a treatment • However, this might not be true for PD1/PDL1 checkpoint inhibitors which are both trialed in a variety of indications and also frequently used off-label
- 6. Additional Costs of PD1/PDL1 and CAR-T Pembrolizumab Nivolumab Nivolumab+Ipilimumab Atezolizumab Durvalumab Tisagenlecleucel Axicabtagene Ciloleucel $K $100K $200K $300K $400K $500K $30K $60K $48K -$2K $110K $26K $108K $144K $329K $462K CAR-T PD-L1 PD-1 Data from own unpublished analysis (PD1/PDL1, 10-year time horizon, discounted) and the Institute for Clinical and Economic Review’s 2018 CAR-T Final Evidence Report (CAR-T, lifetime horizon, discounted)
- 7. Likert Scale: How likely is it that PD1/PDL1 will be cost-effective? Remove the icon above when building your slides. The presentation platform will automatically input the icon beneath your slide.
- 8. Additional Costs of PD1/PDL1 and CAR-T Pembrolizumab Nivolumab Nivolumab+Ipilimumab Atezolizumab Durvalumab Tisagenlecleucel Axicabtagene Ciloleucel $K $100K $200K $300K $400K $500K $30K $60K $48K -$2K $110K $26K $108K $144K $329K $462K CAR-T PD-L1 PD-1 Data from own unpublished analysis (PD1/PDL1, 10-year time horizon, discounted) and the Institute for Clinical and Economic Review’s 2018 CAR-T Final Evidence Report (CAR-T, lifetime horizon, discounted)
- 9. Likert Scale: How likely is it that CAR-T will be cost-effective? Remove the icon above when building your slides. The presentation platform will automatically input the icon beneath your slide.
- 10. Incremental Costs/Effectiveness Over Time S Cressman et al. The Oncologist 2015 1L met. breast ca 2L met. breast ca 1L met. CRC 2L met. CRC 1L adv NSCLC 2L adv NSCLC
- 11. Incremental Costs/Effectiveness Over Time DH Howard et al. J Econ Perspectives 2015
- 12. Incremental Costs/Effectiveness Over Time Beta coefficients and p-values were derived from generalized linear models; ASCO & ESMO (European Society of Medical Oncology) scores are measures of effectiveness in the societies’ respective value frameworks; source: R Saluja et al. JCO 2018
- 13. Incremental Costs/Effectiveness Over Time New strategy Comp. Indication Trial basc ICERsens. ICER Nivolumab Chemo SCC H+N Checkmate 141 dom. 4,361 Pembrolizumab+chemo Chemo NSCLC Keynote 189 28,804 dom. Atezolizumab Docetaxel NSCLC OAK 41,487 75,268 Pembrolizumab Chemo Urothel. Keynote 045 42,064 69,400 Pembrolizumab Chemo NSCLC Keynote 024 79,303 204,026 Nivolumab+Ipilimumab Sunitinib RCC Checkmate 214 95,278 301,438 Durvalumab+chemorad.Chemorad. NSCLC Pacific 198,376 adjuvant Source: own analysis (unpublished) based on 10-year extrapolation of trial data via survival models; base case models treatment as in trial; sensitivity analysis models treatment until progression of disease
- 14. Incremental Costs/Effectiveness Over Time New strategy Comp. Indication Trial basc ICERsens. ICER Nivolumab Chemo SCC H+N Checkmate 141 dom. 4,361 Pembrolizumab+chemo Chemo NSCLC Keynote 189 28,804 dom. Atezolizumab Docetaxel NSCLC OAK 41,487 75,268 Pembrolizumab Chemo Urothel. Keynote 045 42,064 69,400 Pembrolizumab Chemo NSCLC Keynote 024 79,303 204,026 Nivolumab+Ipilimumab Sunitinib RCC Checkmate 214 95,278 301,438 Durvalumab+chemorad.Chemorad. NSCLC Pacific 198,376 adjuvant Tisagenlecleucel Clofarabine B-ALL B2202, ENSIGN 41,656 n.a. Axicabtagene Ciloleucel Chemo B-NHL ZUMA-1 112,146 n.a. Data from own unpublished analysis (PD1/PDL1, 10-year time horizon, discounted $/LY) and the Institute for Clinical and Economic Review’s 2018 CAR-T Final Evidence Report (CAR-T, lifetime horizon, discounted $/LY)
- 15. Budget Impact Over Time 1L = 1st line, 2L+ = 2nd line or beyond etc.; * withdrawal in place/considered Chart courtesy of IQVIA Institute: Global Oncology Trends 2018; sources: FDA, IQVIA, National Sales Perspective 2018 * *
- 16. Budget Impact Over Time Chart courtesy of IQVIA Institute: Global Oncology Trends 2018; source: IQVIA, based on longitudinally linked claims data Total # U.S. Patients treated with PD1/PDL1 in ’17: 147,699
- 17. Budget Impact Over Time Chart courtesy of IQVIA Institute: Global Oncology Trends 2018; source: IQVIA and MIDAS data Comparison of Cancer Drug Spending: 2012 vs 2017 with Components Broken Out
- 18. Conclusions • Cost-effectiveness and budget impact have changed over time: • Immunotherapies (both checkpoint inhibitors and CAR-T) might arguably offer a better “bang for the buck”, compared to other targeted therapies, at least in formal assessments of trial-based data • However, there is a steady increase in total U.S. drug expenditures that seems to be driven by the uptake of PD1/PDL1 • The future value of immunotherapies will largely depend on whether “real world” data match those from the clinical studies to-date • Using PD1/PDL1s off-label could lead to less effectiveness than projected from pivotal trial extrapolations while also driving up budget impact • CAR-T needs 1) trial or matched comparison and 2) resource utilization (incl SCT, supportive care, retreatment) data Twitter: @ben_geisler
Editor's Notes
- Thank you, Professor Sullivan. It is great to be here. First, my disclosures as a health economic outcomes research consultant.
- So in the next 20 minutes, we’ll talk about trends over time. First, we’ll look at the growth of published cost-effectiveness analyses in oncology as a share of the whole field. We’ll then talk about how effectiveness has involved over the last two decades. Then, we’ll look at some more recent cost increases. We’ll then get some predictions from you – if I may ask you to open the ASCO app npw for that purpose and select this panel and talk. We’ll then look at cost-effectiveness trends over time. First, the whole field, undifferentiated if you will, until around 2014 or so. And then we’ll single out PD1/PDL1 and CAR-T. Before concluding, we’ll think about affordability or budget impact.
- So first, the published cost-effectiveness literature. These numbers are from the Tuft’s CEA registry – actually from Dr. Ollendorf here - which, if you haven’t come across it yet, is a great resource. So these are just full economic evaluations with ratios, not cost-minimization (that’s pure costing studies) or cost-benefit analyses (where costs are monetized) – just cost-effectiveness or -utility analyses. Unsuprisingly, both the absolute numbers for the non-cancer and the cancer CEAs has been growing over time. What NOT on this slide, and it’s actually harder to get more recent numbers on this – is that even though CEA is not FORMALLY used in the U.S. (Peter Neumann said in a 2005 book that it was “used under the radar” – every private payor has their tech assessment center, there is some evidence that CMS, the Centers for Medicare and Medicaid Services – at least notices it, and the United States Preventive Services Taks Force which, for example, looks at cancer screening, finds CEAS quote “helpful” – that the majority of these studies (meaning greater than 50%) is actually from U.S. researchers conducted for U.S. settings, with U.S. costs.
- For the effectiveness side of things, just a few general observations. Whether you’re a practicing oncologist or – I am not, I’m a hospitalist, in terms of cancer I see mostly see adverse events that require admission – we’ve witness the evolution from universally cell-toxic chemo via targeted therapy for other targets, and then, finally, to immunotherapy via inhibition of immune system “check points”, CTLA-4, PD1, PDL1, and now CAR-T-leukocyte therapy “made to order” for each individual patient. While targeted therapy led to longer remissions – look at the schematized curve in purple here, compared to the dark blue chemo one – with immunotherapy you often have different-looking survival curves – kind of a “plateau effect” – which might have led to a higher use of the c-word, cure, for some patients.
- So while these things are all very costly – does that mean that the comparative value has gone down? Not necessarily, because effectiveness, in overall survival or in QALYs, has also increased. But patients – and health insurers question mark – experience this thing called “financial toxicity” And for payors that depends on the absolute number treatment-eligible cases in your insured cohort and of course the costs per treatment incl all the downstream effects from it. More on that later.
- So here are the incremental costs – meaning the costs of the newer treatment minus the ones of the old ones – of the PD1/PDL1 trials and the uncontrolled T-CAR studies that led to approval. The latter two are taken from the Institute for Clinical and Economic Review (or ICER’s) HTA. The incremental PD1/PDL1 are from Dr. Sharon’s an my own analysis, from Red Book prices. You can see that they vary quite a bit by trial and agent. So if you keep just these PD1/PDL1 costs here in mind..
- how likely do you think that PD1/PDL1-based regimens will be cost effective. Please pull up your app – go to the panel and talk and vote.
- Keep the app open, please. Now, let’s get your temperature on those CAR-T costs. What’s notable in this context is that some more recent observational studies have shown quite high additional costs for what’s called “supportive care” – including those extreme cases where patients spend weeks & weeks in the ICU due to their cytokine storm. They also don’t include retreatment.
- So now for CAR-T. How likely do you think that this will be cost-effective?
- OK, so now we’ll look at costs and effectiveness at the same time. This 2015 review looked back at approvals for various indications, 1st/2nd line breast, colo-rectal, and non-small cell lung cancer, until 2013 and plotted the incremental effectiveness in filled squares on the y-axis #1 (on the left) with the year of approval on the x-axis. Costs on the second y-axis are the outlined squares. They then fitted a linea regression for both costs and effectiveness. Just by glancing at the slopes of the dashed lines you can see that costs went up while effectiveness only went up for some of the indications, breast cancer and 1st line colorectal, and went down for the others – and for breast cancer, effectiveness is expressed as progression-free not overall survival. However, all of these studies are all just based on the survival gains from the trials – these are not long-term extrapolations, which might lead to higher effectiveness and maybe also slightly higher direct medical costs.
- Here’s a similar analysis by Howard and colleages, also from 2015 with approvals until 2014, except you already have, conveniently, your ICER in dollars per QALY on just one y-axis. The authors fitted a regression of the natural logarithm of these ICERs, and you can see that it increases quite a bit, from 60, 65-thousand to a bit over 200-thousand. However, there are some studies included here which only reported progression-free survival – the gray triangles – and only the outlined squares are long-term results from model projections.
- This analysis is from 2018, with approvals until 2015 – and it expresses costs and effects separately – costs in blue on the left y-axis and effectiveness in yellow on the right one. Note that effectiveness here is expressed in ASCO and the ESMO, the European Society for Medical Oncology scores. These also take into account health-related quality of life. They fitted generalized linear models and per the p-values from those – or you can see it already from the slopes of the curves – incremental effectiveness is flat on the left or even goes down on the right (again, this is incremental effectiveness compared to older regimens) while costs seem to upslope particularly in those last years. Two PD1 inhibitors, pembro and nivo, were approved in late 2014, but we don’t know whether or not they’re included here. So to recap a little bit, we have a mix of more advanced chemo regimens and targeted therapies (and then maybe some PD1 here at the end) and – what all 3 analyses seem to show is that additional value for extra money seemed to be generally getting worse.
- For PD1/PDL1, these are cost-effectiveness results from model-based 10-year extrapolations from Dr. Sharon’s and my own work. It’s work in progress. We took overall survival from the pivotal trials that led to approval for a particular agents and fitted survival models. In Markov models, we then computed discounted life years up to 10-year follow up as well as Red book costs, that’s average wholse sale prices in the year of approval. As you can see in the second to last column, the base case ICERs are mostly below those thresholds of either 50,000, 100,000, or 200,000 $/QALY that Peter Neumann mentioned in a 2014 New England journal paper. Nivo for head and neck was economically dominant (meaning better overall survival and lower costs). As a sensitivity analysis, we looked at a more extreme case, treatment until survival, with generall higher ICERs.
- If you compare this with CAR-T – these are the the Institute for Clinical and Economic Review’s ICERs from their final report you can see that despite the high incremental costs that I showed earlier, the ICERs are actually in a range that could be considered cost-effective. This might be less surprising for Tisagenlecleucel – sorry, I’m not supposed to use brand names – as patients with B-precursor ALL had to be under 30 and the median age in B2202 was 12. Generally, the younger a cohort for a new intervention with increased long0term survival – remember the plateaued survival curves from earlier), the more likely it is economically favourable – despite discounting and high costs. There two things two note on these findings The long0term effectiveness can change quite a bit based on what assumptions you model, so the donominator could easily change quite a bit compared to other CEAs, and just small changes can have a BIG impact on ICERs And 2) on the cost side, there are also several X-factors on which we are just beginning to get some more claity. Those “supportive” care costs for CAR-T that I’ve mentioned, the need for retreatment, development of resistance etc.
- So switching grea one last time, a treatment could be cost-effective – meaning it adds additional life years at an acceptable cost PER THOSE LIFE YEARS – but that could amount to a lotta money, making those treatments take up a bigger part of a payor’s increased budget and thus potentially unaffordable. We call this budget impact. Here you see the sold PD1/ODL1 units over time – globally, with all of those agents’ approval dates noted. You can see that the curve in early to mid 2015 seemed to tilt the curve quite a bit upward here after approvals as 2nd line for advanced melanoma, and 2nd line for advanced squamous non-small cell.
- In the U.S., from linked claims data, there were around 150,000 patients in 2017 alone that were treated with PD1/PDL1s. The majority was lung and then there’s also quite a bit melanoma – maybe owing to that ealy approval. There’s not much colorectal or breast cancer cases. In these numbers included are patients who are treated off-label.
- Now in terms of budget impact, the spending on cancer drugs has about doubled over five years. And about 2/3s of that increase is from PD1/PDL1s
- So in conclusion, cost-effectiveness and budget impact have both changed over time. Immunotherapies might arguably provider a higher valued compared to targeted therapies and advanced chemo regimens, at least in those more formal assessments of data from trials. However, the is a steady increase in expenditures for drug costs in the U.S. in the last years and that seems to be driven by the PD1/PDL1 uptake. The future value of immunotherapies will large depend on if the real world efficacy will be the same (or better or wose), compared to trial results: particularly if PD1/PDL1 off-label use does not lead to the same health results as those from trials, that drives up the budget while not providing the value that we hope for. CAR-T needs matched comparison and then also more resource utilization data to update economic analyses.