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Research Letter
August 22/29, 2017

Updated Cost-effectiveness Analysis of PCSK9 Inhibitors Based on the Results of the FOURIER Trial

Author Affiliations
  • 1Division of Cardiology, Zuckerberg San Francisco General Hospital, San Francisco, California
  • 2Center for Vulnerable Populations, Zuckerberg San Francisco General Hospital, San Francisco, California
  • 3Division of General Internal Medicine, Columbia University Medical Center, New York, New York
  • 4Institute for Clinical and Economic Review, Boston, Massachusetts
  • 5Department of Medicine, University of California, San Francisco
JAMA. 2017;318(8):748-750. doi:10.1001/jama.2017.9924

A cost-effectiveness analysis of proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors based on their lowering of low-density lipoprotein cholesterol (LDL-C) demonstrated that the 2015 price of PCSK9 inhibitors would need to be reduced by more than two-thirds (to $4536 per year) to meet generally accepted cost-effectiveness thresholds.1 Since that report, the Further Cardiovascular Outcomes Research With PCSK9 Inhibition in Subjects With Elevated Risk (FOURIER) trial found the PCSK9 inhibitor evolocumab reduced risk of major adverse cardiovascular events (MACE; myocardial infarction, stroke, or cardiovascular death).2 This study assessed how the cost-effectiveness of PCSK9 inhibitors is altered by the FOURIER results and current prices.

Methods

As with the prior analysis,1 the Cardiovascular Disease Policy Model (CVDPM) was used to estimate the cost-effectiveness of PCSK9 inhibitors or ezetimibe added to statin therapy among US adults with atherosclerotic cardiovascular disease (ASCVD) from a health system perspective and a lifetime analytic horizon. The primary outcome was the incremental cost-effectiveness ratio (ICER; incremental health care costs per quality-adjusted life-year [QALY] gained). The secondary outcome was the drug cost at which PCSK9 inhibitors would become cost-effective at a willingness-to-pay threshold of $100 000/QALY.

The simulation cohort in this update approximated the FOURIER inclusion criteria (US adults aged 40-80 years with ASCVD and LDL-C ≥70 mg/dL [to convert to mmol/L, multiply by 0.0259] despite statin therapy, based on 2005-2012 National Health and Nutrition Examination Surveys [NHANES]).3 Reductions in myocardial infarction and stroke risk were estimated from FOURIER, with separate hazard ratios for the first year and subsequent years to account for the increasing effectiveness over time observed in the trial (Table 1). Drug costs were based on current wholesale acquisition costs ($3818 for ezetimibe [32% increase between 2015 and 2017] and $14 542 for PCSK9 inhibitors [1% increase between 2015 and 2017])4; all other health care costs were inflated to 2017 US dollars. Because PCSK9 inhibitors did not reduce risk of cardiovascular death in FOURIER, we conducted an additional analysis with no effect on cardiovascular death except as a direct result of lowering myocardial infarction or stroke risk. Table 1 compares the approach in the prior analysis and this update.

Table 1.  
Comparison of Input Parameters for the Prior Cost-effectiveness Analyses Using LDL-C Lowering vs the Current Analysis Based on FOURIER Trial Criteria
Comparison of Input Parameters for the Prior Cost-effectiveness Analyses Using LDL-C Lowering vs the Current Analysis Based on FOURIER Trial Criteria

The CVDPM is programmed in Fortran 95 (Lahey Computer Systems). Outcomes were analyzed using QuickBasic 64 and Excel 2011 (Microsoft); statistical analyses were performed using SAS (SAS Institute), version 9.4, and Stata (StataCorp), version 13.

Results

Approximately 8.9 million US adults meet the age, ASCVD, LDL-C, and statin treatment criteria of FOURIER. Based on NHANES, this population is 61% men (95% CI, 55%-67%), with a mean age of 66 years (95% CI, 65-68), mean LDL-C of 104 mg/dL (95% CI, 100-108), and diabetes proportion of 33% (95% CI, 28%-39%). The CVDPM accurately reproduced FOURIER MACE rates (statin only: FOURIER estimate, 3.7% in year 1, 3.7% in year 2; CVDPM, 3.6% in year 1, 3.8% in year 2; statin plus PCSK9 inhibitors: FOURIER estimate, 3.1% in year 1, 2.7% in year 2; CVDPM, 3.0% in year 1, 2.7% in year 2). Adding PCSK9 inhibitors to statins was estimated to prevent 2 893 500 more MACE compared with adding ezetimibe, at an ICER of $450 000/QALY (80% uncertainty interval, $301 000-$787 000) (Table 2). Reducing annual drug costs by 71% (to ≤$4215) would be needed for PCSK9 inhibitors to be cost-effective at a threshold of $100 000/QALY. Assuming no direct effect on cardiovascular death as observed in FOURIER, the ICER increased to $1 795 000/QALY.

Table 2.  
Clinical and Economic Outcomes of Treatment Strategies in ASCVDa
Clinical and Economic Outcomes of Treatment Strategies in ASCVDa
Discussion

PCSK9 inhibitor use in patients with ASVCD was not cost-effective at 2017 prices, and these updated analyses based on FOURIER estimates suggest that even greater price reductions than previously reported are required to meet cost-effectiveness thresholds. The 71% price reduction required to make PCSK9 inhibitor therapy cost-effective is greater than the 25% to 30% discounts typically offered by manufacturers.5 A rebate model proposed by 1 PCSK9 inhibitor manufacturer6 (refunding the drug costs if patients experience MACE while receiving PCSK9 inhibitor therapy) is also unlikely to meaningfully reduce drug expenditures given the low overall MACE rate (approximately 3% per year). Although computer simulations that synthesize data from observational studies and clinical trials may not precisely reflect clinical effectiveness that may be observed in practice over time, these updated results continue to demonstrate that reducing the price of PCSK9 inhibitors remains the best approach to delivering the potential health benefits of PCSK9 inhibitors therapy at an acceptable cost.

Section Editor: Jody W. Zylke, MD, Deputy Editor.
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Article Information

Corresponding Author: Kirsten Bibbins-Domingo, PhD, MD, MAS, Division of General Internal Medicine, Zuckerberg San Francisco General Hospital, University of California, San Francisco, PO Box 1364, San Francisco, CA 94143-1364 (kirsten.bibbins-domingo@ucsf.edu).

Author Contributions: Drs Kazi and Bibbins-Domingo had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Kazi, Moran, Ollendorf, Tice, Bibbins-Domingo.

Acquisition, analysis, or interpretation of data: Kazi, Penko, Coxson, Ollendorf, Tice, Bibbins-Domingo.

Drafting of the manuscript: Kazi, Moran, Bibbins-Domingo.

Critical revision of the manuscript for important intellectual content: Kazi, Penko, Coxson, Ollendorf, Tice, Bibbins-Domingo.

Statistical analysis: Kazi, Coxson, Bibbins-Domingo.

Obtained funding: Ollendorf.

Administrative, technical, or material support: Penko, Ollendorf.

Supervision: Kazi, Bibbins-Domingo.

Conflict of Interest Disclosures: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Dr Ollendorf reports being an employee of the Institute for Clinical and Economic Review, which is funded by grants from the Laura and John Arnold Foundation, Blue Shield of California Foundation, and the California Healthcare Foundation. The organization’s annual summit is supported by dues from Aetna, America’s Health Insurance Plans, Anthem, Blue Shield of California, CVS Caremark, Express Scripts, Harvard Pilgrim Health Care, Omeda Rx, United Healthcare, Kaiser Permanente, Premera Blue Cross, AstraZeneca, Genentech, GlaxoSmithKline, Johnson & Johnson, Merck, National Pharmaceutical Council, Takeda, Pfizer, Novartis, Eli Lilly, and Humana. Dr Tice reports receiving grant funding from the Institute for Clinical and Economic Review. No other disclosures are reported.

Funding/Support: This work was supported by the University of California, San Francisco.

Role of Funder/Sponsor: The funder had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Additional Contributions: We thank Eugene C. Fairley, MS (Linqia), for developing and refining the Monte Carlo Simulation module for the Cardiovascular Disease Policy Model, which was used to generate the uncertainty intervals in this analysis. This work was performed while he was employed as a research analyst at the University of California, San Francisco.

References
1.
Kazi  DS, Moran  AE, Coxson  PG,  et al.  Cost-effectiveness of PCSK9 inhibitor therapy in patients with heterozygous familial hypercholesterolemia or atherosclerotic cardiovascular disease.  JAMA. 2016;316(7):743-753.PubMedGoogle ScholarCrossref
2.
Sabatine  MS, Giugliano  RP, Keech  AC,  et al.  Evolocumab and clinical outcomes in patients with cardiovascular disease.  N Engl J Med. 2017;376(18):1713-1722.PubMedGoogle ScholarCrossref
3.
National Center for Health Statistics.  National Health and Nutrition Examination Survey, 2005-2012. https://www.cdc.gov/nchs/nhanes/nhanes_questionnaires.htm. Accessed March 28, 2017.
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Truven Health Analytics.  Red Book Online. http://truvenhealth.com/products/micromedex/product-suites/clinical-knowledge/red-book/about. Accessed April 10, 2017.
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Beasley  D, Hummer  C.  Update 1—Amgen discounts cholesterol drug, but payers want more. http://www.reuters.com/article/heart-amgen-pricing-idUSL2N1GU23H. Accessed April 8, 2017.
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Amgen.  Amgen and Harvard Pilgrim agree to first cardiovascular outcomes-based refund contract for Repatha (Evolocumab). https://www.amgen.com/media/news-releases/2017/05/amgen-and-harvard-pilgrim-agree-to-first-cardiovascular-outcomesbased-refund-contract-for-repatha-evolocumab/ Accessed June 10, 2017.
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