METHODOLOGICAL REVIEW AND QUALITY ASSESSMENT OF MODEL-BASED ECONOMIC EVALUATIONS OF PCSK9 INHIBITORS FOR CARDIOVASCULAR DISEASE: A SYSTEMATIC REVIEW
Author(s)
Lei Wang, MS1, Yifang Liang, MS2, Ying-dan Cao, MS1, Yuyanzi Zhang, BS2, Luying Wang, PhD2.
1School of Pharmacy, Xi'an Jiaotong University, Xian, China, 2School of International Pharmaceutical Business, China Pharmaceutical University, Nanjing, China.
1School of Pharmacy, Xi'an Jiaotong University, Xian, China, 2School of International Pharmaceutical Business, China Pharmaceutical University, Nanjing, China.
OBJECTIVES: To systematically review model-based economic evaluations of proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors for cardiovascular disease, summarize their methodological characteristics, and appraise reporting and methodological quality.
METHODS: This systematic review followed PRISMA guidance and was registered in PROSPERO (CRD42024558571). Five databases were searched from inception through June 2026. Model-based economic evaluations of PCSK9 inhibitors in adults with, or at risk of, cardiovascular disease were included. Study characteristics, model structures, treatment-effect modelling, cost and utility inputs, uncertainty analyses, and validation practices were extracted. Both reporting and methodological quality were assessed using the CHEERS 2022 and Philips checklists, respectively.
RESULTS: Forty-eight studies from 18 countries were included. Cost-utility analysis was the predominant framework (n=41, 85.4%). Cohort Markov models were most common (n=39, 81.3%), typically including myocardial infarction and stroke. Treatment effects were incorporated using three approaches: direct relative effects for cardiovascular endpoints derived from clinical trials, network meta-analyses, or comparative studies (n=20, 41.7%); LDL-C surrogate-based approaches, which translated treatment-related LDL-C reductions into cardiovascular event-risk reductions using epidemiologic risk relationships (n=24, 50.0%); and hybrid approaches combining both methods (n=4, 8.3%). Twenty-five studies (52.1%) combined long-term or lifetime horizons with constant treatment-effect assumptions. Additionally, only 14 studies (29.2%) explicitly modelled or explored adherence or treatment discontinuation. Among 11 Asian-setting studies, local utility evidence was often unavailable. Parameter uncertainty was generally assessed (n=42, 87.5%), whereas structural uncertainty, model validation, and transparent reporting of half-cycle correction and cost-year adjustment remained limited.
CONCLUSIONS: Although long-term horizons were generally appropriate for cardiovascular prevention, many models treated treatment effects as static over time, limiting their ability to reflect evolving treatment exposure. Future evaluations should better characterize clinically plausible changes in treatment exposure and effectiveness over time. Structural uncertainty analysis, robust model validation, and locally relevant inputs would improve model credibility and decision relevance.
METHODS: This systematic review followed PRISMA guidance and was registered in PROSPERO (CRD42024558571). Five databases were searched from inception through June 2026. Model-based economic evaluations of PCSK9 inhibitors in adults with, or at risk of, cardiovascular disease were included. Study characteristics, model structures, treatment-effect modelling, cost and utility inputs, uncertainty analyses, and validation practices were extracted. Both reporting and methodological quality were assessed using the CHEERS 2022 and Philips checklists, respectively.
RESULTS: Forty-eight studies from 18 countries were included. Cost-utility analysis was the predominant framework (n=41, 85.4%). Cohort Markov models were most common (n=39, 81.3%), typically including myocardial infarction and stroke. Treatment effects were incorporated using three approaches: direct relative effects for cardiovascular endpoints derived from clinical trials, network meta-analyses, or comparative studies (n=20, 41.7%); LDL-C surrogate-based approaches, which translated treatment-related LDL-C reductions into cardiovascular event-risk reductions using epidemiologic risk relationships (n=24, 50.0%); and hybrid approaches combining both methods (n=4, 8.3%). Twenty-five studies (52.1%) combined long-term or lifetime horizons with constant treatment-effect assumptions. Additionally, only 14 studies (29.2%) explicitly modelled or explored adherence or treatment discontinuation. Among 11 Asian-setting studies, local utility evidence was often unavailable. Parameter uncertainty was generally assessed (n=42, 87.5%), whereas structural uncertainty, model validation, and transparent reporting of half-cycle correction and cost-year adjustment remained limited.
CONCLUSIONS: Although long-term horizons were generally appropriate for cardiovascular prevention, many models treated treatment effects as static over time, limiting their ability to reflect evolving treatment exposure. Future evaluations should better characterize clinically plausible changes in treatment exposure and effectiveness over time. Structural uncertainty analysis, robust model validation, and locally relevant inputs would improve model credibility and decision relevance.
Conference/Value in Health Info
2026-11, ISPOR Europe 2026, Vienna, Austria
Value in Health, Volume 29, Issue 12S
Code
MSR128
Topic
Economic Evaluation, Health Technology Assessment, Methodological & Statistical Research
Disease
Cardiovascular Disorders (including MI, Stroke, Circulatory), No Additional Disease & Conditions/Specialized Treatment Areas