Systematic Review of Cost-utility Analysis Methodology for PD- 1/PD-L1 Inhibitors in the Treatment of Non- small Cell Lung Cancer / 中国药房

ABSTRACT

OBJECTIVE：To provide reference for impro ving the quality of programmed cell death protein 1 （PD-1）/ programmed cell death 1 ligand（PD-L1）inhibitors in the treatment of non-small cell lung cancer related pharmacoeconomic studies in China. METHODS ：Retrieved from Embase ，PubMed，Medline，Cochrane Library ，CNKI，Wanfang database ，VIP and other Chinese and English database ，cost-utility studies about PD- 1/PD-L1 inhibitors in the treatment of non-small cell lung cancer published during Jan. 2016-Jan. 2021 were collected. The data of the included studies were extracted. After the quality of the included studies was evaluated by using the Consolidated Health Economic Evaluation Reporting Standards list ，the relevant data were summarized and compared from the aspects of model framework ，model parameters and uncertainty analysis. RESULTS & CONCLUSIONS：A total of 17 studies were finally included ，the overall quality of them was high but the differences in methodology were great. Markov model or partition survival model based on three states was adopted for 16 studies. The time horizon ranged from 5 years to lifetime ；the cycle length ranged from 1 week to 6 weeks. A total of 8 studies used the standard parameter distribution method for parameter fitting ，and 7 studies additionally adopted other parameters estimation methods as KM curves or spline models. Eleven studies performed the validation of model extrapolation. All studies considered the direct medical costs and reported the incremental cost-effectiveness ratio using quality-adjusted life years as the health outcome. Sixteen studies conducted the deterministic sensitivity analysis and probabilistic sensitivity analysis to improve the stability of the model. It is suggested that studies should keep the integrity of the report ； format，choose the appropriate positive comparators ，selectthe health economic model and construct reasonable assumptions according to the available data format ， use Cholesky decomposition to explore the uncertainty of the parameter fitting ， perform the validation of extrapolation combined with external data and use the appropriate indirect comparison in the absence of the head-to-head clinical trials to improve the quality of related pharmacoeconomic studies in China.