Supplementary materials: Bayesian hierarchical model-based network meta-analysis to overcome survival extrapolation challenges caused by data immaturity

These are peer-reviewed supplementary materials for the article 'Bayesian hierarchical model-based network meta-analysis to overcome survival extrapolation challenges caused by data immaturity' published in the Journal of Comparative Effectiveness Research.Figure S1: Network of evidenceFigure S2: Observed survival by reference trial vs predicted survival with standard Weibull mixture-cure model network meta-analysisFigure S3: Observed survival by reference trial vs predicted survival with BH WCM NMA with τ' = σ’ = 0.01Table S1: Overview of parameters, confidence intervals, effective sample size and Rhat by approach testedFigure S4: Density plots with the numbers corresponding to the parameter numbers in supplementary Table S1Figure S5: Autocorrelation plots on the cure parametersAim: This research evaluated standard Weibull mixture cure (WMC) network meta-analysis (NMA) with Bayesian hierarchical (BH)WMCNMAto inform long-term survival of therapies. Materials & methods: Four trials in previously treated metastatic non-small-cell lung cancer with PD-L1 >1% were used comparing docetaxel with nivolumab, pembrolizumab and atezolizumab. Cure parameters related to a certain treatment class were assumed to share a common distribution. Results: Standard WMC NMA predicted cure rates were 0.03 (0.01; 0.07), 0.18 (0.12; 0.24), 0.07 (0.02; 0.15) and 0.03 (0.00; 0.09) for docetaxel, nivolumab, pembrolizumab and atezolizumab, respectively,with corresponding incremental life years (LY) of 3.11 (1.65; 4.66), 1.06 (0.41; 2.37) and 0.42 (-0.57; 1.68). The Bayesian hierarchical-WMC-NMA rates were 0.06 (0.03; 0.10), 0.17 (0.11; 0.23), 0.12 (0.05; 0.20) and 0.12 (0.03; 0.23), respectively, with incremental LY of 2.35 (1.04; 3.93), 1.67 (0.68; 2.96) and 1.36 (-0.05; 3.64). Conclusion: BH-WMC-NMA impacts incremental mean LYs and cost–effectiveness ratios, potentially affecting reimbursement decisions.

本数据集为发表于《比较有效性研究杂志》的论文《基于贝叶斯分层模型的网络荟萃分析以克服数据不成熟导致的生存外推挑战》的同行评审补充材料。图S1：证据网络图；图S2：参考试验观察到的生存率与标准韦伯尔混合治愈模型网络荟萃分析预测的生存率对比；图S3：参考试验观察到的生存率与BH WCM NMA预测的生存率对比，其中τ' = σ’ = 0.01；表S1：通过测试方法概述的参数、置信区间、有效样本量和Rhat值；图S4：密度图，其中数字对应补充表S1中的参数编号；图S5：治愈参数的自相关图。研究目的：本研究评估了标准韦伯尔混合治愈（WMC）网络荟萃分析（NMA）与贝叶斯分层（BH）WMC-NMA，以提供关于疗法长期生存的信息。材料与方法：选取了四项已治疗的转移性非小细胞肺癌临床试验，其中PD-L1 >1%，比较了多西他赛与尼伏单抗、派姆单抗和阿替利珠单抗。假设与某一治疗类别相关的治愈参数具有共同的分布。结果：标准WMC-NMA预测的治愈率分别为0.03（0.01；0.07）、0.18（0.12；0.24）、0.07（0.02；0.15）和0.03（0.00；0.09）对应于多西他赛、尼伏单抗、派姆单抗和阿替利珠单抗，相应的增量寿命年（LY）分别为3.11（1.65；4.66）、1.06（0.41；2.37）和0.42（-0.57；1.68）。贝叶斯分层-WMC-NMA的比率分别为0.06（0.03；0.10）、0.17（0.11；0.23）、0.12（0.05；0.20）和0.12（0.03；0.23），相应的增量寿命年分别为2.35（1.04；3.93）、1.67（0.68；2.96）和1.36（-0.05；3.64）。结论：BH-WMC-NMA对增量平均寿命年和成本-效果比产生影响，可能影响补偿决策。