Supplementary material: Challenges in conducting fractional polynomial and standard parametric network meta-analyses of immune checkpoint inhibitors for first-line advanced renal cell carcinoma

These are peer-reviewed supplementary materials for the article 'Challenges in conducting fractional polynomial and standard parametric network meta-analyses of immune checkpoint inhibitors for first-line advanced renal cell carcinoma' published in the Journal of Comparative Effectiveness Research.1. Feasibility assessment1.1 Heterogeneity assessment1.1.1 Items assessed for heterogeneity between trials1.1.2 Overview of relevant baseline characteristics across trials1.2 Assessment of the proportional hazards (PH) assumption1.2.1 Criteria applied1.2.2 Results1.3 Network of evidence2. Non-proportional hazards NMA outcomes2.1 Model fitting2.2 Model selection algorithm: face validity check of first- and second-order models2.2.1 Time-varying HR plots versus trial hazards second order polynomial for OS2.3 Model selection algorithm: Predictive accuracy against trial data2.3.1 PFS 2.3.2 OSAim: Network meta-analyses (NMAs) increasingly feature time-varying hazards to account for nonproportional hazards between different drug classes. This paper outlines an algorithm for selecting clinically plausible fractional polynomial NMA models. Methods: The NMA of four immune checkpoint inhibitors (ICIs) + tyrosine kinase inhibitors (TKIs) and one TKI therapy for renal cell carcinoma (RCC) served as case study. Overall survival (OS) and progression free survival (PFS) data were reconstructed from the literature, 46 models were fitted. The algorithm entailed a-priori face validity criteria for survival and hazards, based on clinical expert input, and predictive accuracy against trial data. Selected models were compared with statistically best-fitting models. Results: Three valid PFS and two OS models were identified. All models overestimated PFS, the OS model featured crossing ICI + TKI versus TKI curves as per expert opinion. Conventionally selected models showed implausible survival. Conclusion: The selection algorithm considering face validity, predictive accuracy, and expert opinion improved the clinical plausibility of first-line RCC survival models.

本数据集为发表于《比较疗效研究杂志》的论文《进行免疫检查点抑制剂一线晚期肾细胞癌的分数多项式和标准参数网络Meta分析的挑战》的同行评审补充材料。1. 可行性评估1.1 异质性评估1.1.1 评估试验间异质性的项目1.1.2 概述各试验中的相关基线特征1.2 比例风险假设的评估1.2.1 应用标准1.2.2 结果1.3 证据网络2. 非比例风险NMA结果2.1 模型拟合2.2 模型选择算法：一阶和二阶模型的面板有效性检查2.2.1 时间变化HR图与OS的二阶多项式风险2.3 模型选择算法：与试验数据的预测准确性2.3.1 PFS2.3.2 OSAim：网络Meta分析（NMAs）日益注重考虑不同药物类别之间的非比例风险，通过引入时间变化风险。本文概述了一种选择临床可行的分数多项式NMA模型的算法。方法：以四种免疫检查点抑制剂（ICIs）+酪氨酸激酶抑制剂（TKIs）和一种TKI疗法治疗肾细胞癌（RCC）的NMA作为案例研究。从文献中重建了总生存期（OS）和无进展生存期（PFS）数据，拟合了46个模型。算法包括基于临床专家意见的生存和风险的前验面板有效性标准，以及与试验数据的预测准确性。选定的模型与统计上最佳拟合模型进行了比较。结果：确定了三个有效的PFS模型和两个OS模型。所有模型高估了PFS，OS模型根据专家意见显示了ICI + TKI与TKI曲线的交叉。常规选择的模型显示生存结果不合理。结论：考虑面板有效性、预测准确性和专家意见的选择算法提高了首线肾细胞癌生存模型的临床合理性。