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

ABSTRACT: Aim: Network meta-analyses (NMAs) increasingly feature time-varying hazards to account for non-proportional 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:</

SUBMITTER: Petersohn S 

PROVIDER: S-EPMC10508301 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature