Pharmacometric modeling and machine learning analyses of prognostic and predictive factors in the JAVELIN Gastric 100 phase III trial of avelumab.

ABSTRACT: Avelumab (anti-PD-L1) is an approved anticancer treatment for several indications. The JAVELIN Gastric 100 phase III trial did not meet its primary objective of demonstrating superior overall survival (OS) with avelumab maintenance versus continued chemotherapy in patients with advanced gastric cancer/gastroesophageal junction cancer; however, the OS rate was numerically higher with avelumab at timepoints after 12 months. Machine learning (random forests, SIDEScreen, and variable-importance assessments) was used to build models to identify prognostic/predictive factors associated with long-term OS and tumor growth dynamics (TGDs). Baseline, re-baseline, and longitudinal variables were evaluated as covariates in a parametric time-to-event model for OS and Gompertzian population model for TG

SUBMITTER: Terranova N 

PROVIDER: S-EPMC8923733 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature