Sex-based prognosis in industry-sponsored advanced solid tumor trials: an individual participant data meta-analysis...

Sex is a recognized modifier of physiology, immunity, and social exposures, yet its independent association with survival and adverse event prognosis in contemporary anticancer therapy remains poorly defined. The aim of the present study was to assess the association between patient sex and overall survival, progression-free survival, and grade 3 or greater adverse events across a pooled individual participant data meta-analysis.

Individual participant data supporting US Food and Drug Administration approval of anticancer medicines for solid tumors between 2011 and 2021 were accessed through the Vivli and Yale University Open Data Access data sharing platforms. A 2-stage random-effects meta-analysis approach was employed using Cox proportional hazards regression to estimate sex-based prognostic differences in overall survival, progression-free survival, and grade 3 or greater adverse events. Analyses were adjusted for key baseline covariates.

In a pooled cohort of 20 806 participants from 39 phase 2 and 3 trials supporting Food and Drug Administration approvals of anticancer medicines for advanced solid tumors, across 12 tumor types, female sex was associated with statistically significantly improved overall survival (hazard ratio = 0.79, 95% CI = 0.73 to 0.85; P < .001) and progression-free survival (hazard ratio = 0.84, 95% CI = 0.79 to 0.89; P < .001). Conversely, female patients experienced a higher risk of grade 3 or greater adverse events (hazard ratio = 1.12, 95% CI = 1.07 to 1.18; P < .001).

In the largest analysis of individual participant data from trials supporting Food and Drug Administration drug approvals, we found that female patients had a 21% lower risk of death and a 16% lower risk of progression but a 12% higher risk of severe adverse events. These findings highlight the value of individual participant data sharing and the importance of sex-stratified evidence for risk stratification, dose optimization, and patient counseling.