Kaplan-Meier Survival Analysis

Kaplan-Meier survival analysis graphically depicts time-to-event outcomes accounting for censored data. Survival curves compare treatment group outcomes. Log-rank tests assess statistical significance. Median survival determination guides clinical interpretation. Subgroup survival analysis identifies differential outcomes.

Regulatory submissions employ Kaplan-Meier analysis demonstrating efficacy. Confidence intervals quantitate estimate uncertainty. Proportional hazards violations warrant alternative analysis. Post-approval monitoring tracks long-term survival. Emerging stratified analysis accounts for prognostic factors.