Which statement best describes why Kaplan-Meier curves do not inherently adjust for covariates?

• A. They are unadjusted; covariate adjustment requires regression models
• B. They are adjusted via stratified analyses automatically
• C. They handle covariates via stratification automatically
• D. They adjust covariates through imputation

Answer: (A)

Kaplan-Meier curves describe survival over time using only the observed event times and censoring, without incorporating how other patient characteristics influence risk. They are nonparametric and do not model covariate effects, so they provide the raw, unadjusted survival experience. To account for covariates, you need a regression-based approach that includes those covariates in the model—most commonly the Cox proportional hazards model—which yields adjusted survival estimates and hazard ratios. Stratified or separate KM curves by a covariate can compare groups but don’t produce a single adjusted curve across covariates, and imputation addresses missing data rather than adjusting for covariates in survival estimation.