KMSubtraction: Reconstruction of unreported subgroup survival data utilizing published Kaplan-Meier survival curves

BACKGROUND: Data from certain subgroups of clinical interest may not be presented in primary manuscripts or conference abstract presentations. In an effort to enable secondary data analyses, we propose a workflow to retrieve unreported subgroup survival data from published Kaplan-Meier (KM) curves. METHODS: We developed KMSubtraction, an R package that retrieves patients from unreported subgroups by matching participants on KM curves of the overall cohort to participants on KM curves of a known subgroup with follow up time. Unmatched patients were assumed to be from the opposing unreported subgroup. Reproducibility and limits of error of the KMSubtraction workflow were assessed by comparing unmatched patients against the original survival data of subgroups from published datasets and simulations. Monte Carlo simulations were utilized to evaluate the effect of the reported subgroup proportion, missing data, censorship proportion in the overall and subgroup cohort, sample size and number at risk table intervals on the limits of error of KMSubtraction. 3 matching algorithms were explored: minimal cost bipartite matching, Mahalanobis distance matching, and nearest neighbor matching by logistic regression. RESULTS: The validation exercise found no material systematic error and demonstrates the robustness of KMSubtraction in deriving unreported subgroup survival data. Limits of error were small and negligible on marginal Cox proportional hazard models comparing reconstructed and original survival data of unreported subgroups. Extensive Monte Carlo simulations demonstrate that datasets with high reported subgroup proportion (r=0.467, p<0.001), small dataset size (r=-0.374, p<0.001) and high proportion of missing data in the unreported subgroup (r=0.553, p<0.001) were associated with uncertainty are likely to yield high limits of error with KMSubtraction. CONCLUSION: While KMSubtraction demonstrates robustness in deriving survival data from unreported subgroups, the implementation of KMSubtraction should take into consideration the aforementioned limitations. The limits of error of KMSubtraction, as reflected by the mean |ln(HR)| from converged Monte Carlo simulations may guide the interpretation of reconstructed survival data of unreported subgroups.