Abstract
All indirect treatment comparisons (ITC) rely on individual patient-level data (IPD) to compare the efficacy of healthcare interventions. However, IPD are often only available for the index study while Kaplan-Meier (KM) and aggregate data are used for the comparator trials. Techniques exist to generate pseudo-IPD from KM outcome data, but this only allows estimation of the outcome and not the covariates. This research aimed to develop a method to generate pseudo-IPD by predicting the covariates on an individual patient level for use in ITCs.
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