Predicting median survival times from early data in immunotherapy trials using exponential-decay modeling

In oncology trials, overall survival (OS) and progression-free survival (PFS) are typically summarized with Kaplan-Meier (KM) curves, but medians cannot be estimated when follow-up is early. We evaluated whether exponential-decay regression applied to the earliest quartile of KM data could approximate mature medians. A total of 114 phase III immunotherapy trials encompassing 420 treatment arms were analyzed, yielding 618 evaluable survival curves across OS and PFS endpoints. For immunotherapy OS, predicted and reported medians showed no significant difference (P=.59; R2 = 0.76; concordance correlation coefficient = 0.87). For immunotherapy PFS, predictions modestly overestimated medians (P < .001; R2 = 0.50). Non-immunotherapy arms demonstrated overestimation for both OS (R2 = 0.61) and PFS (R2 = 0.68). Pooled OS performance was good (R2 = 0.70). Early exponential modeling may offer a transparent tool for interim OS estimation in immunotherapy trials, warranting prospective validation.