Extrapolation of survival outcomes is key to health technology assessments in oncology to quantify lifetime benefit of a novel intervention. Conventional methods to extrapolate limited overall survival (OS) data beyond clinical trial follow-up may lead to high uncertainty in long-term estimations. External data can further inform the extrapolation of OS data and increase confidence in estimates of long-term survival outcomes.

The analysis focused on cilta-cel, a CAR-T therapy for triple-class relapsed/refractory multiple myeloma. Data from the initial cutoff of the pivotal phase Ib/II CARTITUDE-1 trial demonstrated strong efficacy results (97% overall response and 89% 12-month OS rate) in this patient population with limited therapy options. OS data from CARTITUDE-1 were extrapolated using various models, including those using conventional parametric methods (without incorporating external data), as well as Bayesian models that were additionally informed by a related external data source (i.e., the phase I LEGEND-2 trial).

Variability among parametric models was greatly reduced when the external LEGEND-2 data informed the extrapolations from the pivotal CARTITUDE-1 trial. These projections were further validated with observed 28-month OS data from CARTITUDE-1.