Our summary
For oncology treatments, the duration of follow-up in clinical trials is often much shorter than the expected survival of patients, posing an issue for understanding treatment benefits long-term. To address this gap, survival extrapolation methods are used to estimate the average life-years gained for both economic analyses and health technology assessments (HTAs). Yet, standard extrapolation methods using clinical trial data only estimate outcomes beyond the trial observation period and may not accurately represent longer-term survival outcomes achieved by patients in the real world.
This study illustrates different approaches to integrating electronic health record-derived real-world data (RWD) with clinical trial data to reduce uncertainty and enhance survival extrapolations. To do this, researchers generated an RWD cohort similar to the trial patients by applying selection criteria, enrollment windows, and weighting on baseline characteristics. The findings demonstrate the strengths and limitations of these enhanced survival extrapolation methods for supplementing trial data with RWD data at various time points.
Why this matters
As the demand for long-term survival data by HTA bodies increases, high-quality RWE is becoming a critical source of evidence in the decision-making process. This publication presents a case study in point. Clinical trials are a gold standard to establish the safety and efficacy profile of a clinical intervention, but clinical trial evidence has notable limitations regarding the real-world effectiveness and estimated cost-effectiveness, in terms of representativeness and ability to support long-term survival extrapolations. In order for RWE to rigorously complement and enhance these areas, researchers must identify data sources with clinical depth and breadth that include covariates similar to the clinical trial and validated survival outcomes, This publication takes an initial crucial step, appraising specific analytic methods to extrapolate clinical outcome results using RWD.