The value of surrogate endpoints for predicting real-world survival across five cancer types

Curr Med Res Opin. 2016;32(4):731-9. doi: 10.1185/03007995.2016.1140027. Epub 2016 Jan 25.

Abstract

Objective: It is unclear how well different outcome measures in randomized controlled trials (RCTs) perform in predicting real-world cancer survival. We assess the ability of RCT overall survival (OS) and surrogate endpoints - progression-free survival (PFS) and time to progression (TTP) - to predict real-world OS across five cancers.

Methods: We identified 20 treatments and 31 indications for breast, colorectal, lung, ovarian, and pancreatic cancer that had a phase III RCT reporting median OS and median PFS or TTP. Median real-world OS was determined using a Kaplan-Meier estimator applied to patients in the Surveillance and Epidemiology End Results (SEER)-Medicare database (1991-2010). Performance of RCT OS and PFS/TTP in predicting real-world OS was measured using t-tests, median absolute prediction error, and R(2) from linear regressions.

Results: Among 72,600 SEER-Medicare patients similar to RCT participants, median survival was 5.9 months for trial surrogates, 14.1 months for trial OS, and 13.4 months for real-world OS. For this sample, regression models using clinical trial OS and trial surrogates as independent variables predicted real-world OS significantly better than models using surrogates alone (P = 0.026). Among all real-world patients using sample treatments (N = 309,182), however, adding trial OS did not improve predictive power over predictions based on surrogates alone (P = 0.194). Results were qualitatively similar using median absolute prediction error and R(2) metrics.

Conclusions: Among the five tumor types investigated, trial OS and surrogates were each independently valuable in predicting real-world OS outcomes for patients similar to trial participants. In broader real-world populations, however, trial OS added little incremental value over surrogates alone.

Keywords: Comparative effectiveness research; neoplasms; observational study; progression-free survival; surrogate endpoints; survival.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Biomarkers*
  • Clinical Trials, Phase III as Topic
  • Databases, Factual
  • Disease Progression
  • Disease-Free Survival
  • Female
  • Humans
  • Kaplan-Meier Estimate
  • Linear Models
  • Male
  • Medicare
  • Middle Aged
  • Neoplasms / epidemiology*
  • Neoplasms / mortality*
  • Odds Ratio
  • Prognosis
  • Randomized Controlled Trials as Topic
  • SEER Program
  • Survival Analysis
  • Treatment Outcome
  • United States

Substances

  • Biomarkers