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

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.

journal_name

Curr Med Res Opin

journal_title

Current medical research and opinion

authors

Shafrin J,Brookmeyer R,Peneva D,Park J,Zhang J,Figlin RA,Lakdawalla DN

doi

10.1185/03007995.2016.1140027

subject

Has Abstract

pub_date

2016-01-01 00:00:00

pages

731-9

issue

eissn

0300-7995

issn

1473-4877

journal_volume

pub_type

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