Strength of Validation for Surrogate End Points Used in the US Food and Drug Administration's Approval of Oncology Drugs

Chul Kim, Vinay Prasad

Research output: Contribution to journalArticle

54 Scopus citations

Abstract

Objective To determine the strength of the surrogate-survival correlation for cancer drug approvals based on a surrogate. Participants and Methods We performed a retrospective study of the US Food and Drug Administration (FDA) database, with focused searches of MEDLINE and Google Scholar. Among cancer drugs approved based on a surrogate end point, we examined previous publications assessing the strength of the surrogate-survival correlation. Specifically, we identified the percentage of surrogate approvals lacking any formal analysis of the strength of the surrogate-survival correlation, and when conducted, the strength of such correlations. Results Between January 1, 2009, and December 31, 2014, the FDA approved marketing applications for 55 indications based on a surrogate, of which 25 were accelerated approvals and 30 were traditional approvals. We could not find any formal analyses of the strength of the surrogate-survival correlation in 14 out of 25 accelerated approvals (56%) and 11 out of 30 traditional approvals (37%). For accelerated approvals, just 4 approvals (16%) were made where a level 1 analysis (the most robust way to validate a surrogate) had been performed, with all 4 studies reporting low correlation (r≤0.7). For traditional approvals, a level 1 analysis had been performed for 15 approvals (50%): 8 (53%) reported low correlation (r≤0.7), 4 (27%) medium correlation (r>0.7 to r<0.85), and 3 (20%) high correlation (r≥0.85) with survival. Conclusions The use of surrogate end points for drug approval often lacks formal empirical verification of the strength of the surrogate-survival association.

Original languageEnglish (US)
Pages (from-to)713-725
Number of pages13
JournalMayo Clinic Proceedings
Volume91
Issue number6
DOIs
StatePublished - Jun 1 2016

ASJC Scopus subject areas

  • Medicine(all)

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