Clinical utility of metrics based on tumor measurements in phase II trials to predict overall survival outcomes in phase III trials by using resampling methods

Ming Wen An, Yu Han, Jeffrey P. Meyers, Jan Bogaerts, Daniel J. Sargent, Sumithra J Mandrekar

Research output: Contribution to journalArticle

4 Scopus citations

Abstract

Purpose Phase II clinical trials inform go/no-go decisions for proceeding to phase III trials, and appropriate end points in phase II trials are critical for facilitating this decision. Phase II solid tumor trials have traditionally used end points such as tumor response defined by Response Evaluation Criteria for Solid Tumors (RECIST). We previously reported that absolute and relative changes in tumor measurements demonstrated potential, but not convincing, improvement over RECIST to predict overall survival (OS). We have evaluated the metrics by using additional measures of clinical utility and data from phase III trials. Methods Resampling methods were used to assess the clinical utility of metrics to predict phase III outcomes from simulated phase II trials. In all, 2,000 phase II trials were simulated from four actual phase III trials (two positive for OS and two negative for OS). Cox models for three metrics landmarked at 12 weeks and adjusted for baseline tumor burden were fit for each phase II trial: absolute changes, relative changes, and RECIST. Clinical utility was assessed by positive predictive value and negative predictive value, that is, the probability of a positive or negative phase II trial predicting an effective or ineffective phase III conclusion, by prediction error, and by concordance index (c-index). Results Absolute and relative change metrics had higher positive predictive value and negative predictive value than RECIST in five of six treatment comparisons and lower prediction error curves in all six. However, differences were negligible. No statistically significant difference in c-index across metrics was found. Conclusion The absolute and relative change metrics are not meaningfully better than RECIST in predicting OS.

Original languageEnglish (US)
Pages (from-to)4048-4057
Number of pages10
JournalJournal of Clinical Oncology
Volume33
Issue number34
DOIs
StatePublished - Dec 1 2015

ASJC Scopus subject areas

  • Cancer Research
  • Oncology

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