Ming-Wen An1, Yu Han2, Jeffrey P Meyers2, Jan Bogaerts2, Daniel J Sargent2, Sumithra J Mandrekar2. 1. Ming-Wen An, Vassar College, Poughkeepsie, NY; Yu Han, Novartis Pharmaceuticals, East Hanover NJ; Jeffrey Meyers, Daniel J. Sargent, and Sumithra J. Mandrekar, Mayo Clinic, Rochester, MN; and Jan Bogaerts, European Organisation for Research and Treatment of Cancer, Brussels, Belgium. mian@vassar.edu. 2. Ming-Wen An, Vassar College, Poughkeepsie, NY; Yu Han, Novartis Pharmaceuticals, East Hanover NJ; Jeffrey Meyers, Daniel J. Sargent, and Sumithra J. Mandrekar, Mayo Clinic, Rochester, MN; and Jan Bogaerts, European Organisation for Research and Treatment of Cancer, Brussels, Belgium.
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.
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.
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