Interim monitoring of clinical trials based on long-term binary endpoints.
This paper discusses interim analysis of randomized clinical trials for which the primary endpoint is observed at a specific long-term follow-up time. For such trials subjects only yield direct information on the primary endpoint once they have been followed through to the long-term follow-up time, potentially eliminating a large proportion of the accrued sample from an interim analysis of the primary endpoint. We advocate more efficient interim analysis of long-term endpoints by augmenting long-term information with short-term information on subjects who have not yet been followed through to the long-term follow-up time. While retaining the long-term endpoint as the subject of the analysis, methods of jointly analysing short- and long-term data are discussed for reversible binary endpoints. It is shown theoretically and by simulation that the use of short-term information improves the efficiency with which long-term treatment differences are assessed based on interim data. Sequential analysis of treatment differences is discussed based on spending functions, and is illustrated with a numerical example from a cholesterol treatment trial.
Marschner
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IC
NHMRC Clinical Trials Centre, University of Sydney, Locked Bag 77, Camperdown, NSW 2050, Australia. ian@ctc.usyd.edu.au
Becker
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SL
D000787:Angina Pectoris / Q000188:drug therapy; D000924:Anticholesteremic Agents / Q000494:pharmacology; D008076:Cholesterol, HDL / Q000097:blood; D003198:Computer Simulation; D023381:Endpoint Determination; D006801:Humans; D009716:Numerical Analysis, Computer-Assisted; D017035:Pravastatin / Q000494:pharmacology; D011446:Prospective Studies; D016032:Randomized Controlled Trials as Topic / Q000379:methods*; D012008:Recurrence; D012107:Research Design
D000924:Anticholesteremic Agents; D008076:Cholesterol, HDL; D017035:Pravastatin