Designing complex group sequential survival trials.
This paper presents methodology for designing complex group sequential survival trials when the survival curves will be compared using the logrank statistic. The method can be applied to any treatment and control survival curves as long as each hazard function can be approximated by a piecewise linear function. The approach allows arbitrary accrual patterns and permits adjustment for varying rates of non-compliance, drop-in and loss to follow-up. The calendar-time-information-time transformation is derived under these complex assumptions. This permits the exploration of the operating characteristics of various interim analysis plans, including sample size and power. By using the calendar-time-information-time transformation, information fractions corresponding to desired calendar times can be determined. In this way, the interim analyses can be scheduled in information time, assuring the desired power and realization of the spending function, while the interim analyses will take place according to the desired calendar schedule.
Forest Laboratories Inc, 909 Third Avenue, New York City, NY 10022-4731, U.S.A. elakatos@msn.com
Edward
E
Lakatos
D002986:Clinical Trials as Topic / Q000379:methods*; D015331:Cohort Studies; D003198:Computer Simulation; D006333:Heart Failure; D006801:Humans; D008137:Longitudinal Studies; D008390:Markov Chains; D000451:Mineralocorticoid Receptor Antagonists / Q000627:therapeutic use; D010349:Patient Compliance; D018401:Sample Size; D013148:Spironolactone / Q000627:therapeutic use; D013223:Statistics as Topic / Q000379:methods*; D016019:Survival Analysis
D000451:Mineralocorticoid Receptor Antagonists; D013148:Spironolactone