JSM 2012 Home

JSM 2012 Online Program

The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.

Online Program Home

Abstract Details

Activity Number: 471
Type: Contributed
Date/Time: Wednesday, August 1, 2012 : 8:30 AM to 10:20 AM
Sponsor: Biopharmaceutical Section
Abstract - #306670
Title: A Hybrid Bootstrap Approach to Interim Analyses of Time-to-Event Data Using Kaplan-Meier Methods
Author(s): Kevin Lawson*+ and Aaron C Camp and Austin L Hand
Companies: PPD and PPD and PPD
Address: 12000 Cascade Caverns Trl., Austin, TX, 78739-4805, United States
Keywords: Bootstrap ; Bayesian ; Oncology ; interim ; survival ; censoring

Efficacy analyses in oncology clinical trials commonly include time-to-event endpoints analyzed using Kaplan-Meier methods. Decisions are frequently required prior to completion of the study. Bootstrapping is a well-known method for drawing inferences from partial data, but is problematic when the maximum event time is small or when right-censoring is large. An alternative method is to use a parametric bootstrap procedure by sampling from a hypothesized or fitted parametric distribution. Here, we present a hybrid bootstrap procedure that uses three strategies to combine the empirical distribution with a conditional parametric distribution fit with observed data. The bootstrap will sample from this mixture distribution under 3 schema for selecting the weights. We implement this method at several timepoints using data from 3 oncology trials. The results of the hybrid bootstrap, including the 95% bootstrap confidence intervals on the median time-to-event and the probability that the median time-to-event will exceed a predetermined value, are compared to the Bayesian posterior distribution of the survival function and to the actual median time-to-event.

The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.

Back to the full JSM 2012 program

2012 JSM Online Program Home

For information, contact jsm@amstat.org or phone (888) 231-3473.

If you have questions about the Continuing Education program, please contact the Education Department.