Statistical Challenges in Comparing Chemotherapy and Bone Marrow Transplantation as a Treatment for Leukemia

John P. Klein and Mei-Jie Zhang
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John P. Klein: The Medical College of Wisconsin, International Bone Marrow Transplant Registry Division of Biostatistics
Mei-Jie Zhang: The Medical College of Wisconsin, International Bone Marrow Transplant Registry Division of Biostatistics

A chapter in Lifetime Data: Models in Reliability and Survival Analysis, 1996, pp 175-185 from Springer

Abstract: Abstract Comparison of survival for patients treated with either post remission chemotherapy or allogeneic bone marrow transplantation (BMT) for leukemias is considered. Two designs for the comparison are considered. The first is a genetic randomized clinical trial. For this type of trial, comparisons can be made either by an intent-to-treat analysis or by a time dependent covariate model. The second design compares data from a multicenter chemotherapy trial with data from a large transplant registry. Here analysis is complicated by the registry only observing patients who are transplanted so adjustments needs to be made for patients who die or relapse while waiting for transplant. Corrections suggested for this source of bias are a matching technique, inclusion of a time dependent covariate and a left truncated Cox model. We examine these techniques through a small Monte Carlo study and compare how much information is lost by using registry data as compared to a genetically randomized trial.

Keywords: Acute Myelogenous Leukemia; Allogeneic Bone Marrow Transplantation; Monte Carlo Study; Time Dependent Covariate; Matched Pair Analysis (search for similar items in EconPapers)
Date: 1996
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4757-5654-8_24

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DOI: 10.1007/978-1-4757-5654-8_24

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