Multi-state models for bone marrow transplantation studies

Abstract

High-dose chemotherapy followed by stem cell recovery, more commonly called a bone marrow transplant, is a common treatment for a number of diseases. This article examines four problems commonly encountered when dealing with bone marrow transplant studies. First, we look at the problem of competing causes of failure and at methods based on a multi-state model to estimate meaningful probabilities for these risks. Second, we examine methods for estimating the prevalence of an intermediate condition, here the prevalence of chronic GVHD. Third, we look at the problem of modeling the post transplant recovery process and we provide two examples of how these estimates can be used to assess dynamically a patient’s prognosis or how these probabilities can be used to design trials of new therapy. Finally, we present an estimate of a new measure of treatment efficiency, the current leukemia free survival function, which is derived from a multi-state model approach.