A cure-rate model for Q-learning: Estimating an adaptive immunosuppressant treatment strategy for allogeneic hematopoietic cell transplant patients

Biometrical Journal. Biometrische Zeitschrift
Erica E M MoodieElizabeth F Krakow

Abstract

Cancers treated by transplantation are often curative, but immunosuppressive drugs are required to prevent and (if needed) to treat graft-versus-host disease. Estimation of an optimal adaptive treatment strategy when treatment at either one of two stages of treatment may lead to a cure has not yet been considered. Using a sample of 9563 patients treated for blood and bone cancers by allogeneic hematopoietic cell transplantation drawn from the Center for Blood and Marrow Transplant Research database, we provide a case study of a novel approach to Q-learning for survival data in the presence of a potentially curative treatment, and demonstrate the results differ substantially from an implementation of Q-learning that fails to account for the cure-rate.

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Citations

Sep 29, 2019·Statistical Methods in Medical Research·Diego I GallardoMário de Castro
Apr 15, 2020·Bone Marrow Transplantation·Erica E M Moodie, Elizabeth F Krakow
Feb 24, 2021·BMC Medical Research Methodology·Robert K MaharJulie A Simpson

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