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.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 442-453 |
| Number of pages | 12 |
| Journal | Biometrical Journal |
| Volume | 61 |
| Issue number | 2 |
| DOIs | |
| State | Published - Mar 2019 |
Bibliographical note
Funding Information:This work was funded by a grant from the Canadian Institutes of Health Research. We are grateful to the two anonymous referees and the associate editor whose thoughtful feedback helped to improve the clarity of our work.
Publisher Copyright:
© 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Q-learning
- adaptive treatment strategy
- cure-rate
- dynamic treatment regime
- survival data
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