Applications of Causal Inference Methods for the Estimation of Effects of Bone Marrow Transplant and Prescription Drugs on Survival of Aplastic Anemia Patients

Author

Yesha M. Patel, Chapman UniversityFollow

Date of Award

Fall 12-2023

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Computational and Data Sciences

First Advisor

Cyril Rakovski

Second Advisor

Peter Jipsen

Third Advisor

Sidi Danoko

Fourth Advisor

Arash Mahajerin

Abstract

This dissertation provides an in-depth exploration into the treatment effectiveness for aplastic anemia using causal inference methods, structured around three pivotal research papers. Each paper contributes to a nuanced understanding of treatment impacts, specifically focusing on bone marrow transplantation (BMT) and prescription drugs, and the identification of optimal treatment strategies.

The first paper, "Causal Inference Analysis for Assessing the Effect of Bone Marrow Transplantation on the One-Year Survival of Adult and Pediatric Aplastic Anemia Patients," sets the foundation. It examines the short-term effectiveness of BMT in both adult and pediatric patients, providing crucial insights into how this treatment affects survival rates within the first-year post-diagnosis. This analysis is instrumental in understanding the implications of BMT across different age groups.

In the second paper, "Assessing the Effect of Bone Marrow Transplantation on the Survival of Adult Aplastic Anemia Patients for the First Five-Years After Initial Diagnosis: A Causal Inference Study," the focus shifts to a longer-term perspective. This study extends the survival analysis to five years, offering a comprehensive view of the sustained effects of BMT. This longitudinal approach helps in understanding the durability of the treatment's impact.

The third paper, "Identification of Optimal Treatment on the One-Year Survival of Aplastic Anemia Patients: A Causal Inference Study," broadens the scope by comparing various treatment options. It seeks to identify the most effective treatment strategy for improving one-year survival rates in aplastic anemia patients, contributing to the decision-making process in clinical settings.

These three papers collectively offer an in-depth, varied analysis of treatment effects in aplastic anemia, employing causal inference techniques to navigate complex data. Utilizing robust, clinically significant methods such as doubly robust estimators, our research reveals a marked improvement in survival rates for BMT recipients, particularly adults, over one year. The studies also recognize the typically more severe stages of illness in BMT patients, underscoring the need for assessing disease severity. Despite constraints like small sample sizes limiting variable adjustments, this research substantially progresses our comprehension of aplastic anemia treatments. This methodological approach guarantees solid, clinically pertinent insights, enhancing our grasp of treatment efficacy in this field.

Creative Commons License

This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Recommended Citation

Y. Patel, "Applications of causal inference methods for the estimation of effects of bone marrow transplant and prescription drugs on survival of aplastic anemia patients," M. S. thesis, Chapman University, Orange, CA, 2023. https://doi.org/10.36837/chapman.000514