Logo-aim
Arch Iran Med. 2026;29(4): 237-248.
doi: 10.34172/aim.35225
  Abstract View: 279196
  PDF Download: 253236
  Full Text View: 86128

Original Article

Bayesian Joint Modeling of Longitudinal Pattern of WT1 Gene Expression and Survival Time in AML Patients

Sahar Dalvand 1 ORCID logo, Amir Kasaeian 2,3,4 ORCID logo, Mohammad Vaezi 5, Shahrbano Rostami 6, Hojjat Zeraati 1* ORCID logo, Mehdi Yaseri 1* ORCID logo

1 Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
2 Research Center for Chronic Inflammatory Diseases, Tehran University of Medical Sciences, Tehran, Iran
3 Liver and Pancreatobiliary Diseases Research Center, Digestive Diseases Research Institute, Tehran University of Medical Sciences, Tehran, Iran
4 Digestive Oncology Research Center, Digestive Diseases Research Institute, Tehran University of Medical Sciences, Tehran, Iran
5 Hematology, Oncology, and Stem Cell, Transplantation Research Center, Research Institute for Oncology, Hematology, and Cell Therapy, Tehran University of Medical Sciences, Tehran, Iran
6 Cell Therapy and Hematopoietic Stem Cell Transplantation Research Center, Research Institute for Oncology, Hematology and Cell Therapy, Tehran University of Medical Sciences, Tehran, Iran
*Corresponding Authors: Hojjat Zeraati, Email: zeraatih@tums.ac.ir; Mehdi Yaseri, Email: m.yaseri@gmail.com

Abstract

Introduction: Acute Myeloid Leukemia (AML) is a malignant hematologic neoplasm with an unfavorable prognosis. The Wilms’ tumor gene (WT1) is a key prognostic biomarker in AML, showing longitudinal patterns that may predict survival outcomes after transplantation. This study aimed to jointly model the longitudinal changes in the WT1 gene expression and the survival time of AML patients using a Bayesian approach.

Methods: This retrospective cohort study used data from 319 AML patients who underwent allo-HSCT and were followed up between 2008 and 2019 at the Hematology Clinic of Shariati Hospital in Tehran. For data analysis using Bayesian joint longitudinal and survival modeling, a random effects model was used for the longitudinal submodel, and a generalized hazard regression model with a Burr XII (BXII) baseline hazard function was used for the survival submodel.

Results: Results demonstrated that a higher baseline WT1 level was significantly associated with reduced survival, increasing the hazard of death by 47.4% (HR=1.474, 95% CI: 1.325-2.052). The longitudinal submodel revealed that WT1 expression significantly increased by 0.169 times in patients with acute Graft-versus-Host Disease (aGVHD) and by 1.103 times in those who relapsed. The survival submodel confirmed that increased age (HR=1.309), disease relapse (HR=1.955), and donor type other relative and unrelated compared to sibling (HR=1.975 and HR=1.479, respectively) were predictors of worse survival.

Conclusion: In conclusion, elevated WT1 expression at transplantation is a critical negative prognostic indicator in AML. Monitoring this biomarker helps identify high risk patients and can guide pre-transplant therapeutic strategies to improve survival outcomes.



Cite this article as: Dalvand S, Kasaeian A, Vaezi M, Rostami S, Zeraati H, Yaseri M. Bayesian joint modeling of longitudinal pattern of WT1 gene expression and survival time in AML patients. Arch Iran Med 2026;29(4): 237-248. doi:10.34172/aim.35225
First Name
Last Name
Email Address
Comments
Security code


Abstract View:

Your browser does not support the canvas element.

PDF Download:

Your browser does not support the canvas element.


Full Text View:

Your browser does not support the canvas element.