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Article Abstract

Background: Acute graft-versus-host disease (aGvHD) is the primary cause of mortality following allogeneic hematopoietic cell transplantation (HCT).

Objectives: This study aimed to predict the risk of aGvHD after HCT in patients with thalassemia major using a novel predictive nomogram.

Design: A retrospective study was used to develop the prediction model.

Methods: We performed retrospective analyses on 402 consecutive thalassemia patients who underwent HCT. Risk factors for aGvHD were analyzed using Cox proportional regression models. T-lymphocyte subsets were collected from 240 patients at the time of neutrophil engraftment. Least Absolute Shrinkage and Selection Operator regression was utilized to screen the indices, with cut-off values established through restricted cubic spline (RCS) regression. The predictive model was developed by integrating these T-lymphocyte subsets with clinical features, aiming to enhance the accuracy of aGvHD risk prediction.

Results: Among 402 thalassemia patients analyzed post-transplantation, significant independent risk factors for aGvHD included matched unrelated donors, haploid-related donors, peripheral blood stem cell infusions, and donor age older than 40 years. Our RCS analysis indicated a marked increase in aGvHD risk when CD4+ T-cell counts exceeded 36 cells/μL and CD8+ T-cell counts exceeded 43 cells/μL during neutrophil engraftment. The integration of T-lymphocyte subsets with clinical risk factors into a Cox regression model demonstrated good predictive performance for assessing aGvHD risk.

Conclusion: This study presents a novel model designed to predict aGvHD in thalassemia patients post-transplantation by utilizing T-lymphocyte data at the time of engraftment. The model facilitates the creation of personalized treatment plans, aiming to minimize the incidence of aGvHD and improve patient outcomes.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11632902PMC
http://dx.doi.org/10.1177/20406207241294054DOI Listing

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