Using T-lymphocyte subsets at engraftment to predict the risk of acute graft-versus-host disease in patients with thalassemia major: development of a new predictive nomogram.

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.