ArticleAnnals of hematology2025
Adult patients with Philadelphia chromosome positive acute lymphoblastic leukemia undergoing allogeneic hematopoietic stem cell transplantation and tyrosine kinase inhibitors: development and validation of a clinical prediction model based on cytogenetics, IKZF1 deletions and minimal residual disease.
Article in Annals of hematology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
The aim of this study was to develop and validate a nomogram predicting progression-free survival (PFS) for adult patients with positive acute lymphoblastic leukemia(Ph + ALL) who have undergone allogeneic hematopoietic stem cell transplantation(allo-HSCT) and tyrosine kinase inhibitor(TKI) treatment. Data were retrospectively collected from 176 adult patients diagnosed with Ph + ALL and treated with allo-HSCT and TKIs at The First Affiliated Hospital, Zhejiang University School of Medicine, between January 2015 and May 2023. 70% of the patients were randomly assigned to the training group(n = 124) and 30% of the patients were assigned to the validation group(n = 52). Univariate Cox regression analysis and Akaike Information Criterion(AIC) were utilized to identify significant predictive factors, leading to the development of a nomogram designed to forecast the probability of PFS at 6, 9, and 12 months post-transplantation. The final nomogram incorporated three key variables: presence of complex additional cytogenetic abnormalities (ACAs), minimal residual disease (MRD) status prior to allo-HSCT, and IKZF1 gene deletions. The calibration curves showed excellent consistency between the nomogram prediction and actual observation for 6-, 9- and 12-month PFS in the training set and validation set. The C-index of the training set was 0.726(95%CI: 0.635-0.816), which was no significantly different from the validation set(C-index = 0.774, 95%CI: 0.674-0.875, P > 0.05). This study may provide a simple and efficient prediction model for patients with Ph + ALL undergoing allo-HSCT and TKIs, which can accurately predict PFS subsequent to transplantation. This tool could potentially aid clinicians in decision-making processes and improve patient outcomes.
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