Nomogram based on serum interleukin-33 levels and clinical characteristics for predicting overall survival in hematologic malignancy patients receiving haplo-HDPSCT

Haploidentical hematopoietic stem cell transplantation (haplo-HSCT) is a crucial modality for managing hematologic malignancies, such as refractory relapsed leukemia and lymphoma. Disease conditions before and after transplantation substantially influence HSCT outcomes. This work focused on establishing a nomogram for predicting outcomes in patients who underwent haploidentical high-dose peripheral blood stem cell transplantation (haplo-HDPSCT). A total of 165 patients who developed hematologic malignancies and who received haplo-HDPSCT at the First Affiliated Hospital of Xinjiang Medical University between January 2017 and August 2023 were recruited. A landmark analysis was performed at 1 month post-transplantation. The independent predictors associated with overall survival (OS) were analyzed through Cox regression, and these prognostic factors were subsequently used for nomogram construction. A bootstrap resampling approach was utilized for internal validation. Multivariate Cox regression analysis identified high interleukin-33 (IL-33) levels and pre-transplant measurable residual disease (MRD) positivity as independent predictors of OS. A prognostic nomogram was established on the basis of these risk factors. The nomogram demonstrated superior goodness-of-fit compared with the MRD-only model, as evidenced by lower Akaike information criterion (AIC) and Bayesian information criterion (BIC) values (324.796 vs. 331.014; 327.907 vs. 332.570, respectively). The bootstrap-corrected concordance index (C-index) of the nomogram was (0.682, 95% CI: 0.592–0.772), which outperformed that of pre-transplant MRD positivity alone (0.598, 95% CI: 0.522–0.674) and high IL-33 alone (0.624; 95% CI: 0.540–0.708). This superior discrimination was further confirmed by time-dependent C-index analysis. With respect to calibration, the nomogram-predicted survival probabilities were in good agreement with the observed survival rates. Furthermore, decision curve analysis (DCA) indicated that the nomogram had superior net clinical benefit. Stratified by the nomogram-derived cutoff value, patients in the high-risk group experienced significantly poorer OS than those in the low-risk group (P < 0.001). IL-33 can independently predict prognosis in haplo-HDPSCT patients. High IL-33 levels are related to unfavorable prognostic outcomes in haplo-HSCT patients. The present work offers a precise nomogram for OS prediction in haplo-HDPSCT patients, with possible clinical usefulness.