Abstract
BACKGROUND: Secondary failure of platelet recovery (SFPR) is a common complication that influences survival and quality of life of patients with β-thalassemia major (β-TM) after hematopoietic stem cell transplantation (HSCT). OBJECTIVES: A model to predict the risk of SFPR in β-TM patients after HSCT was developed. DESIGN: A retrospective study was used to develop the prediction model. METHODS: The clinical data for 218 β-TM patients who received HSCT comprised the training set, and those for another 89 patients represented the validation set. The least absolute shrinkage and selection operator regression algorithm was used to identify the critical clinical factors with nonzero coefficients for constructing the nomogram. Calibration curve, C-index, and receiver operating characteristic curve assessments and decision curve analysis (DCA) were used to evaluate the calibration, discrimination, accuracy, and clinical usefulness of the nomogram. Internal and external validation were used to test and verify the predictive model. RESULTS: The nomogram based on pretransplant serum ferritin, hepatomegaly, mycophenolate mofetil use, and posttransplant serum albumin could be conveniently used to predict the SFPR risk of thalassemia patients after HSCT. The calibration curve of the nomogram revealed good concordance between the training and validation sets. The nomogram showed good discrimination with a C-index of 0.780 (95% CI: 70.3-85.7) and 0.868 (95% CI: 78.5-95.1) and AUCs of 0.780 and 0.868 in the training and validation sets, respectively. A high C-index value of 0.766 was reached in the interval validation assessment. DCA confirmed that the nomogram was clinically useful when intervention was decided at the possibility threshold ranging from 3% to 83%. CONCLUSION: We constructed a nomogram model to predict the risk of SFPR in patients with β-TM after HSCT. The nomogram has a good predictive ability and may be used by clinicians to identify SFPR patients early and recommend effective preventive measures.