Risk factor analysis and predictive model development for secondary failure of platelet recovery following allogeneic hematopoietic stem cell transplantation.

Secondary failure of platelet recovery (SFPR) is a common complication following allogeneic hematopoietic stem cell transplantation (allo-HSCT), occurring in approximately 20% of cases, and is closely associated with poor patient prognosis. The purpose of this study is to analyze the risk factors associated with SFPR following allo-HSCT, develop a nomogram-based predictive model for SFPR, and validate its accuracy. Clinical data of patients who underwent allo-HSCT in the Department of Hematology at the First Hospital of Lanzhou University from January 2016 to December 2023 were collected. Variables with P < 0.05 in univariate analysis were included in a logistic multivariate stepwise regression to identify the final variables for the model. An SFPR nomogram prediction model was developed using R software and internally validated using the Bootstrap method. The accuracy of the prediction model was assessed through receiver operating characteristic(ROC) and calibration curves, while decision curve analysis evaluated its clinical predictive performance. Based on the body mass index(BMI), chromosome karyotype, transplant type, acute graft-versus-host disease(aGVHD) and post-transplant Interleukin-6(IL-6) and Procalcitonin(PCT), the predicted area under the ROC curve of SFPR is 0.778 (95% CI 0.697-0.858). The absolute error between the predicted risk of SFPR and the actual risk is 0.019. The SFPR nomogram prediction model developed in this study exhibits high accuracy and excellent predictive efficiency, thereby possessing significant clinical guidance value.