Development of a prognostic model
REGRESSION
In total, 185 patients were randomized into two groups (training and validation cohorts) based on a ratio of 7 to 3. the following medical characteristics were evaluated to identify the predictive factors of survival in the training cohort: age at HSCT, sex, DRI, HCT-CI, CAR, donor–recipient relationship, donor–recipient sex match, donor–recipient blood type match, number of HLA mismatches and conditioning regimens. The construction of nomograms is based on multivariate regression models (such as Cox and logistic regression models), which can may simplify and visualize complex regression equations, and making the results of prediction model more readable and valuable for use.Variables significant at P < 0.10 in univariate analysis as underlying survival risk elements were selected for multivariate Cox proportional risk regression to Identify independent prognostic factors. According to the above results, Statistically significant parameters (P<0.05) were incorporated into a nomogram to predict OS in patients after haplo-HSCT.