Development and validation of a predictive model for chronic or persistent immune thrombocytopenia in children incorporating anti-glycoprotein IIb antibody: a retrospective cohort study utilizing LASSO regression and bootstrap stability analysis

Background Pediatric immune thrombocytopenia (ITP) is an autoimmune condition involving platelet destruction. While most cases resolve spontaneously, 20%–30% progress to chronic disease (cITP), necessitating early risk prediction. Current prognostic models for childhood ITP lack platelet-specific immunological markers. This study aimed to develop and validate a predictive model for chronic/persistent ITP(c/pITP) integrating clinical factors and anti-platelet glycoprotein antibodies. Methods We retrospectively analyzed 381 children with newly diagnosed ITP (2022–2024). Patients were randomly allocated into training ( n = 266) and test ( n = 115) sets (7:3 ratio, seed = 42). Missing data were addressed via multiple imputation (m = 5). Predictors were selected through univariate analysis ( P < 0.1), LASSO regression with 10-fold cross-validation, and bootstrap stability assessment (λ.1se, B = 1,000, selection frequency ≥ 90%). Candidate models were compared using bootstrap optimism correction and the Equivalent Parsimony Principle. The final model was evaluated on the independent test set for discrimination (AUC), calibration (Hosmer–Lemeshow test), and clinical utility (decision curve analysis). Results Fourteen highly stable predictors were identified; the top three were platelet count (PLT, 100%), recent infection or vaccination history (IOV, 100%), and anti-GPIIb antibody status (99.9%). The final 4-variable model (age, IOV, PLT, anti-GPIIb) demonstrated good discrimination in the test set (AUC = 0.743; 95% CI: 0.650–0.836), with no evidence of overfitting (training AUC = 0.732). Calibration was satisfactory (Hosmer–Lemeshow P = 0.859). At a low-risk threshold (predicted probability ≤ 15%), the negative predictive value reached 94.7%, facilitating the rule-out of chronic progression. Decision curve analysis confirmed positive net benefit across threshold probabilities of 0%–60%. Conclusion This concise model incorporating anti-GPIIb antibody enables early risk stratification, primarily to identify children unlikely to develop c/pITP.