Study on the Influencing Factors of the First-Line Treatment Response to Primary Immune Thrombocytopenia in Children

Bihan Zhang^*Qian HuQiaodao WuJianying Ning^*

• Department of Pediatrics, The First Affiliated Hospital of Shihezi University, Shihezi, Xinjiang, China

Aims: This study aims to investigate the factors influencing the first-line treatment response in children with primary immune thrombocytopenia (ITP) and to evaluate the predictive value of these indicators for therapeutic outcomes. Methods: A total of 140 pediatric patients diagnosed with ITP at the Pediatrics Department of the First Affiliated Hospital of Shihezi University, between June 2022 and December 2024, were enrolled. Patients were grouped according to the type of first-line treatment and treatment response. Laboratory tests such as platelet parameters, P-glycoprotein (P-gp), T lymphocyte subsets, immunoglobulins, and complements were collected and analyzed. Results: Multivariate logistic regression analysis identified elevated P-gp and platelet-to-lymphocyte ratio (PLR), decreased of CD4⁺/CD8⁺ ratio and complement 3 (C3) levels as independent risk factors for glucocorticosteroid (GC) treatment failure in children with ITP. Receiver operating characteristic curve (ROC) analysis identified the areas under the curve (AUCs) were 0.772, 0.763, 0.731, and 0.731. The combined model yielded an AUC of 0.919. Elevated PLR and immunoglobulin G (IgG) were independent risk factors for intravenous immune globulin (IVIG) treatment failure.ROC analysis showed that PLR and IgG were predictive of IVIG treatment failure in children with ITP. The AUCs were 0.769 and 0.722, respectively. The combined model yielded an AUC of 0.810. Conclusions: Elevated P-gp and PLR, along with reduced CD4⁺/CD8⁺ ratio and C3 levels, are independent risk factors for GC treatment failure in children with ITP. For IVIG therapy, increased PLR and IgG levels are associated with poor response. These indicators demonstrate predictive value for first-line treatment efficacy, with combined marker analysis offering superior predictive accuracy compared to individual indicators.