Development and validation of a nomogram for steroid-resistance prediction in immune thrombocytopenia patients

Objectives: Corticosteroid is first-line therapy in immune thrombocytopenia. However, nearly 30% of patients appear in steroid-resistance. Our research analyses the relevant indicators of patients and develops a risk prediction model to predict the poor response to steroid-therapy in ITP patients.

Methods: We collected data from 111 ITP patients admitted to Xiamen University Zhongshan Hospital from 2013 to 2019 as the training cohort and 65 ITP patients during 2019-2020 as the external validation cohort. Screening significant factors(P < 0.05) in univariate analysis, and further identified to be independent variables in multivariable logistic regression analysis. Incorporated the significant risk factors in and presented them with a nomogram based on independent risk predictors. The nomogram was assessed by receiver operating characteristics curves and decision curve analysis.

Results: We constructed a steroid-resistance prediction model based on the potential predictors including age, serum ferritin and expression of HBsAg. As a result, based on the area under the ROC curves, the training cohort (AUC: 0.718, 95% CI: 0.615-0.821) and the external validation cohort (AUC:0.799,95%CI:0.692-0.905), which displayed good discrimination. The decision curve showed that predicting the steroid-refractory risk in ITP patients using this nomogram with a range of the threshold probability between >16% and <70%. The nomogram appears good performance in predicting steroid-refractory ITP patients.

Conclusion: Prediction model shows that elder patients with a high level of ferritin and positive expression of HBsAg may appear a high possibility of steroid-resistance. For these patients, TPO-RAs can be considered to help patients to get better treatment effects and develop a better health-related quality of life.