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

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.

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.

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.

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.