Objective: To determine a decision tree model that is an effective as well as less time- and cost-consuming method to identify those with high probability of development of systemic lupus erythematosus (SLE) amongst patients with immune thrombocytopenic purpura (ITP). Methods: We identified ITP patients without previous SLE diagnosis from the National Health Insurance Research Database between 1997 and 2012 and ascertained those who had the diagnosis of SLE during follow up. We also analyzed the symptoms and comorbidities as well as the dose of average oral steroid to derive the decision trees, which classified the ITP patients with different probabilities of development of SLE. Results: A total of 10,265 ITP patients were enrolled, among whom 80 patients developed SLE while following-up. The whole ITP patients were allocated to training group (7,186 patients including 57 with SLE) and testing group (3,079 patients including 23 with SLE); the former was used for derivation of the decision-tree based model and the latter for validation of the previously mentioned model, and provided high sensitivity (78.2%), specificity (99.2%) and negative prediction value (99.8%). To reduce the complexity, we also proposed another models with different complexity parameters (CP). Conclusion: We derived classification decision tree exempt from the necessity of laboratory data and suitable for various clinical scenarios of ITP patients, amongst whom were those with a high probability of SLE development.
- immune thrombocytopenic purpura
- systemic lupus erythematosus
- decision tree