Keele Research Repository

OBJECTIVE: To develop and validate a prognostic model for leflunomide discontinuation with abnormal blood-test results. METHODS: Data from CPRD Gold and Aurum were used for model development and external validation respectively. Participants prescribed leflunomide between 01/01/2007 and 31/12/2019 were followed-up from six-months after first GP-prescription to the earliest of date of outcome, death, 5-year follow-up or 31/12/2019. Candidate prognostic factors were ascertained using theory and data driven approaches. Penalised Cox regression was performed to develop the risk equation, followed by internal validation using 500-bootstraps to correct for optimism. Multiple imputation was applied to handle missing data. Model performance was assessed in terms of calibration and discrimination. RESULTS: Data for 1,487 and 2,329 participants contributing 3,140 and 5,246 person-years follow-up were included in the development and validation cohorts, respectively. Thirteen candidate predictors were included in the model. Epilepsy, and either cytopenia or elevated liver enzymes during first six months of shared-care leflunomide prescription were strong predictors of drug discontinuation with hazard ratio (95%CI) 4.39 (1.74 -11.06) and 3.06 (2.15 - 4.35), respectively. The unadjusted and optimism adjusted calibration slope in development data was 1.00 (95% CI 0.75-1.25) and 0.72 (95% CI 0.47-0.97), respectively. The calibration slope in validation data was 0.91 (95% CI 0.74-1.07). The model showed prognostic separation with optimism adjusted Royston D statistic of 0.73 (95% CI 0.44-1.02). CONCLUSION: We have developed and externally validated an easy-to-use prognostic model that may be used to risk-stratify monitoring for leflunomide toxicity and to make informed choices about risks when choosing treatments.