Development of a clinical model to predict secondary non-response of infliximab treatment in Crohn's disease.

Abstract

Secondary non-response to infliximab (IFX) in patients with Crohn's disease (CD) is so common that prediction of non-response is required to adopt the optimal therapy for an individual patient. The clinical model was constructed in a training cohort. Clinical features, serological parameters, and genetic biomarkers at week 14 IFX therapy were obtained as predictors. Secondary non-response was defined at week 54. Univariate analysis was first performed to eliminate irrelevant predictors with non-response. Then, a logistic regression model was developed by using predictors with P < 0.1 in a univariate analysis. Finally, the model was validated with reference to its discrimination, calibration, and decision curve analysis (DCA). In a univariate analysis, erythrocyte sedimentation rate (ESR), the previous surgery, disease location, C-reactive protein (CRP), and TNFRSF1B (676 T>G) were found associated with secondary non-response to IFX. Logistic regression analysis with stepwise backward selection P < 0.05 then identified that ESR, the previous surgery, CRP, and TNFRSF1B (676 T>G) could serve as independent predictors, and a clinical model was developed based on the above predictors. Model 2 with TNFRSF1B (676 T>G) incorporated demonstrated more satisfactory discrimination (P = 0.029), better calibration (U P2 > 0.05), and higher clinical value in the validation cohort. The study presents a model to predict non-response to IFX in CD, which incorporates previous surgery, ESR, CRP, and TNFRSF1B (676 T>G). This model can be used to help clinicians adjust the therapeutic strategy and CD patients avoid unnecessary exposure to IFX.