Establishment and Internal Validation of a Model to Predict the Efficacy of Adalimumab in Crohn's Disease

Background Clinically, the ability to distinguish which Crohn's Disease patients can benefit from Adalimumab is limited. Aims This study aimed to develop a model for predicting clinical remission probability for Crohn's disease patients with Adalimumab at 12 weeks. Methods Demographic and clinical characteristics of Crohn's disease patients were utilized to develop a model for clinical remission probability. The discriminatory and calibrating ability of the model and the internal validation were determined. Results 68 patients with Crohn's disease were enrolled in this study. Clinical remission was observed in 55.9% at 12 weeks. Three variables were selected through the least absolute shrinkage and selection operator regression method, including Adalimumab-positive cell count, disease duration, and neutrophil count of Crohn's disease patients. A predictive model was constructed by multivariate logistic regression (Adalimumab-positive cell count (OR, 1.143; 95%CI, 1.056–1.261), disease duration (OR, 0.967; 95%CI, 0.937–0.986), and neutrophil count (×10 ⁹ /L) (OR, 1.274; 95%CI,1.014–1.734)). The predictive model yielded an area under the curve of 0.866 (95%CI, 0.776–0.956), and in the internal validation, the area under the curve was 0.870 (95%CI, 0.770–0.940). Conclusions The predicting model is of great value for predicting clinical remission probability in Crohn's disease patients with Adalimumab therapies.