Background Biologics and targeted therapies are a first-line treatment option for individuals with Crohn’s disease (CD). Nevertheless, clinical remission rates vary considerably among different biologics and targeted therapies. This study aims to develop and validate a predictive nomogram for the response to biologics and targeted therapy in individuals with CD. Methods This study included individuals with CD admitted to the First People’s Hospital of Wuhu from January 2020 to June 2025. Clinical remission rates at 14 and 26 weeks were observed. The clinical remission rates of different biologics and targeted therapy were analyzed using the chi-square test, and multiple comparisons were performed. The least absolute contraction and selection operator (LASSO) regression algorithm was used to determine variables related to clinical remission. A nomogram model was constructed, and the model performance was assessed utilizing receiver operating characteristic (ROC) curves, calibration curves, and decision curves (DCA). Internal validation was performed using repeated sampling and Harrell’s concordance index (C-index). Results 218 patients were included in the study. Compared with other biologics, upadacitinib (UPA) had the highest clinical remission rate at week 26 (94.1%,16/17subjects). Nine variables were identified by LASSO regression, including pre-treatment Crohn’s disease activity index (CDAI), disease duration, smoking history, disease site, disease behavior, perianal lesions, hemoglobin (Hb), erythrocyte sedimentation rate (ESR), and type of biologic. The area under the curve (AUC value) was 0.796. The calibration curve and DCA curve showed good calibration and clinical applicability. The internal validation also demonstrated moderate discriminative performance, with a C-index of 0.74. Conclusions The study results demonstrate that UPA appears to show a significant clinical remission rate in a small cohort, but this finding needs to be validated in a larger-scale study. Furthermore, a practical tool has been developed to help clinicians identify the treatment response to biologics and targeted therapy in CD patients, promoting the development of personalized treatment and precision medicine.
Lin et al. (Thu,) studied this question.