Development and validation of a nomogram to predict non-response to 5-aminosalicylic acid in patients with ulcerative colitis

Abstract

Background: there are some patients with ulcerative colitis (UC) who have non-response (NR) to 5-aminosalicylic acid (5-ASA). To promote individualized treatment in UC patients, it is crucial to identify valid predictors to estimate NR to 5-ASA. Therefore, this study aimed to identify the predictive value of clinical and biochemical markers and to construct a nomogram model predicting NR to 5-ASA in patients with UC. Methods: data of patients diagnosed with UC in the First Hospital of China Medical University between January 2012 and December 2020 were retrospectively analyzed. Primary outcome was the proportion of NR to 5-ASA. Multivariable logistic regression was used to construct prediction models. Area under the curve (AUC), calibration and decision curve analyses (DCA) were assessed in the validation cohort. Results: of 284 UC patients who were treatment-naive, 86 (30.3 %) had NR to 5-ASA. Univariate regression analysis showed that disease classification (DC) (p = 0.008), monocytes (MONO) (p = 0.041), platelet distribution width (PDW) (p = 0.027), serum total cholesterol (TC) (p = 0.031) and a1 globulin (p < 0.001) were strongly associated with NR to 5-ASA. Receiver operating characteristics (ROC) analysis indicated the AUC was 0.852, it showed that this model has a good degree of discrimination. The DCA curve showed that the predicted probability is 0.0-96.0 %. Conclusion: this study developed a predictive model with good discrimination and calibration, and high clinical validity, which can effectively estimate the risk of NR to 5-ASA. DC, MONO, PDW, TC and a1 globulin can be used as predictors for NR to 5-ASA in UC patients.