Objective:To investigate the influencing factors of mucosal healing under endoscopy in patients with Crohn′s disease (CD) and to establish a predictive model.Methods:From January 1, 2023 to August 31, 2024, 124 patients with CD were hospitalized at the Department of Gastroenterology, Renmin Hospital of Wuhan University were retrospectively enrolled as the modeling group. And from January 1, 2021 to December 31, 2022, 88 patients with CD were hospitalized at the Department of Gastroenterology in the same hospital were collected as the validation group. The data including simple Crohn′s disease activity index (CDAI) scores, serological markers such as fibrinogen (FIB), and medication regimens (including ustekinumab) of the patients in the modeling group were collected. Multivariate logistic regression analysis was used to screen the independent predictors of mucosal healing in CD patients, and the nomogram predictive model was established. The receiver operating characteristic curve (ROC) was plotted to evaluate the predictive performance, and calibration curve was drawn for validation. Mann-Whitney U test and Chi-square test were used for statistical analysis. Results:According to the simple endoscopic score for CD and endoscopic findings, among the 124 patients in the modeling group, 92 cases were diagnosed as mucosal healing, while 32 cases did not. The simple CDAI and FIB of patients with mucosal healing were lower than those of patients without mucosal healing (2.00(2.00, 3.00) vs. 3.00(2.25, 4.00), 2.37(2.03, 2.88) g/L vs.2.92(2.40, 4.40) g/L); the proportion of patients who used ustekinumab in mucosal healing patients was higher than that of patients without mucosal healing (62.0%, 57/92 vs. 31.2%, 10/32), and the differences were statistically significant ( Z=-2.98 and -3.57, χ2=9.01; all P<0.01).The results of multivariate logistic regression analysis showed that low simple CDAI score ( OR=0.560, 95% confidence interval (95% CI): 0.343 to 0.913), low FIB ( OR=0.475, 95% CI: 0.302 to 0.747), and ustekinumab usage ( OR=4.218, 95% CI: 1.621 to 10.977) were independent predictive factors of mucosal healing under endoscopy in CD patients (all P<0.05). The regression equation was derived as ln( p/(1- p)) mucosal healing=4.215-0.580×simple CDAI score -0.745×FIB(g/L)+ 1.439×ustekinumab usage(1 for use, 0 for unused), and the nomogram model was established. The results of ROC demonstrated that the area under the curve of the nomogram model in the modeling and validation group were 0.791(95% CI: 0.700 to 0.883) and 0.781 (95% CI: 0.666 to 0.895), with the sensitivity of 0.859 and 0.868, and with the specificity of 0.688 and 0.650, respectively. The results of calibration curve analysis showed that the average absolute errors of the nomogram model in the internal and external validation were 0.032 and 0.039, respectively, indicating a good consistency between the predicted and actual probability. Conclusions:Low simple CDAI score, low FIB, and ustekinumab usage are the independent predictive factors of mucosal healing under endoscopy in CD patients. The predictive model has certain reference value for CD management.

Objective:To investigate the influencing factors of mucosal healing under endoscopy in patients with Crohn′s disease (CD) and to establish a predictive model.Methods:From January 1, 2023 to August 31, 2024, 124 patients with CD were hospitalized at the Department of Gastroenterology, Renmin Hospital of Wuhan University were retrospectively enrolled as the modeling group. And from January 1, 2021 to December 31, 2022, 88 patients with CD were hospitalized at the Department of Gastroenterology in the same hospital were collected as the validation group. The data including simple Crohn′s disease activity index (CDAI) scores, serological markers such as fibrinogen (FIB), and medication regimens (including ustekinumab) of the patients in the modeling group were collected. Multivariate logistic regression analysis was used to screen the independent predictors of mucosal healing in CD patients, and the nomogram predictive model was established. The receiver operating characteristic curve (ROC) was plotted to evaluate the predictive performance, and calibration curve was drawn for validation. Mann-Whitney U test and Chi-square test were used for statistical analysis. Results:According to the simple endoscopic score for CD and endoscopic findings, among the 124 patients in the modeling group, 92 cases were diagnosed as mucosal healing, while 32 cases did not. The simple CDAI and FIB of patients with mucosal healing were lower than those of patients without mucosal healing (2.00(2.00, 3.00) vs. 3.00(2.25, 4.00), 2.37(2.03, 2.88) g/L vs.2.92(2.40, 4.40) g/L); the proportion of patients who used ustekinumab in mucosal healing patients was higher than that of patients without mucosal healing (62.0%, 57/92 vs. 31.2%, 10/32), and the differences were statistically significant ( Z=-2.98 and -3.57, χ2=9.01; all P<0.01).The results of multivariate logistic regression analysis showed that low simple CDAI score ( OR=0.560, 95% confidence interval (95% CI): 0.343 to 0.913), low FIB ( OR=0.475, 95% CI: 0.302 to 0.747), and ustekinumab usage ( OR=4.218, 95% CI: 1.621 to 10.977) were independent predictive factors of mucosal healing under endoscopy in CD patients (all P<0.05). The regression equation was derived as ln( p/(1- p)) mucosal healing=4.215-0.580×simple CDAI score -0.745×FIB(g/L)+ 1.439×ustekinumab usage(1 for use, 0 for unused), and the nomogram model was established. The results of ROC demonstrated that the area under the curve of the nomogram model in the modeling and validation group were 0.791(95% CI: 0.700 to 0.883) and 0.781 (95% CI: 0.666 to 0.895), with the sensitivity of 0.859 and 0.868, and with the specificity of 0.688 and 0.650, respectively. The results of calibration curve analysis showed that the average absolute errors of the nomogram model in the internal and external validation were 0.032 and 0.039, respectively, indicating a good consistency between the predicted and actual probability. Conclusions:Low simple CDAI score, low FIB, and ustekinumab usage are the independent predictive factors of mucosal healing under endoscopy in CD patients. The predictive model has certain reference value for CD management.

Objective:To investigate the risk factors and establish a prediction model of primary non-response (PNR) to anti-tumor necrosis factor-α(TNF-α) monoclonal antibody in Crohn′s disease (CD) patients.Methods:From December 1, 2018 to July 31, 2022, 103 patients with CD treated with the anti-TNF-α monoclonal antibody in Renmin Hospital of Wuhan University were enrolled (modeling group), and at the same time, 109 patients with CD treated with anti-TNF-α monoclonal antibody in Zhongnan Hospital of Wuhan University were selected (validation group). The baseline clinical data of all the patients before the first treatment of anti-TNF-α monoclonal antibody were collected, which included C-reactive protein (CRP), the simplified Crohn′s disease activity index (CDAI), and modified multiplier simple endoscopic score for Crohn′s disease (MM-SES-CD), etc. Multivariate logistic regression was used to screen the independent risk factors of PNR in patients with CD treated with the anti-TNF-α monoclonal antibody, and to establish the nomograms prediction model. The area under the curve (AUC) of the receiver operating characteristic curve (ROC), the net reclassification index (NRI), integrated discrimination improvement index (IDI), and decision curve analysis (DCA) were used to evaluate the predictive efficacy and clinical application value of the prediction model. DeLong test was used for statistical analysis.Results:The results of multivariate logistic regression analysis showed that high level of CRP ( OR=1.030, 95% confidence interval (95% CI) 1.002 to 1.059), simplified CDAI ( OR=1.399, 95% CI 1.023 to 1.913), and MM-SES-CD ( OR=1.100, 95% CI 1.025 to 1.181) in baseline were independent risk factors of PNR in patients with CD treated with the anti-TNF-α monoclonal antibody ( P=0.033, 0.036 and 0.008). The results of ROC analysis showed that the AUCs of CRP, simplified CDAI, MM-SES-CD, and the prediction model in the modeling group and the validation group were 0.697(95% CI 0.573 to 0.821), 0.772(95% CI 0.666 to 0.879), 0.819(95% CI 0.725 to 0.912), 0.869 (95% CI 0.786 to 0.951) and 0.856 (95% CI 0.756 to 0.955), respectively. The AUC of the prediction model in the modeling group was greater than those of CRP and simplified CDAI, and the differences were statistically significant ( Z=3.00 and 2.75, P=0.003 and 0.006), while compared with MM-SES-CD and the validation group, the differences were not statistically significant (both P>0.05). However, compared with MM-SES-CD, the NRI and IDI of the prediction model in the modeling group were 0.205(95% CI 0.002 to 0.409, P=0.048) and 0.098(95% CI 0.022 to 0.174, P=0.011), respectively, suggesting that the predictive ability of the prediction model was better than that of MM-SES-CD. The results of DCA indicated that the prediction model had significant clinical benefits in both the modeling group and the validation group. Conclusions:A prediction model was successfully constructed based on the independent risk factors for PNR in patients with CD treated with the anti-TNF-α monoclonal antibody. After verification, the prediction model has good prediction performance and significant clinical benefits.