Tao Su,1,2,* Ling Liu,3,* Fan Meng,4,* Hongzhen Wu,1,2 Tao Liu,1,2 Jun Deng,1,2 Xiang Peng,1,2 Min Zhi,1,2 Jiayin Yao1,2 

1Department of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Disease, The Sixth Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong Province, People’s Republic of China; 2Biomedical Innovation Center, The Sixth Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong Province, People’s Republic of China; 3Department of Anesthesiology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong Province, People’s Republic of China; 4Digestive System Department, The First Affiliated Hospital of Gannan Medical University, Ganzhou, People’s Republic of China

*These authors contributed equally to this work

Correspondence: Min Zhi; Jiayin Yao, Department of Gastroenterology, The Sixth Affiliated Hospital, Sun Yat-Sen University, 26th Yuancun the Second Road, Guangzhou, Guangdong Province, 510655, People’s Republic of China, Email zhimin@mail.sysu.edu.cn; yjyin@mail3.sysu.edu.cn

Background: Ustekinumab (UST) is recommended as the first-line treatment for patients with moderate to severe Crohn’s disease (CD). However, the efficacy of certain patients may be suboptimal and necessitate intensive treatment or modification of the treatment regimen. We sought to establish a nomogram model to predict the short-term effectiveness of UST in moderate to severe CD patients.
Methods: We established a derivation cohort comprising patients diagnosed with CD and treated with UST at the Sixth Affiliated Hospital of Sun Yat-sen University from May 2020 to July 2023. The patient data, including demographic and clinical characteristics as well as treatment details, were systematically collected. The achievement of clinical remission (defined as Crohn’s Disease Activity Index, CDAI < 150, without corticosteroid usage) after induction therapy was the endpoint observed during follow-up. Potential predictors were identified through the Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis. Subsequently, a multivariate logistic regression analysis was conducted to construct a nomogram model. The predictive accuracy and discriminative power of the model were assessed by Receiver Operating Characteristics (ROC) curves and calibration curves. Decision curve analysis (DCA) was employed to assess the clinical application value of the model.
Results: 162 patients were included in the derivation cohort. The predictor’s selection was according to the minimum criteria. Prognostic factors, including duration, body mass index (BMI), smoking, extraintestinal manifestations (EIMs), perianal lesions (P), history of Vedolizumab therapy, and albumin levels (ALB), were identified and included in the nomogram. The model showed good discrimination and calibration on internal validation based on the bootstrap method (C-index: 0.843, 95% confidence interval: 0.768– 0.903). Moreover, DCA demonstrated that the nomogram was clinically beneficial.
Conclusion: We constructed a practical tool to assist clinicians in identifying moderate to severe CD patients who are expected to have a good clinical response to UST, promoting personalized treatment and the development of precision medicine.

Keywords: Ustekinumab, Crohn’s disease, clinical remission, nomogram