| Autor: |
Guo, Huili, Tang, Jian, Qin, Xiusen, Lin, Minzhi, Li, Miao, Yang, Qingfan, Huang, Zicheng, Gao, Xiang, Chao, Kang |
| Předmět: |
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| Zdroj: |
Gastroenterology Report; 2024, Vol. 12, p1-7, 7p |
| Abstrakt: |
Background Small bowel involvement is related to poor prognosis in Crohn's disease (CD), which may be a potential marker to stratify patients with a high risk of progression. This study aimed to establish a novel location classification system for CD and to develop a predictive model for disease progression. Methods Consecutive patients with non-stricturing/non-penetrating CD were retrospectively included in the Sixth Affiliated Hospital, Sun Yat-sen University (Guangzhou, P. R. China) between January 2012 and January 2018. Patients were classified into two groups according to disease location: small bowel involvement group and isolated colon group. The primary outcome was disease progression to stricturing or penetrating phenotypes. Progression-free survival was estimated using Cox proportional hazards regression analysis and Kaplan–Meier method. Results A total of 463 patients were analysed, with a median follow-up time of 55.3 months. Patients with small bowel involvement had a higher risk of disease progression than those with isolated colon disease (hazard ratio = 1.998, P = 0.007), while no differences were found between Montreal location classification and disease progression. Median progression-free survival was higher in the isolated colon group than in the small bowel involvement group (84.5 vs 77.3 months, P = 0.006). Four independent factors associated with disease progression were identified: small bowel involvement, duration of onset of >1 year, deep mucosal ulcer, and C-reactive protein levels of ≥10 mg/L (all P < 0.05). The nomogram model based on these factors showed good performance in predicting disease progression, with a C-index of 0.746 (95% confidence interval, 0.707–0.785). Conclusions Classifying CD based on small bowel involvement and isolated colon was superior to the Montreal location classification for predicting disease progression. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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