Exploring the guiding role of the number of adverse pathological features in risk stratification for recurrence of stage Ⅰ-Ⅲ colorectal cancer: a retrospective cohort study of 9 875 cases

• Published in: Zhongguo ai zheng za zhi Vol. 34; no. 6; pp. 527 - 536
• Main Author: WENG Junyong, YE Zilan, ZHANG Ruoxin, LIU Qi, LI Xinxiang
• Format: Journal Article
• Language: English
• Published: Editorial Office of China Oncology 01.06.2024
• Subjects: colorectal cancer|recurrence|incorporating high-risk pathological features|prediction model
• ISSN: 1007-3639
• DOI: 10.19401/j.cnki.1007-3639.2024.06.001

Background and purpose: According to current consensus, adverse high-risk pathological features are only associated with adjuvant therapy for stage Ⅱ colorectal cancer (CRC). As important prognostic factors, we further explored the possibility of identifying patients with potential recurrence and poor prognosis based on these incorporating high-risk pathological features. Methods: This is a cohort study. A retrospective analysis was conducted on clinical data of CRC patients who underwent surgical treatment at the Second Department of Colorectal Surgery, Fudan University Affiliated Shanghai Cancer Center from 2008 to 2018. This study was approved by the Ethics Committee of the Fudan University Shanghai Cancer Center (approval No.: 050432-4-2108*), and the study complies with the Declaration of Helsinki. A total of 9 875 patients were enrolled, including 5 859 males and 4 016 females, aged [M (IQR)] 60 (16) years (range: 16 to 94). Median follow-up time was 1 779.0 days [95% CI: 1 750.1-1 807.9]. We used the Kaplan-Meier method to plot survival curves for different groups. Cox multivariate analysis was used to identify independent risk factors for 5-year overall survival (OS), disease-free survival (DFS) and recurrence-free survival (RFS). Finally, a column chart model was constructed to evaluate and stratify patient prognosis. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist was followed for this cohort study. Results: According to the number of incorporating high-risk pathological features, patients were divided into five groups: Hr_0 group (0 incorporating high-risk pathological feature), Hr_1 group (1 incorporating high-risk pathological feature), Hr_2 group (2 incorporating high-risk pathological features), Hr_3 group (3 incorporating high-risk pathological features), and Hr_4 group (4 or more incorporating high-risk pathological features). The Kaplan-Meier survival curve results indicated significant differences in OS, DFS and RFS among different groups (all P<0.001). Subgroup analysis was conducted on stage Ⅱ colorectal cancer, and the survival curves of OS, DFS and RFS in different Hr groups overlapped with each other. Compared to the overall population, the survival differences in different groups were significantly reduced, indicating that stage Ⅱ colon cancer patients with incorporating high-risk pathological features may benefit from adjuvant chemotherapy. The independent prognostic factors for RFS included age, pT stage, pN stage and Hr group. The survival curves of OS, DFS and RFS indicated that the prognosis of Hr_4 group was significantly worse than that of stage Ⅲc patients; 5.2% and 14.1% of stage Ⅰ and Ⅱ patients had two or more incorporating high-risk pathological features (Hr group≥2), respectively. Finally, a column chart model was constructed by incorporating the independent prognostic risk factors for CRC mentioned above. The calibration curve showed a good consistency between the actual observations and the predictions made by the nomogram, and the decision curve analysis (DCA) indicated that the model constructed in this study had good efficacy in stratifying recurrence. Conclusion: The number of incorporating high-risk pathological features is an independent prognostic factor for RFS in patients with stage Ⅰ-Ⅲ CRC. Combining it as a multiclass variable with age, pT and pN stage has good prognostic stratification and recurrence stratification efficacy, which is expected to guide clinical treatment.