Shu Yan1,2, Haiyang Ding3, Xiaomu Zhao1,2, Jin Wang4,5, Wei Deng6,7. 1. Department of Gastrointestinal Surgery, Capital Medical University Affiliated Beijing Friendship Hospital, Beijing, People's Republic of China. 2. Beijing Key Laboratory of Cancer Invasion and Metastasis Research & National Clinical Research Center for Digestive Diseases, Beijing, People's Republic of China. 3. Graduate School of Capital Medical University, Capital Medical University Affiliated Beijing Friendship Hospital, Beijing, People's Republic of China. 4. Department of Gastrointestinal Surgery, Capital Medical University Affiliated Beijing Friendship Hospital, Beijing, People's Republic of China. drwangjin522@163.com. 5. Beijing Key Laboratory of Cancer Invasion and Metastasis Research & National Clinical Research Center for Digestive Diseases, Beijing, People's Republic of China. drwangjin522@163.com. 6. Department of Gastrointestinal Surgery, Capital Medical University Affiliated Beijing Friendship Hospital, Beijing, People's Republic of China. dengweiwei@126.com. 7. Beijing Key Laboratory of Cancer Invasion and Metastasis Research & National Clinical Research Center for Digestive Diseases, Beijing, People's Republic of China. dengweiwei@126.com.
Abstract
PURPOSE: The aim of this study was to develop and validate a nomogram to assist physicians making further decisions on the requirement of a radical surgery for T1 colorectal cancer (CRC) after local excision through preoperative prediction of lymph node metastasis (LNM). METHODS: A total of 141 T1 CRC patients were enrolled from January 2013 to August 2020. The independent predictive parameters were determined in multivariate analyses. The nomogram was constructed based on predictors of LNM and its performance was evaluated with respect to its calibration, discrimination, and decision curve analysis. Internal validation by bootstrapping was performed to verify the applicability of the nomogram. RESULTS: cN in CT/MRI (N+), histologic type (poorly differentiated, mucinous adenocarcinoma, and signet-ring cell carcinoma), tumor budding (G3), and lymphovascular invasion were identified in the multivariable analysis (p<0.05). The developed nomogram incorporated these four predictors and it yielded good discrimination and calibration, with an area under the curve (AUC) of 0.89 (95% confidence interval [CI]: 0.80-0.97). However, the Japanese guideline yielded an AUC of 0.75 (95% CI: 0.63-0.87). A decision curve analysis showed that the predictive scoring system had a high clinical application value, and the nomogram conferred a greater benefit than the Japanese guideline did (range of threshold within 10%-80%). CONCLUSIONS: This study proposed a novel predictive model to assist physicians in making treatment decisions regarding additional surgery after local excision.
PURPOSE: The aim of this study was to develop and validate a nomogram to assist physicians making further decisions on the requirement of a radical surgery for T1 colorectal cancer (CRC) after local excision through preoperative prediction of lymph node metastasis (LNM). METHODS: A total of 141 T1 CRCpatients were enrolled from January 2013 to August 2020. The independent predictive parameters were determined in multivariate analyses. The nomogram was constructed based on predictors of LNM and its performance was evaluated with respect to its calibration, discrimination, and decision curve analysis. Internal validation by bootstrapping was performed to verify the applicability of the nomogram. RESULTS: cN in CT/MRI (N+), histologic type (poorly differentiated, mucinous adenocarcinoma, and signet-ring cell carcinoma), tumor budding (G3), and lymphovascular invasion were identified in the multivariable analysis (p<0.05). The developed nomogram incorporated these four predictors and it yielded good discrimination and calibration, with an area under the curve (AUC) of 0.89 (95% confidence interval [CI]: 0.80-0.97). However, the Japanese guideline yielded an AUC of 0.75 (95% CI: 0.63-0.87). A decision curve analysis showed that the predictive scoring system had a high clinical application value, and the nomogram conferred a greater benefit than the Japanese guideline did (range of threshold within 10%-80%). CONCLUSIONS: This study proposed a novel predictive model to assist physicians in making treatment decisions regarding additional surgery after local excision.
Entities:
Keywords:
Computed tomography; Local excision; Lymphovascular invasion; Magnetic resonance imaging; Predictive model
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