Atsuhiko Sumii1, Koya Hida2, Yoshiharu Sakai3, Nobuaki Hoshino1, Daisuke Nishizaki1, Tomonori Akagi4, Meiki Fukuda5, Tomohiro Yamaguchi6, Ichiro Takemasa7, Takuya Tokunaga8, Jun Watanabe9, Masahiko Watanabe10. 1. Department of Surgery, Kyoto University Graduate School of Medicine, 54 Shogoin-Kawahara-cho, Sakyo-ku, Kyoto, 606-8507, Japan. 2. Department of Surgery, Kyoto University Graduate School of Medicine, 54 Shogoin-Kawahara-cho, Sakyo-ku, Kyoto, 606-8507, Japan. hidakoya@kuhp.kyoto-u.ac.jp. 3. Department of Surgery, Osaka Red Cross Hospital, Osaka, Japan. 4. Gastroenterological and Pediatric Surgery, Oita University of Faculty of Medicine, Oita, Japan. 5. Department of Surgery, Kitano Hospital, Osaka, Japan. 6. Department of Gastroenterological Surgery, Cancer Institute Hospital of Japanese Foundation for Cancer Research, Tokyo, Japan. 7. Department of Gastroenterological Surgery, Graduate School of Medicine, Osaka University, Osaka, Japan. 8. Department of Surgery, Tokushima University, Tokushima, Japan. 9. Department of Surgery, Gastroenterological Center, Yokohama City University Medical Center, Yokohama, Japan. 10. Department of Surgery, Kitasato University Kitasato Institute Hospital, Tokyo, Japan.
Abstract
BACKGROUND: Identifying lateral pelvic lymph node (LPN) metastasis in low rectal cancer is crucial before treatment. Several risk factors and prediction models for LPN metastasis have been reported. However, there is no useful tool to accurately predict LPN metastasis. Therefore, we aimed to construct a nomogram for predicting LPN metastasis in rectal cancer. METHODS: We analyzed the risk factors for potential LPN metastasis by logistic regression analysis in 705 patients who underwent primary resection of low rectal cancer. We included patients at 49 institutes of the Japan Society of Laparoscopic Colorectal Surgery between June 2010 and February 2012. Clinicopathological factors and magnetic resonance imaging findings were evaluated. The nomogram performance was assessed using the c-index and calibration plots, and the nomogram was validated using an external cohort. RESULTS: In the univariable logistic regression analysis, age, sex, carcinoembryonic antigen, tumor location, clinical T stage, tumor size, circumferential resection margin (CRM), extramural vascular invasion (EMVI), and the short and long axes of LPN and perirectal lymph node (PRLN) were nominated as risk factors for potential LPN metastasis. We identified a combination of the short axis of LPN, tumor location, EMVI, and short axis of PRLN as optimal for predicting potential LPN metastasis and developed a nomogram using these factors. This model had a c-index of 0.74 and was moderately calibrated and well-validated. CONCLUSIONS: This is the first study to construct a well-validated nomogram for predicting potential LPN metastasis in rectal cancer, and its performance was high.
BACKGROUND: Identifying lateral pelvic lymph node (LPN) metastasis in low rectal cancer is crucial before treatment. Several risk factors and prediction models for LPN metastasis have been reported. However, there is no useful tool to accurately predict LPN metastasis. Therefore, we aimed to construct a nomogram for predicting LPN metastasis in rectal cancer. METHODS: We analyzed the risk factors for potential LPN metastasis by logistic regression analysis in 705 patients who underwent primary resection of low rectal cancer. We included patients at 49 institutes of the Japan Society of Laparoscopic Colorectal Surgery between June 2010 and February 2012. Clinicopathological factors and magnetic resonance imaging findings were evaluated. The nomogram performance was assessed using the c-index and calibration plots, and the nomogram was validated using an external cohort. RESULTS: In the univariable logistic regression analysis, age, sex, carcinoembryonic antigen, tumor location, clinical T stage, tumor size, circumferential resection margin (CRM), extramural vascular invasion (EMVI), and the short and long axes of LPN and perirectal lymph node (PRLN) were nominated as risk factors for potential LPN metastasis. We identified a combination of the short axis of LPN, tumor location, EMVI, and short axis of PRLN as optimal for predicting potential LPN metastasis and developed a nomogram using these factors. This model had a c-index of 0.74 and was moderately calibrated and well-validated. CONCLUSIONS: This is the first study to construct a well-validated nomogram for predicting potential LPN metastasis in rectal cancer, and its performance was high.