BACKGROUND: Local recurrence is one of the remaining problems in rectal and rectosigmoid cancer, and it is sometimes difficult to treat. OBJECTIVE: This study aimed to explore various factors that are highly related to local recurrence and to develop a new prediction model for local recurrence after curative resection. DESIGN: This is a retrospective cohort study SETTINGS:: This study was conducted at 2 academic hospitals in Japan and Korea. PATIENTS: A total of 2237 patients with stage I to III rectal and rectosigmoid cancer who underwent a curative operation with a negative circumferential margin were selected. INTERVENTIONS: Surgical treatment was the intervention. MAIN OUTCOME MEASURES: Local recurrence was the primary outcome measure. RESULTS: A total of 1232 patients were selected, and rectosigmoid cancer with rare local recurrence (2/221) was excluded. A different set of 792 patients with rectal cancer were chosen for validation. Multivariate analysis showed the following factors as significant for local recurrence: poorly differentiated tumor (HR, 11.2; 95% CI, 4.5-28.0), tumor depth (HR, 5.0), lymph node metastasis (HR, 4.1), operative procedure (HR, 3.2), postoperative complications (HR, 2.9), tumor location (HR, 2.6), and CEA level (HR, 2.4); a new prediction score was created by using these factors. A poorly differentiated tumor was assigned 2 points, and all other factors were assigned 1 point each. Patients who scored more than 5 points (n = 21) were judged as "high risk," with a 2-year local recurrence rate of 66.5%. The new predictive model could also separate the patients into different risk groups in the validation set. The high-risk group had higher recurrence rates than medium- and low-risk groups (2-year local recurrence rate: 41%, 15%, and 2.1%). LIMITATIONS: This study was limited by its retrospective nature and potential for selection bias. CONCLUSIONS: Seven factors were shown to be significantly correlated with the local recurrence of rectal cancer, and the usefulness of this new prediction model was demonstrated. See Video Abstract at http://links.lww.com/DCR/A429.
BACKGROUND: Local recurrence is one of the remaining problems in rectal and rectosigmoid cancer, and it is sometimes difficult to treat. OBJECTIVE: This study aimed to explore various factors that are highly related to local recurrence and to develop a new prediction model for local recurrence after curative resection. DESIGN: This is a retrospective cohort study SETTINGS:: This study was conducted at 2 academic hospitals in Japan and Korea. PATIENTS: A total of 2237 patients with stage I to III rectal and rectosigmoid cancer who underwent a curative operation with a negative circumferential margin were selected. INTERVENTIONS: Surgical treatment was the intervention. MAIN OUTCOME MEASURES: Local recurrence was the primary outcome measure. RESULTS: A total of 1232 patients were selected, and rectosigmoid cancer with rare local recurrence (2/221) was excluded. A different set of 792 patients with rectal cancer were chosen for validation. Multivariate analysis showed the following factors as significant for local recurrence: poorly differentiated tumor (HR, 11.2; 95% CI, 4.5-28.0), tumor depth (HR, 5.0), lymph node metastasis (HR, 4.1), operative procedure (HR, 3.2), postoperative complications (HR, 2.9), tumor location (HR, 2.6), and CEA level (HR, 2.4); a new prediction score was created by using these factors. A poorly differentiated tumor was assigned 2 points, and all other factors were assigned 1 point each. Patients who scored more than 5 points (n = 21) were judged as "high risk," with a 2-year local recurrence rate of 66.5%. The new predictive model could also separate the patients into different risk groups in the validation set. The high-risk group had higher recurrence rates than medium- and low-risk groups (2-year local recurrence rate: 41%, 15%, and 2.1%). LIMITATIONS: This study was limited by its retrospective nature and potential for selection bias. CONCLUSIONS: Seven factors were shown to be significantly correlated with the local recurrence of rectal cancer, and the usefulness of this new prediction model was demonstrated. See Video Abstract at http://links.lww.com/DCR/A429.
Authors: Wei Xu; Yazhou He; Yuming Wang; Xue Li; Jane Young; John P A Ioannidis; Malcolm G Dunlop; Evropi Theodoratou Journal: BMC Med Date: 2020-06-26 Impact factor: 8.775
Authors: Biche Osong; Carlotta Masciocchi; Andrea Damiani; Inigo Bermejo; Elisa Meldolesi; Giuditta Chiloiro; Maaike Berbee; Seok Ho Lee; Andre Dekker; Vincenzo Valentini; Jean-Pierre Gerard; Claus Rödel; Krzysztof Bujko; Cornelis van de Velde; Joakim Folkesson; Aldo Sainato; Robert Glynne-Jones; Samuel Ngan; Morten Brændengen; David Sebag-Montefiore; Johan van Soest Journal: Phys Imaging Radiat Oncol Date: 2022-03-29
Authors: Waad Farhat; Mohamed Azzaza; Abdelkader Mizouni; Houssem Ammar; Mahdi Ben Ltaifa; Sami Lagha; Mohamed Kahloul; Rahul Gupta; Mohamed Ben Mabrouk; Ali Ben Ali Journal: World J Surg Oncol Date: 2019-10-28 Impact factor: 2.754