Relationship between Lymph Node Ratio and Survival Rate in Preopertive Chemoradiation Rectal Cancer Patients

• Main Authors: Puvee Punmeechao, Chairat Supsamutchai, Thanida Janbavonkij, Chumpon Wilasrusmee, Tharin Thampongsa, Jakrapan Jirasiritham, Visarat Palitnonkiat, Pattawia Choikura
• Other Authors: Ramathibodi Hospital
• Format: Article
• Published: 2022
• Subjects: Medicine
• Online Access: https://repository.li.mahidol.ac.th/handle/123456789/77436
• Institution: Mahidol University

Background: Number of positive lymph nodes is one of the most-important prognostic factors in rectal cancer. Rectal cancer patients who undergo colorectal surgery following neoadjuvant chemoradiation therapy are sometimes unable to retrieve an adequate amount of lymph nodes. Objective: We proposed to confirm the new way to predict outcome of rectal cancer patients based on positive lymph node ratio. Materials and Methods: This is a retrospective, single-centered study, collecting data of patients from January 2011 to December 2017. Data from 149 patients with rectal cancer who underwent colorectal surgery following neoadjuvant chemoradiation were analyzed. Cox regression and Kaplan-Meier survival analysis were used to determine the prognostic values of lymph node ratio, total lymph nodes harvested, and TNM staging. Results: A higher positive lymph node ratio significantly related to poorer survival rate of patients with rectal cancer who received neoadjuvant chemoradiation. There was no statistically significant difference between total lymph nodes harvested and survival rate. There was no statistical difference in survival rate among pathological stages II, IIIA, IIIB, and IIIC. Five-year survival rates after neoadjuvant chemoradiation therapy were 86.18%, 75%, 86.50%, and 83.33% in rectal cancer patients stage II, IIIA, IIIB, and IIIC, respectively. Conclusion: The lymph node ratio can be used as predictor for survival in post-surgery rectal cancer patients who received neoadjuvant chemoradiation therapy. Future research is needed to find the optimum cut-off value.