Chunyan Cui1, Min Zhang2, Li Tian1, Wu Jiang3, Zhifang Zeng4, Li Li1. 1. Imaging Diagnosis and Interventional Center, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine 651 Dongfeng Road East, Guangzhou 510060, People's Republic of China. 2. Department of Radiology, The People's Hospital of Laiwu Laiwu 271100, People's Republic of China. 3. Department of Colorectal Surgery, Sun Yat-sen University Cancer Center Guangzhou, People's Republic of China. 4. Department of Radiation Oncology, Sun Yat-sen University Cancer Center Guangzhou, People's Republic of China.
Abstract
PURPOSE: To determine the correlation between pretreatment computed tomography (CT) data and survival duration after neoadjuvant chemoradiotherapy and surgery for locally advanced rectal cancer. MATERIALS AND METHODS: 122 consecutive patients with advanced rectal cancer were assessed retrospectively. Pretreatment imaging and postoperative data were evaluated through Kaplan-Meier and Cox proportional hazard regression analyses. RESULTS: Pretreatment CT identified 557 metastatic lymph nodes (mean, 4.55 per patient; median 4). Survival durations were measured during the period between the application of CT and death or the last follow-up examination. Univariate analysis showed that the following factors had a significant impact on survival: maximum tumor diameter (P = 0.019), distance from inferior tumor margin to anorectal ring (P <0.0001), number of lymph nodes involved in patients with short-axis, lymph node diameter ≥8 mm (P <0.0001) in pretreatment CT, distance from the anorectal ring (P = 0.027), ypN stage (P = 0.0008), ypM stage (P = 0.046) and number of metastatic lymph nodes (P <0.0001) in clinical assessment. Multivariate analysis showed that the following factors were significant: number of lymph nodes in patients with short-axis lymph node diameter ≥5 mm but <8 mm (P = 0.044) and in those with this diameter ≥8 mm (P = 0.028; pretreatment CT) and number of metastatic lymph nodes (assessed in histopathological examination). CONCLUSION: Pretreatment lymph node size and number can predict survival duration after treatment for locally advanced rectal cancer. For patients with lymph nodes >8 mm (short-axis diameter) and/or >1, such lymph nodes tend to have a poor performance for prognosis.
PURPOSE: To determine the correlation between pretreatment computed tomography (CT) data and survival duration after neoadjuvant chemoradiotherapy and surgery for locally advanced rectal cancer. MATERIALS AND METHODS: 122 consecutive patients with advanced rectal cancer were assessed retrospectively. Pretreatment imaging and postoperative data were evaluated through Kaplan-Meier and Cox proportional hazard regression analyses. RESULTS: Pretreatment CT identified 557 metastatic lymph nodes (mean, 4.55 per patient; median 4). Survival durations were measured during the period between the application of CT and death or the last follow-up examination. Univariate analysis showed that the following factors had a significant impact on survival: maximum tumor diameter (P = 0.019), distance from inferior tumor margin to anorectal ring (P <0.0001), number of lymph nodes involved in patients with short-axis, lymph node diameter ≥8 mm (P <0.0001) in pretreatment CT, distance from the anorectal ring (P = 0.027), ypN stage (P = 0.0008), ypM stage (P = 0.046) and number of metastatic lymph nodes (P <0.0001) in clinical assessment. Multivariate analysis showed that the following factors were significant: number of lymph nodes in patients with short-axis lymph node diameter ≥5 mm but <8 mm (P = 0.044) and in those with this diameter ≥8 mm (P = 0.028; pretreatment CT) and number of metastatic lymph nodes (assessed in histopathological examination). CONCLUSION: Pretreatment lymph node size and number can predict survival duration after treatment for locally advanced rectal cancer. For patients with lymph nodes >8 mm (short-axis diameter) and/or >1, such lymph nodes tend to have a poor performance for prognosis.
Authors: E Kapiteijn; C A Marijnen; I D Nagtegaal; H Putter; W H Steup; T Wiggers; H J Rutten; L Pahlman; B Glimelius; J H van Krieken; J W Leer; C J van de Velde Journal: N Engl J Med Date: 2001-08-30 Impact factor: 91.245
Authors: Glòria Fernández-Esparrach; Juan R Ayuso-Colella; Oriol Sendino; Mario Pagés; Miriam Cuatrecasas; Maria Pellisé; Joan Maurel; Carmen Ayuso-Colella; Begoña González-Suárez; Josep Llach; Antoni Castells; Angels Ginès Journal: Gastrointest Endosc Date: 2011-08 Impact factor: 9.427
Authors: Chan Wook Kim; Chang Sik Yu; Song-Soo Yang; Kyung Ho Kim; Yong Sik Yoon; Sang Nam Yoon; Seok-Byung Lim; Jin Cheon Kim Journal: Ann Surg Oncol Date: 2011-05-03 Impact factor: 5.344
Authors: Juan A Díaz-González; Felipe A Calvo; Javier Cortés; José L García-Sabrido; Marina Gómez-Espí; Emilio Del Valle; Fernando Muñoz-Jiménez; Emilio Alvarez Journal: Int J Radiat Oncol Biol Phys Date: 2006-01-06 Impact factor: 7.038
Authors: E A Zerhouni; C Rutter; S R Hamilton; D M Balfe; A J Megibow; I R Francis; A A Moss; J P Heiken; C M Tempany; A M Aisen; J C Weinreb; C Gatsonis; B J McNeil Journal: Radiology Date: 1996-08 Impact factor: 11.105