Yufeng Wang1,2, Jiayuan Wu1,3, Hairong He3, Huan Ma2, Liren Hu4, Jiyu Wen5, Jun Lyu6,7. 1. Department of Clinical Research, Affiliated Hospital of Guangdong Medical University, Zhanjiang, Guangdong, People's Republic of China. 2. School of Public Health, Guangdong Medical University, No. 2, Wenmin East Road, Zhanjiang, 524023, Guangdong, People's Republic of China. 3. Clinical Research Center, First Affiliated Hospital of Xi'an Jiaotong University, No. 277, Yanta West Road, Xi'an, 710061, Shaanxi, People's Republic of China. 4. School of Public Health, Guangdong Medical University, No. 2, Wenmin East Road, Zhanjiang, 524023, Guangdong, People's Republic of China. fox833@163.com. 5. Department of Oncology, Affiliated Hospital of Guangdong Medical University, No. 57, South of Renmin Avenue, Zhanjiang, 524001, Guangdong, People's Republic of China. 15812388788@163.com. 6. Clinical Research Center, First Affiliated Hospital of Xi'an Jiaotong University, No. 277, Yanta West Road, Xi'an, 710061, Shaanxi, People's Republic of China. lujun2006@xjtu.edu.cn. 7. Clinical Research Center, First Affiliated Hospital of Jinan Unversity, Guangzhou, Guangdong, People's Republic of China. lujun2006@xjtu.edu.cn.
Abstract
BACKGROUND: The incidence of rectal cancer has meaningfully increased in young patients. However, quantitative evaluation for the competing data of early-onset rectal cancer is lacking. So, we performed a competing risk analysis to calculate the cumulative incidence of death for patients with early-onset rectal cancer and developed a nomogram to predict the probability of cancer-specific mortality for these patients. METHODS: We abstracted data of patients with early-onset rectal cancer between 2004 and 2016 by using the Surveillance, Epidemiology, and End Results program database. The cumulative incidence function was used to calculate the crude cancer-specific mortality of early-onset rectal cancer. Fine and Gray's proportional sub-distribution hazard model was adopted to explore the risk factors of cancer-specific death. Then, we establish a nomogram to predict their 3-, 5-, and 10-year probabilities. RESULTS: We identified 9917 patients with early-onset rectal cancer, and they were randomly divided into training (n = 6941) and validation (n = 2976) cohorts. In the training cohort, the 3-, 5-, and 10-year cumulative incidences of cancer-specific death after diagnosis for early-onset rectal cancer were 11.4%, 19.9%, and 28.8%, respectively. Fine and Gray's model showed that sex, race, marital status, histology, T stage, N stage, M stage, examined lymph nodes, and pretreatment carcinoembryonic antigen were independently associated with cancer-specific mortality. Such factors were selected to develop a prognostic nomogram. CONCLUSION: The competing risk nomogram has an ideal performance for predictive cancer-specific mortality in early-onset rectal cancer.
BACKGROUND: The incidence of rectal cancer has meaningfully increased in young patients. However, quantitative evaluation for the competing data of early-onset rectal cancer is lacking. So, we performed a competing risk analysis to calculate the cumulative incidence of death for patients with early-onset rectal cancer and developed a nomogram to predict the probability of cancer-specific mortality for these patients. METHODS: We abstracted data of patients with early-onset rectal cancer between 2004 and 2016 by using the Surveillance, Epidemiology, and End Results program database. The cumulative incidence function was used to calculate the crude cancer-specific mortality of early-onset rectal cancer. Fine and Gray's proportional sub-distribution hazard model was adopted to explore the risk factors of cancer-specific death. Then, we establish a nomogram to predict their 3-, 5-, and 10-year probabilities. RESULTS: We identified 9917 patients with early-onset rectal cancer, and they were randomly divided into training (n = 6941) and validation (n = 2976) cohorts. In the training cohort, the 3-, 5-, and 10-year cumulative incidences of cancer-specific death after diagnosis for early-onset rectal cancer were 11.4%, 19.9%, and 28.8%, respectively. Fine and Gray's model showed that sex, race, marital status, histology, T stage, N stage, M stage, examined lymph nodes, and pretreatment carcinoembryonic antigen were independently associated with cancer-specific mortality. Such factors were selected to develop a prognostic nomogram. CONCLUSION: The competing risk nomogram has an ideal performance for predictive cancer-specific mortality in early-onset rectal cancer.
Authors: Maria C Russell; Y Nancy You; Chung-Yuan Hu; Janice N Cormier; Barry W Feig; John M Skibber; Miguel A Rodriguez-Bigas; Heidi Nelson; George J Chang Journal: JAMA Surg Date: 2013-08 Impact factor: 14.766
Authors: W van Gijn; R G P M van Stiphout; C J H van de Velde; V Valentini; G Lammering; M A Gambacorta; L Påhlman; K Bujko; P Lambin Journal: Ann Oncol Date: 2015-01-21 Impact factor: 32.976