Open AccessRole of postoperative radiotherapy in pT3N0 rectal cancer: A risk‐stratification system based on population analyses
Author(s) -
Huang Yunxia,
Lin Yanzong,
Li Jinluan,
Zhang Xueqing,
Tang Lirui,
Zhuang Qingyang,
Lin Feifei,
Lin Xijin,
Wu Junxin
Publication year - 2019
Publication title -
cancer medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.403
H-Index - 53
ISSN - 2045-7634
DOI - 10.1002/cam4.1991
Subject(s) - medicine , proportional hazards model , oncology , radiation therapy , colorectal cancer , adjuvant radiotherapy , risk stratification , multivariate analysis , cancer
The impact of adjuvant radiotherapy in pT3N0 rectal cancer is controversial. We aimed to determine the risk factors for cancer‐specific survival (CSS) among these patients and to develop a risk‐stratification system to identify which of these patients would benefit from adjuvant radiotherapy. In this review of the Surveillance, Epidemiology, and End Results database (2010‐2014), we analyzed the data of pT3N0 rectal cancer patients who had not undergone neoadjuvant radiotherapy. Prognostic factors were identified using the Cox proportional hazards model, and risk scores were derived according to the β regression coefficient. A total of 1021 patients were identified from the database search. The overall 5‐year CSS was 86.31%. Multivariate analysis showed that age ( P < 0.001), tumor differentiation ( P = 0.044), number of nodes resected ( P = 0.032), marital status ( P = 0.005), and radiotherapy ( P = 0.006) were independent prognostic factors for CSS. A risk‐stratification system composed of age, tumor differentiation, and number of nodes resected was generated. Low‐risk patients had better CSS than high‐risk patients (92.13% vs 72.55%, P < 0.001). The addition of radiotherapy to surgery doubled the CSS among the high‐risk patients (42.06% vs 91.26%, P = 0.001) but produced no survival benefit among the low‐risk patients (93.36% vs 96.38%, P = 0.182). Our risk‐stratification model based on age, tumor differentiation, and number of nodes resected predicted the outcomes of pT3N0 rectal cancer patients. This model could help identify patients who may benefit from adjuvant radiotherapy.