AUTHOR=Zhong Chonghan , Ju Houqiong , Liu Dongning , He Penghui , Wang Daqiang , Yu Hongxin , Lu Weijie , Li Taiyuan 

TITLE=A nomogram and risk classification system forecasting the cancer-specific survival of lymph- node- positive rectal cancer patient after radical proctectomy

JOURNAL=Frontiers in Oncology

VOLUME=Volume 13 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2023.1120960

DOI=10.3389/fonc.2023.1120960

ISSN=2234-943X

ABSTRACT=Abstract
Background: Aim of the study was to develop and validate a nomogram for predicting cancer-specific survival (CSS) in lymph node positive rectal cancer patients after radical proctectomy.
Methods: In this study, we analyzed data collected from the Surveillance, Epidemiology, and End Results (SEER) database between 2004 and 2015. In addition, in a 7:3 randomized design, all patients were split into two groups (development and validation cohorts). CSS predictors selected via univariate and multivariate Cox regressions. The nomogram was constructed by analyzing univariate and multivariate predictors. The effectiveness of this nomogram was evaluated by concordance index (C-index), calibration plots, receiver operating characteristic (ROC) curve. Based on the total score of each patient in the development cohort in the nomogram, developing a risk stratification system. In order to analyze the survival outcomes among different risk groups, Kaplan-Meier method was used.
Results: We selected 4310 lymph node positive rectal cancer patients after radical proctectomy, including a development cohort (70%, 3017) and a validation cohort (30%, 1293). The nomogram correlation C-index for the development cohort and the validation cohort were 0.702 (95% CI: 0.687-0.717) and 0.690 (95% CI: 0.665-0.715) respectively. The calibration curves for 3- and 5-year CSS showed great concordance. The 3- and 5-year area under curve (AUC) of ROC curves in the development cohort were 0.758, 0.740 respectively, and 0.735, 0.730 in the validation cohort, respectively. Following the establishment of the nomogram, we also established a risk stratification system. According to their nomogram total points, patients were divided into three risk groups. There were significant differences between the low-risk group, the intermediate-risk group and the high-risk group (P< 0.05). 
Conclusions: As a result of our research, we developed a highly discriminatory and accurate nomogram and associated risk classification system to predict CSS in lymph node positive rectal cancer patients after radical proctectomy. This model can help predict the prognosis of patients with lymph node positive rectal cancer.