Li Ying, Lai Xiaorong, Yang Dongyang, Ma Dong
Department II of Medical Oncology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
J Gastrointest Oncol. 2022 Oct;13(5):2393-2405. doi: 10.21037/jgo-22-878.
Colon cancer (CC) is the third most commonly diagnosed malignant tumor and remains the second leading cause of cancer-related deaths worldwide. However, the risk assessment of poor prognosis of CC is limited in previous studies. This study aimed to develop a predictive nomogram for the survival of CC patients.
In this retrospective cohort study, 113,239 CC patients from the Surveillance, Epidemiology, and End Results (SEER) database were randomly divided into training (n=56,619) and testing (n=56,620) sets with a ratio of 1:1. Demographic, clinical data and survival status of patients were extracted. The outcomes were 3- and 5-year survival of CC. Univariate and multivariate Cox regression analyses were used to screen the predictors to develop the predictive nomogram. Internal validation and stratified analyses were further assessed the nomogram. The C-index and area under the curve (AUC) were calculated to estimate the model's predictive capacity, and calibration curves were adopted to estimate the model fit.
Totally 38,522 (34.02%) patients died during the 5-year follow-up. The nomogram incorporated variables associated with the prognosis of CC patients, including age, gender, marital status, insurance status, tumor grade, stage (T/N/M), surgery, and number of nodes examined, with a C-index of 0.775 in the training set and 0.774 in the testing set. The AUCs of the nomogram for the 3- and 5-year survival prediction in the training set were 0.817 and 0.808, with the sensitivity of 0.688 and 0.716, and the specificity of 0.785 and 0.740, respectively. Similar results were found in the testing set. The C-index of the predictive nomogram for male, female, White, Black, and other races was 0.769, 0.779, 0.773, 0.770, and 0.770, respectively. The calibration curves for the nomogram in the above five cohorts showed a good agreement between actual and predicted values.
The nomogram may exhibit a certain predictive performance based on the SEER database, which may provide individual survival predictions for CC patients.
结肠癌（CC）是全球第三大最常被诊断出的恶性肿瘤，仍是癌症相关死亡的第二大主要原因。然而，先前研究中对CC预后不良的风险评估有限。本研究旨在开发一种用于预测CC患者生存情况的列线图。
在这项回顾性队列研究中，将来自监测、流行病学和最终结果（SEER）数据库的113239例CC患者按1:1的比例随机分为训练集（n = 56619）和测试集（n = 56620）。提取患者的人口统计学、临床数据和生存状态。结局指标为CC患者的3年和5年生存率。采用单因素和多因素Cox回归分析筛选预测因素以构建预测列线图。通过内部验证和分层分析进一步评估列线图。计算C指数和曲线下面积（AUC）以评估模型的预测能力，并采用校准曲线评估模型拟合度。
在5年随访期间，共有38522例（34.02%）患者死亡。该列线图纳入了与CC患者预后相关的变量，包括年龄、性别、婚姻状况、保险状况、肿瘤分级、分期（T/N/M）、手术以及检查的淋巴结数量，训练集的C指数为0.775，测试集的C指数为0.774。训练集中列线图对3年和5年生存预测的AUC分别为0.817和0.808，敏感性分别为0.688和0.716，特异性分别为0.785和0.740。测试集也得到了类似结果。男性、女性、白人、黑人及其他种族的预测列线图的C指数分别为0.769、0.779、0.773、0.770和0.770。上述五个队列中列线图的校准曲线显示实际值与预测值之间具有良好的一致性。
基于SEER数据库，该列线图可能具有一定的预测性能，可为CC患者提供个体生存预测。
