Department of General Surgery, Ningbo No. 2 Hospital, Ningbo 315000, Zhejiang Province, China.
Center for Health Economics, Faculty of Humanities and Social Sciences, University of Nottingham, Ningbo 315100, Zhejiang Province, China.
World J Gastroenterol. 2024 Feb 7;30(5):450-461. doi: 10.3748/wjg.v30.i5.450.
Colorectal cancer (CRC) is a serious threat worldwide. Although early screening is suggested to be the most effective method to prevent and control CRC, the current situation of early screening for CRC is still not optimistic. In China, the incidence of CRC in the Yangtze River Delta region is increasing dramatically, but few studies have been conducted. Therefore, it is necessary to develop a simple and efficient early screening model for CRC.
To develop and validate an early-screening nomogram model to identify individuals at high risk of CRC.
Data of 64448 participants obtained from Ningbo Hospital, China between 2014 and 2017 were retrospectively analyzed. The cohort comprised 64448 individuals, of which, 530 were excluded due to missing or incorrect data. Of 63918, 7607 (11.9%) individuals were considered to be high risk for CRC, and 56311 (88.1%) were not. The participants were randomly allocated to a training set (44743) or validation set (19175). The discriminatory ability, predictive accuracy, and clinical utility of the model were evaluated by constructing and analyzing receiver operating characteristic (ROC) curves and calibration curves and by decision curve analysis. Finally, the model was validated internally using a bootstrap resampling technique.
Seven variables, including demographic, lifestyle, and family history information, were examined. Multifactorial logistic regression analysis revealed that age [odds ratio (OR): 1.03, 95% confidence interval (CI): 1.02-1.03, < 0.001], body mass index (BMI) (OR: 1.07, 95%CI: 1.06-1.08, < 0.001), waist circumference (WC) (OR: 1.03, 95%CI: 1.02-1.03 < 0.001), lifestyle (OR: 0.45, 95%CI: 0.42-0.48, < 0.001), and family history (OR: 4.28, 95%CI: 4.04-4.54, < 0.001) were the most significant predictors of high-risk CRC. Healthy lifestyle was a protective factor, whereas family history was the most significant risk factor. The area under the curve was 0.734 (95%CI: 0.723-0.745) for the final validation set ROC curve and 0.735 (95%CI: 0.728-0.742) for the training set ROC curve. The calibration curve demonstrated a high correlation between the CRC high-risk population predicted by the nomogram model and the actual CRC high-risk population.
The early-screening nomogram model for CRC prediction in high-risk populations developed in this study based on age, BMI, WC, lifestyle, and family history exhibited high accuracy.
结直肠癌（CRC）是全球范围内的严重威胁。尽管早期筛查被认为是预防和控制 CRC 的最有效方法，但 CRC 的早期筛查现状仍不容乐观。在中国，长三角地区 CRC 的发病率正在急剧上升，但相关研究却很少。因此，有必要开发一种简单有效的 CRC 早期筛查模型。
开发和验证一种用于识别 CRC 高危个体的早期筛查列线图模型。
回顾性分析了 2014 年至 2017 年间中国宁波医院的 64448 名参与者的数据。该队列包括 64448 名参与者，其中 530 名因数据缺失或错误而被排除。在 63918 名参与者中，7607 名（11.9%）被认为有 CRC 高危风险，56311 名（88.1%）没有。参与者被随机分配到训练集（44743 人）或验证集（19175 人）。通过构建和分析受试者工作特征（ROC）曲线和校准曲线，以及决策曲线分析，评估了模型的区分能力、预测准确性和临床实用性。最后，使用自举重采样技术对模型进行了内部验证。
共检查了 7 个变量，包括人口统计学、生活方式和家族史信息。多因素逻辑回归分析显示，年龄[比值比（OR）：1.03，95%置信区间（CI）：1.02-1.03，<0.001]、体重指数（BMI）（OR：1.07，95%CI：1.06-1.08，<0.001）、腰围（WC）（OR：1.03，95%CI：1.02-1.03，<0.001）、生活方式（OR：0.45，95%CI：0.42-0.48，<0.001）和家族史（OR：4.28，95%CI：4.04-4.54，<0.001）是 CRC 高危的最显著预测因素。健康的生活方式是保护因素，而家族史是最显著的危险因素。最终验证集 ROC 曲线的曲线下面积为 0.734（95%CI：0.723-0.745），训练集 ROC 曲线的曲线下面积为 0.735（95%CI：0.728-0.742）。校准曲线表明，列线图模型预测的 CRC 高危人群与实际 CRC 高危人群具有高度相关性。
本研究基于年龄、BMI、WC、生活方式和家族史开发的 CRC 高危人群早期筛查列线图模型具有较高的准确性。
