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Risk prediction rule for advanced neoplasia on screening colonoscopy for average-risk individuals

机译:高级肿瘤筛查结肠镜检查平均风险个体的风险预测规则

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BACKGROUND In resource-limited countries, risk stratification can be used to optimize colorectal cancer screening. Few prospective risk prediction models exist for advanced neoplasia (AN) in true average-risk individuals. AIM To create and internally validate a risk prediction model for detection of AN in average-risk individuals. METHODS Prospective study of asymptomatic individuals undergoing first screening colonoscopy. Detailed characteristics including diet, exercise and medications were collected. Multivariate logistic regression was used to elucidate risk factors for AN (adenoma ≥1 cm, villous histology, high-grade dysplasia or carcinoma). The model was validated through bootstrapping, and discrimination and calibration of the model were assessed. RESULTS 980 consecutive individuals (51% F; 49% M) were enrolled. Adenoma and AN detection rates were 36.6% (F 29%: M 45%; P 0.001) and 5.1% (F 3.8%; M 6.5%) respectively. On multivariate analysis, predictors of AN [OR (95%CI)] were age [1.036 (1.00-1.07); P = 0.048], BMI [overweight 2.21 (0.98-5.00); obese 3.54 (1.48-8.50); P = 0.018], smoking [ 40 pack-years 2.01 (1.01-4.01); ≥ 40 pack-years 3.96 (1.86-8.42); P = 0.002], and daily red meat consumption [2.02 (0.92-4.42) P = 0.079]. Nomograms of AN risk were developed in terms of risk factors and age separately for normal, overweight and obese individuals. The model had good discrimination and calibration. CONCLUSION The prevalence of adenoma and AN in average-risk Lebanese individuals is similar to the West. Age, smoking, and BMI are important predictors of AN, with obesity being particularly powerful. Though external validation is needed, this model provides an important platform for improved risk-stratification for screening programs in regions where universal screening is not currently employed.
机译:背景技术在资源有限的国家,风险分层可用于优化结肠直肠癌筛选。在真正的平均风险中的晚期肿瘤(AN)存在很少的前瞻性风险预测模型。旨在创建和内部验证风险预测模型,以检测平均风险的个体。方法对筛选结肠镜检查的无症状个体的前瞻性研究。收集了详细的特征,包括饮食,运动和药物。多变量逻辑回归用于阐明(腺瘤≥1厘米,绒毛组织学,高级发育不良或癌)的危险因素。该模型通过自动启动验证,评估模型的歧视和校准。结果980连续个人(51%F; 49%M)注册。腺瘤和检测率分别为36.6%(F 29%:m 45%; p <0.001)和5.1%(F 3.8%; m 6.5%)。在多变量分析上,[或(95%CI)的预测因子是年龄[1.036(1.00-1.07); P = 0.048],BMI [超重2.21(0.98-5.00);肥胖3.54(1.48-8.50); P = 0.018]吸烟[<40包 - 年2.01(1.01-4.01); ≥40包 - 年3.96(1.86-8.42); P = 0.002],每日红肉消耗[2.02(0.92-4.42)P = 0.079]。风险的载体是在危险因素和年龄分别进行正常,超重和肥胖的人方面开发的。该模型具有良好的歧视和校准。结论腺瘤的患病率和平均风险的黎巴嫩个人类似于西方。年龄,吸烟和BMI是一个重要的预测因子,肥胖尤为强大。尽管需要外部验证,但该模型提供了一种重要的平台,用于改善当前未采用通用筛选的区域中的筛选节目的风险分层。

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