A clinical risk prediction model for Barrett esophagus.
A clinical risk prediction model for Barrett esophagus.
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DOI：
10.1158/1940-6207.capr-12-0010
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发表时间：
2012-09
期刊：
影响因子：
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通讯作者：
Study of Digestive Health
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文献类型：
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作者：
Thrift AP;Kendall BJ;Pandeya N;Vaughan TL;Whiteman DC;Study of Digestive Health
巴雷特食管（BE）是唯一已知的食管腺癌的前兆。由于明确诊断需要昂贵的内窥镜检查，我们试图建立一个风险预测模型，以帮助决定哪些有胃食管反流（GER）症状的患者需要进行内窥镜筛查。该研究纳入了来自非发育不良BE患者（n=285）和内镜检查控制的食管炎症改变无BE患者（“炎症对照组”，n=313）的数据。我们使用了两个阶段的逐步反向逻辑回归来分别确定男性和女性BE的重要预测因素：首先包括来自单变量分析的所有重要协变量；然后从单变量分析中拟合非显著协变量，以确定只有在调整其他因素后才能检测到的影响。最终的模型汇集了这些预测因子，并使用来自美国华盛顿州西部进行的一项BE研究的数据进行了外部识别和校准验证。最终的风险模型包括年龄、性别、吸烟状况、体重指数、最高教育水平和使用抑酸药物的频率（ROC曲线下面积0.70,95%CI 0.66-0.74）。该模型对外部数据集具有中等判别性（ROC曲线下面积0.61,95%CI 0.56 ~ 0.66）。模型校正良好（Hosmer-Lemeshow检验，p=0.75），预测概率与观察风险高度相关。该预测模型表现相当好，有潜力成为一种有效和有用的临床工具，用于选择有GER症状的患者进行内镜筛查。
Barrett’s esophagus (BE) is the only known precursor to esophageal adenocarcinoma. As definitive diagnosis requires costly endoscopic investigation, we sought to develop a risk prediction model to aid in deciding which patients with gastroesophageal reflux (GER) symptoms to refer for endoscopic screening for BE. The study included data from patients with incident nondysplastic BE (n=285) and endoscopy control patients with esophageal inflammatory changes without BE (“inflammation controls”, n=313). We used two phases of stepwise backwards logistic regression to identify the important predictors for BE in men and women separately: firstly including all significant covariates from univariate analyses; then fitting non-significant covariates from univariate analyses to identify those effects detectable only after adjusting for other factors. The final model pooled these predictors and was externally validated for discrimination and calibration using data from a BE study conducted in western Washington State, USA. The final risk model included terms for age, sex, smoking status, body mass index, highest level of education, and frequency of use of acid suppressant medications (area under the ROC curve, 0.70, 95%CI 0.66–0.74). The model had moderate discrimination in the external dataset (area under the ROC curve, 0.61, 95%CI 0.56–0.66). The model was well calibrated (Hosmer-Lemeshow test, p=0.75), with predicted probability and observed risk highly correlated. The prediction model performed reasonably well and has the potential to be an effective and useful clinical tool in selecting patients with GER symptoms to refer for endoscopic screening for BE.