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基于人口统计学和临床风险因素的风险评分可预测美国人群的胃肠化生风险。

Risk Score Using Demographic and Clinical Risk Factors Predicts Gastric Intestinal Metaplasia Risk in a U.S. Population.

机构信息

Section of Gastroenterology and Hepatology, Department of Medicine, Baylor College of Medicine, One Baylor Plaza, MS: BCM 285, Houston, TX, 77030-3498, USA.

Texas Tech University, Lubbock, TX, USA.

出版信息

Dig Dis Sci. 2022 Sep;67(9):4500-4508. doi: 10.1007/s10620-021-07309-3. Epub 2021 Nov 19.

Abstract

BACKGROUND/AIMS: Screening for gastric intestinal metaplasia (GIM) may lead to early gastric cancer detection. We developed and validated a pre-endoscopy risk prediction model for detection of GIM based on patient-level risk factors in a U.S.

METHODS

We used data from 423 GIM cases and 1796 controls from a cross-sectional study among primary care and endoscopy clinic patients at the Houston VA. We developed the model using backwards stepwise regression and assessed discrimination using area under the receiver operating characteristic (AUROC). The model was internally validated using cross-validation and bootstrapping. The final expanded model was compared to a model including H. pylori infection alone and a baseline model including remaining terms without H. pylori.

RESULTS

Male sex, older age, non-white race/ethnicity, smoking status, and H. pylori were associated with GIM risk. The expanded model including these terms had AUROC 0.73 (95%CI 0.71-0.76) for predicting GIM and AUROC 0.82 (95%CI 0.79-0.86) for extensive GIM. This model discriminated better than a model including only H. pylori (AUROC 0.66; 95%CI 0.63-0.68) and the baseline model (AUROC 0.67; 95%CI 0.64-0.70). The expanded model performed similarly among primary care (AUROC 0.75) and endoscopy (AUROC 0.73) patients. The expanded model showed sufficient internal validity (cross-validation AUROC 0.72) with little evidence of over-fitting.

CONCLUSIONS

We develop and validate a non-invasive risk model for GIM detection in a U.S. population that included terms for sex, age, race/ethnicity, smoking status, and H. pylori infection. Validated risk models would identify individuals with GIM who should be referred for endoscopic screening.

摘要

背景/目的:筛查胃肠化生(GIM)可能会导致早期胃癌的检出。我们在美国的一项初级保健和内镜诊所患者的横断面研究中,基于患者水平的危险因素,开发并验证了一种用于检测 GIM 的内镜前风险预测模型。

方法

我们使用了来自休斯顿退伍军人事务部 423 例 GIM 病例和 1796 例对照的资料。我们使用向后逐步回归法建立了该模型,并使用接收者操作特征曲线下的面积(AUROC)来评估其区分能力。使用交叉验证和引导法对内部分别验证了该模型。最后,将扩展后的模型与仅包含 H. pylori 感染的模型以及包含无 H. pylori 的其余术语的基线模型进行了比较。

结果

男性、年龄较大、非白种人/族裔、吸烟状况和 H. pylori 与 GIM 风险相关。包含这些术语的扩展模型用于预测 GIM 的 AUROC 为 0.73(95%CI 0.71-0.76),用于预测广泛 GIM 的 AUROC 为 0.82(95%CI 0.79-0.86)。该模型比仅包含 H. pylori(AUROC 0.66;95%CI 0.63-0.68)和基线模型(AUROC 0.67;95%CI 0.64-0.70)的模型具有更好的区分能力。该扩展模型在初级保健(AUROC 0.75)和内镜(AUROC 0.73)患者中表现相似。扩展模型具有足够的内部有效性(交叉验证 AUROC 0.72),几乎没有过度拟合的证据。

结论

我们在美国人群中开发并验证了一种用于 GIM 检测的非侵入性风险模型,该模型包含性别、年龄、种族/族裔、吸烟状况和 H. pylori 感染等术语。验证后的风险模型将确定应转介进行内镜筛查的 GIM 患者。

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