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肝功能检查与 2 型糖尿病发病风险预测:两项独立队列研究评估

Liver function tests and risk prediction of incident type 2 diabetes: evaluation in two independent cohorts.

机构信息

Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.

出版信息

PLoS One. 2012;7(12):e51496. doi: 10.1371/journal.pone.0051496. Epub 2012 Dec 17.

Abstract

BACKGROUND

Liver function tests might predict the risk of type 2 diabetes. An independent study evaluating utility of these markers compared with an existing prediction model is yet lacking.

METHODS AND FINDINGS

We performed a case-cohort study, including random subcohort (6.5%) from 38,379 participants with 924 incident diabetes cases (the Dutch contribution to the European Prospective Investigation Into Cancer and Nutrition, EPIC-NL, the Netherlands), and another population-based cohort study including 7,952 participants with 503 incident cases (the Prevention of Renal and Vascular End-stage Disease, PREVEND, Groningen, the Netherlands). We examined predictive value of combination of the Liver function tests (gamma-glutamyltransferase, alanine aminotransferase, aspartate aminotransferase and albumin) above validated models for 7.5-year risk of diabetes (the Cooperative Health Research in the Region of Augsburg, the KORA study). Basic model includes age, sex, BMI, smoking, hypertension and parental diabetes. Clinical models additionally include glucose and uric acid (model1) and HbA1c (model2). In both studies, addition of Liver function tests to the basic model improved the prediction (C-statistic by0.020; NRI by9.0%; P<0.001). In the EPIC-NL case-cohort study, addition to clinical model1 resulted in statistically significant improvement in the overall population (C-statistic = +0.009; P<0.001; NRI = 8.8%; P<0.001), while addition to clinical model 2 yielded marginal improvement limited to men (C-statistic = +0.007; P = 0.06; NRI = 3.3%; P = 0.04). In the PREVEND cohort study, addition to clinical model 1 resulted in significant improvement in the overall population (C-statistic change = 0.008; P = 0.003; NRI = 3.6%; P = 0.03), with largest improvement in men (C-statistic change = 0.013; P = 0.01; NRI = 5.4%; P = 0.04). In PREVEND, improvement compared to clinical model 2 could not be tested because of lack of HbA1c data.

CONCLUSIONS

Liver function tests modestly improve prediction for medium-term risk of incident diabetes above basic and extended clinical prediction models, only if no HbA1c is incorporated. If data on HbA1c are available, Liver function tests have little incremental predictive value, although a small benefit may be present in men.

摘要

背景

肝功能检测结果可能可以预测 2 型糖尿病的发病风险。目前还缺乏独立研究来评估这些标志物的实用性与现有预测模型相比。

方法和发现

我们进行了病例-队列研究,队列部分(6.5%)包括来自 38379 名参与者的随机子队列,其中有 924 名糖尿病患者(荷兰对欧洲癌症前瞻性调查和营养研究的贡献,EPIC-NL,荷兰),另一项基于人群的队列研究包括 7952 名参与者,其中有 503 名糖尿病患者(预防肾脏和血管终末期疾病,PREVEND,格罗宁根,荷兰)。我们评估了联合使用(γ-谷氨酰转移酶、丙氨酸氨基转移酶、天冬氨酸氨基转移酶和白蛋白)肝脏功能检测的预测价值,这些检测结果高于针对 7.5 年糖尿病风险的验证模型(奥格斯堡合作健康研究,KORA 研究)。基础模型包括年龄、性别、BMI、吸烟、高血压和父母糖尿病史。临床模型另外还包括葡萄糖和尿酸(模型 1)和糖化血红蛋白(模型 2)。在这两项研究中,将肝功能检测结果加入基本模型可以提高预测能力(C 统计量增加约 0.020;NRI 增加约 9.0%;P<0.001)。在 EPIC-NL 病例-队列研究中,联合临床模型 1 的检测结果可以显著提高总体人群的预测效果(C 统计量增加 0.009;P<0.001;NRI 增加 8.8%;P<0.001),而联合临床模型 2 的检测结果仅在男性中可以达到统计学意义上的改善(C 统计量增加 0.007;P=0.06;NRI 增加 3.3%;P=0.04)。在 PREVEND 队列研究中,联合临床模型 1 可以显著提高整体人群的预测效果(C 统计量增加 0.008;P=0.003;NRI 增加 3.6%;P=0.03),男性的改善效果最大(C 统计量增加 0.013;P=0.01;NRI 增加 5.4%;P=0.04)。在 PREVEND 研究中,由于缺乏糖化血红蛋白数据,无法对联合临床模型 2 的检测结果进行检验。

结论

如果没有糖化血红蛋白数据,肝功能检测结果可以适度提高基本和扩展临床预测模型对中期糖尿病发病风险的预测能力。如果有糖化血红蛋白数据,则肝功能检测结果几乎没有额外的预测价值,但男性可能会有一定的获益。

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