Division of Epidemiology, Human Genetics and Environmental Sciences, Brownsville Regional Campus, The University of Texas School of Public Health, Brownsville, Texas, United States of America.
PLoS One. 2011;6(6):e21041. doi: 10.1371/journal.pone.0021041. Epub 2011 Jun 14.
The lack of standardized reference range for the homeostasis model assessment-estimated insulin resistance (HOMA-IR) index has limited its clinical application. This study defines the reference range of HOMA-IR index in an adult Hispanic population based with machine learning methods.
This study investigated a Hispanic population of 1854 adults, randomly selected on the basis of 2000 Census tract data in the city of Brownsville, Cameron County. Machine learning methods, support vector machine (SVM) and Bayesian Logistic Regression (BLR), were used to automatically identify measureable variables using standardized values that correlate with HOMA-IR; K-means clustering was then used to classify the individuals by insulin resistance.
Our study showed that the best cutoff of HOMA-IR for identifying those with insulin resistance is 3.80. There are 39.1% individuals in this Hispanic population with HOMA-IR>3.80.
Our results are dramatically different using the popular clinical cutoff of 2.60. The high sensitivity and specificity of HOMA-IR>3.80 for insulin resistance provide a critical fundamental for our further efforts to improve the public health of this Hispanic population.
稳态模型评估估算的胰岛素抵抗（HOMA-IR）指数缺乏标准化参考范围，限制了其临床应用。本研究使用机器学习方法定义了基于成年西班牙裔人群的 HOMA-IR 指数的参考范围。
本研究调查了 1854 名成年西班牙裔人群，这些人是根据布朗斯维尔市卡梅伦县 2000 年普查区数据随机选择的。使用支持向量机（SVM）和贝叶斯逻辑回归（BLR）等机器学习方法，自动识别与 HOMA-IR 相关的可测量变量，并使用标准化值进行测量；然后使用 K-均值聚类法根据胰岛素抵抗对个体进行分类。
我们的研究表明，用于识别胰岛素抵抗个体的最佳 HOMA-IR 截断值为 3.80。在这个西班牙裔人群中，有 39.1%的个体的 HOMA-IR>3.80。
使用 2.60 这一流行的临床截断值，我们的结果有很大的不同。HOMA-IR>3.80 对胰岛素抵抗具有较高的灵敏度和特异性，为我们进一步努力改善这一西班牙裔人群的公共卫生状况提供了重要的基础。
