Development of Risk Score for Predicting 3-Year Incidence of Type 2 Diabetes: Japan Epidemiology Collaboration on Occupational Health Study.
Development of Risk Score for Predicting 3-Year Incidence of Type 2 Diabetes: Japan Epidemiology Collaboration on Occupational Health Study.
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DOI：
10.1371/journal.pone.0142779
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发表时间：
2015
期刊：
影响因子：
3.7
通讯作者：
Japan Epidemiology Collaboration on Occupational Health Study Group
中科院分区：
文献类型：
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作者：
Nanri A;Nakagawa T;Kuwahara K;Yamamoto S;Honda T;Okazaki H;Uehara A;Yamamoto M;Miyamoto T;Kochi T;Eguchi M;Murakami T;Shimizu C;Shimizu M;Tomita K;Nagahama S;Imai T;Nishihara A;Sasaki N;Hori A;Sakamoto N;Nishiura C;Totsuzaki T;Kato N;Fukasawa K;Huanhuan H;Akter S;Kurotani K;Kabe I;Mizoue T;Sone T;Dohi S;Japan Epidemiology Collaboration on Occupational Health Study Group
已经开发了风险模型和评分来预测西方人群中2型糖尿病的发病率，但当应用于非西方人群时，它们的表现可能不同。我们开发并验证了用于预测日本人群中3年内2型糖尿病发病率的风险评分。参与者为37416名年龄在30岁或以上的男性和女性，他们在2008-2009年间在8家公司接受了定期健康检查。糖尿病定义为空腹血糖≥12 6 mg/dl，随机血糖≥2 0 0 mg/dl，糖化血红蛋白≥6.5%，或因糖尿病接受内科治疗。对包括空腹血糖和糖化血红蛋白在内的非侵入性和侵入性模型的风险评分在派生队列中使用Logistic回归进行计算，并在其余队列中进行验证。包括年龄、性别、体重指数、腰围、高血压和吸烟状况在内的无创模型的曲线下面积为0.717(95%CI，0.703-0.731)。在非侵入性模型中同时加入空腹血糖和糖化血红蛋白的侵入性模型中，AUC增加到0.893(95%CI，0.883-0.902)。将风险评分应用于验证队列时，无创和有创模型的AUC(95%CI)分别为0.734(0.715-0.753)和0.882(0.868-0.895)。非侵袭性评分为≥15和侵袭性评分为≥19的参与者预计在3年内患2型糖尿病的风险分别为20%和50%。非侵入性模型的简单风险评分可能有助于预测2型糖尿病的发生，结合空腹血糖和糖化血红蛋白可以显著改善其预测性能。
Risk models and scores have been developed to predict incidence of type 2 diabetes in Western populations, but their performance may differ when applied to non-Western populations. We developed and validated a risk score for predicting 3-year incidence of type 2 diabetes in a Japanese population. Participants were 37,416 men and women, aged 30 or older, who received periodic health checkup in 2008–2009 in eight companies. Diabetes was defined as fasting plasma glucose (FPG) ≥126 mg/dl, random plasma glucose ≥200 mg/dl, glycated hemoglobin (HbA1c) ≥6.5%, or receiving medical treatment for diabetes. Risk scores on non-invasive and invasive models including FPG and HbA1c were developed using logistic regression in a derivation cohort and validated in the remaining cohort. The area under the curve (AUC) for the non-invasive model including age, sex, body mass index, waist circumference, hypertension, and smoking status was 0.717 (95% CI, 0.703–0.731). In the invasive model in which both FPG and HbA1c were added to the non-invasive model, AUC was increased to 0.893 (95% CI, 0.883–0.902). When the risk scores were applied to the validation cohort, AUCs (95% CI) for the non-invasive and invasive model were 0.734 (0.715–0.753) and 0.882 (0.868–0.895), respectively. Participants with a non-invasive score of ≥15 and invasive score of ≥19 were projected to have >20% and >50% risk, respectively, of developing type 2 diabetes within 3 years. The simple risk score of the non-invasive model might be useful for predicting incident type 2 diabetes, and its predictive performance may be markedly improved by incorporating FPG and HbA1c.