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Development and validation of risk models to predict the 7-year risk of type 2 diabetes: The Japan Epidemiology Collaboration on Occupational Health Study.

ABSTRACT: AIMS/INTRODUCTION:We previously developed a 3-year diabetes risk score in the working population. The objective of the present study was to develop and validate flexible risk models that can predict the risk of diabetes for any arbitrary time-point during 7 years. MATERIALS AND METHODS:The participants were 46,198 Japanese employees aged 30-59 years, without diabetes at baseline and with a maximum follow-up period of 8 years. Incident diabetes was defined according to the American Diabetes Association criteria. With routine health checkup data (age, sex, abdominal obesity, body mass index, smoking status, hypertension status, dyslipidemia, glycated hemoglobin and fasting plasma glucose), we developed non-invasive and invasive risk models based on the Cox proportional hazards regression model among a random two-thirds of the participants, and used another one-third for validation. RESULTS:The range of the area under the receiver operating characteristic curve increased from 0.73 (95% confidence interval 0.72-0.74) for the non-invasive prediction model to 0.89 (95% confidence interval 0.89-0.90) for the invasive prediction model containing dyslipidemia, glycated hemoglobin and fasting plasma glucose. The invasive models showed improved integrated discrimination and reclassification performance, as compared with the non-invasive model. Calibration appeared good between the predicted and observed risks. These models performed well in the validation cohort. CONCLUSIONS:The present non-invasive and invasive models for the prediction of diabetes risk up to 7 years showed fair and excellent performance, respectively. The invasive models can be used to identify high-risk individuals, who would benefit greatly from lifestyle modification for the prevention or delay of diabetes.

SUBMITTER: Hu H

PROVIDER: S-EPMC6123034 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature

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Development and validation of risk models to predict the 7-year risk of type 2 diabetes: The Japan Epidemiology Collaboration on Occupational Health Study.

Hu Huanhuan H Nakagawa Tohru T Yamamoto Shuichiro S Honda Toru T Okazaki Hiroko H Uehara Akihiko A Yamamoto Makoto M Miyamoto Toshiaki T Kochi Takeshi T Eguchi Masafumi M Murakami Taizo T Shimizu Makiko M Tomita Kentaro K Nagahama Satsue S Imai Teppei T Nishihara Akiko A Sasaki Naoko N Ogasawara Takayuki T Hori Ai A Nanri Akiko A Akter Shamima S Kuwahara Keisuke K Kashino Ikuko I Kabe Isamu I Mizoue Tetsuya T Sone Tomofumi T Dohi Seitaro S

Journal of diabetes investigation 20180306 5

<h4>Aims/introduction</h4>We previously developed a 3-year diabetes risk score in the working population. The objective of the present study was to develop and validate flexible risk models that can predict the risk of diabetes for any arbitrary time-point during 7 years.<h4>Materials and methods</h4>The participants were 46,198 Japanese employees aged 30-59 years, without diabetes at baseline and with a maximum follow-up period of 8 years. Incident diabetes was defined according to the American ...[more]

PMID: 29380553

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Project description:AimsThe control of blood glucose levels, blood pressure (BP), and low-density lipoprotein cholesterol (LDL-C) levels reduces the risk of diabetes complications; however, data are scarce on control status of these factors among workers with diabetes. The present study aimed to estimate the prevalence of participants with diabetes who meet glycated hemoglobin (HbA1c), BP, and LDL-C recommendations, and to investigate correlates of poor glycemic control in a large working population in Japan.MethodsThe Japan Epidemiology Collaboration on Occupational Health (J-ECOH) Study is an ongoing cohort investigation, consisting mainly of employees in large manufacturing companies. We conducted a cross-sectional analysis of 3,070 employees with diabetes (2,854 men and 216 women) aged 20-69 years who attended periodic health examinations. BP was measured and recorded using different company protocols. Risk factor targets were defined using both American Diabetes Association (ADA) guidelines (HbA1c < 7.0%, BP < 140/90 mmHg, and LDL-C < 100 mg/dL) and Japan Diabetes Society (JDS) guidelines (HbA1c < 7.0%, BP < 130/80 mmHg, and LDL-C < 120 mg/dL). Logistic regression models were used to explore correlates of poor glycemic control (defined as HbA1c ? 8.0%).ResultsThe percentages of participants who met ADA (and JDS) targets were 44.9% (44.9%) for HbA1c, 76.6% (36.3%) for BP, 27.1% (56.2%) for LDL-C, and 11.2% (10.8%) for simultaneous control of all three risk factors. Younger age, obesity, smoking, and uncontrolled dyslipidemia were associated with poor glycemic control. The adjusted odds ratio of poor glycemic control was 0.58 (95% confidence interval, 0.46-0.73) for participants with treated but uncontrolled hypertension, and 0.47 (0.33-0.66) for participants with treated and controlled hypertension, as compared with participants without hypertension. There was no significant difference in HbA1c levels between participants with treated but uncontrolled hypertension and those with treated and controlled hypertension.ConclusionData from a large working population, predominantly composed of men, suggest that achievement of HbA1c, BP, and LDL-C targets was less than optimal, especially in younger participants. Uncontrolled dyslipidemia was associated with poor glycemic control. Participants not receiving antihypertensive treatment had higher HbA1c levels.

Project description:AimTo develop a personalized nomogram and risk score to predict the 5-year risk of diabetes among Chinese adults with prediabetes.MethodsThere were 26 018 participants with prediabetes at baseline in this retrospective cohort study. We randomly stratified participants into two cohorts for training (n = 12 947) and validation (n = 13 071). The least absolute shrinkage and selection operator (LASSO) model was applied to select the most significant variables among candidate variables. And we further established a stepwise Cox proportional hazards model to screen out the risk factors based on the predictors chosen by the LASSO model. We presented the model with a nomogram. The model's discrimination, clinical use and calibration were assessed using the area under the receiver operating characteristic (ROC) curve, decision curve and calibration analysis. The associated risk factors were also categorized according to clinical cut-points or tertials to create the diabetes risk score model. Based on the total score, we divided it into four risk categories: low, middle, high and extremely high. We also evaluated our diabetes risk score model's performance.ResultsWe developed a simple nomogram and risk score that predicts the risk of prediabetes by using the variables age, triglyceride, fasting blood glucose, body mass index, alanine aminotransferase, high-density lipoprotein cholesterol and family history of diabetes. The area under the ROC curve of the nomogram was 0.8146 (95% CI 0.8035-0.8258) and 0.8147 (95% CI 0.8035-0.8259) for the training and validation cohort, respectively. The calibration curve showed a perfect fit between predicted and observed diabetes risks at 5 years. Decision curve analysis presented the clinical use of the nomogram, and there was a wide range of alternative threshold probability spectrums. A total risk score of 0 to 2.5, 3 to 4.5, 5 to 7.5 and 8 to 13.5 is associated with low, middle, high and extremely high diabetes risk status, respectively.ConclusionsWe developed and validated a personalized prediction nomogram and risk score for 5-year diabetes risk among Chinese adults with prediabetes, identifying individuals at a high risk of developing diabetes. Doctors and other healthcare professionals can easily and quickly use our diabetes score model to assess the diabetes risk status in patients with prediabetes. In addition, the nomogram model and risk score we developed need to be validated in a prospective cohort study.

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Development and validation of risk models to predict the 7-year risk of type 2 diabetes: The Japan Epidemiology Collaboration on Occupational Health Study.

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Development and validation of risk models to predict the 7-year risk of type 2 diabetes: The Japan Epidemiology Collaboration on Occupational Health Study.

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