Development and Validation of Prediction Models for the 5-year Risk of Type 2 Diabetes in a Japanese Population: Japan Public Health Center-based Prospective (JPHC) Diabetes Study
Background: This study aimed to develop models to predict the 5-year incidence of type 2 diabetes mellitus (T2DM) in a Japanese population and validate them externally in an independent Japanese population. Methods: Data from 10,986 participants (aged 46–75 years) in the development cohort of the Ja...
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| Format: | Article |
| Language: | English |
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Japan Epidemiological Association
2024-04-01
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| Series: | Journal of Epidemiology |
| Subjects: | |
| Online Access: | https://www.jstage.jst.go.jp/article/jea/34/4/34_JE20220329/_pdf |
| _version_ | 1797221266238734336 |
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| author | Juan Xu Atsushi Goto Maki Konishi Masayuki Kato Tetsuya Mizoue Yasuo Terauchi Shoichiro Tsugane Norie Sawada Mitsuhiko Noda |
| author_facet | Juan Xu Atsushi Goto Maki Konishi Masayuki Kato Tetsuya Mizoue Yasuo Terauchi Shoichiro Tsugane Norie Sawada Mitsuhiko Noda |
| author_sort | Juan Xu |
| collection | DOAJ |
| description | Background: This study aimed to develop models to predict the 5-year incidence of type 2 diabetes mellitus (T2DM) in a Japanese population and validate them externally in an independent Japanese population. Methods: Data from 10,986 participants (aged 46–75 years) in the development cohort of the Japan Public Health Center-based Prospective Diabetes Study and 11,345 participants (aged 46–75 years) in the validation cohort of the Japan Epidemiology Collaboration on Occupational Health Study were used to develop and validate the risk scores in logistic regression models. Results: We considered non-invasive (sex, body mass index, family history of diabetes mellitus, and diastolic blood pressure) and invasive (glycated hemoglobin [HbA1c] and fasting plasma glucose [FPG]) predictors to predict the 5-year probability of incident diabetes. The area under the receiver operating characteristic curve was 0.643 for the non-invasive risk model, 0.786 for the invasive risk model with HbA1c but not FPG, and 0.845 for the invasive risk model with HbA1c and FPG. The optimism for the performance of all models was small by internal validation. In the internal-external cross-validation, these models tended to show similar discriminative ability across different areas. The discriminative ability of each model was confirmed using external validation datasets. The invasive risk model with only HbA1c was well-calibrated in the validation cohort. Conclusion: Our invasive risk models are expected to discriminate between high- and low-risk individuals with T2DM in a Japanese population. |
| first_indexed | 2024-04-24T13:02:42Z |
| format | Article |
| id | doaj.art-39a3d60e9c574f49877db46a2491d8f8 |
| institution | Directory Open Access Journal |
| issn | 0917-5040 1349-9092 |
| language | English |
| last_indexed | 2024-04-24T13:02:42Z |
| publishDate | 2024-04-01 |
| publisher | Japan Epidemiological Association |
| record_format | Article |
| series | Journal of Epidemiology |
| spelling | doaj.art-39a3d60e9c574f49877db46a2491d8f82024-04-05T10:03:41ZengJapan Epidemiological AssociationJournal of Epidemiology0917-50401349-90922024-04-0134417017910.2188/jea.JE20220329Development and Validation of Prediction Models for the 5-year Risk of Type 2 Diabetes in a Japanese Population: Japan Public Health Center-based Prospective (JPHC) Diabetes StudyJuan Xu0Atsushi Goto1Maki Konishi2Masayuki Kato3Tetsuya Mizoue4Yasuo Terauchi5Shoichiro Tsugane6Norie Sawada7Mitsuhiko Noda8Department of Endocrinology and Metabolism, Graduate School of Medicine, Yokohama City University, Yokohama, JapanDepartment of Health Data Science, Graduate School of Data Science, Yokohama City University, Yokohama, JapanDepartment of Epidemiology and Prevention, Center for Clinical Sciences, National Center for Global Health and Medicine, Tokyo, JapanHealth Management Center and Diagnostic Imaging Center, Toranomon Hospital, Tokyo, JapanDepartment of Epidemiology and Prevention, Center for Clinical Sciences, National Center for Global Health and Medicine, Tokyo, JapanDepartment of Endocrinology and Metabolism, Graduate School of Medicine, Yokohama City University, Yokohama, JapanDivision of Cohort Research, National Cancer Center Institute for Cancer Control, Tokyo, JapanDivision of Cohort Research, National Cancer Center Institute for Cancer Control, Tokyo, JapanDepartment of Diabetes, Metabolism and Endocrinology, Ichikawa Hospital, International University of Health and Welfare, Chiba, JapanBackground: This study aimed to develop models to predict the 5-year incidence of type 2 diabetes mellitus (T2DM) in a Japanese population and validate them externally in an independent Japanese population. Methods: Data from 10,986 participants (aged 46–75 years) in the development cohort of the Japan Public Health Center-based Prospective Diabetes Study and 11,345 participants (aged 46–75 years) in the validation cohort of the Japan Epidemiology Collaboration on Occupational Health Study were used to develop and validate the risk scores in logistic regression models. Results: We considered non-invasive (sex, body mass index, family history of diabetes mellitus, and diastolic blood pressure) and invasive (glycated hemoglobin [HbA1c] and fasting plasma glucose [FPG]) predictors to predict the 5-year probability of incident diabetes. The area under the receiver operating characteristic curve was 0.643 for the non-invasive risk model, 0.786 for the invasive risk model with HbA1c but not FPG, and 0.845 for the invasive risk model with HbA1c and FPG. The optimism for the performance of all models was small by internal validation. In the internal-external cross-validation, these models tended to show similar discriminative ability across different areas. The discriminative ability of each model was confirmed using external validation datasets. The invasive risk model with only HbA1c was well-calibrated in the validation cohort. Conclusion: Our invasive risk models are expected to discriminate between high- and low-risk individuals with T2DM in a Japanese population.https://www.jstage.jst.go.jp/article/jea/34/4/34_JE20220329/_pdfdiabetesrisk scoreprediction modeljapanese populationjapan public health center-based prospective (jphc) study |
| spellingShingle | Juan Xu Atsushi Goto Maki Konishi Masayuki Kato Tetsuya Mizoue Yasuo Terauchi Shoichiro Tsugane Norie Sawada Mitsuhiko Noda Development and Validation of Prediction Models for the 5-year Risk of Type 2 Diabetes in a Japanese Population: Japan Public Health Center-based Prospective (JPHC) Diabetes Study Journal of Epidemiology diabetes risk score prediction model japanese population japan public health center-based prospective (jphc) study |
| title | Development and Validation of Prediction Models for the 5-year Risk of Type 2 Diabetes in a Japanese Population: Japan Public Health Center-based Prospective (JPHC) Diabetes Study |
| title_full | Development and Validation of Prediction Models for the 5-year Risk of Type 2 Diabetes in a Japanese Population: Japan Public Health Center-based Prospective (JPHC) Diabetes Study |
| title_fullStr | Development and Validation of Prediction Models for the 5-year Risk of Type 2 Diabetes in a Japanese Population: Japan Public Health Center-based Prospective (JPHC) Diabetes Study |
| title_full_unstemmed | Development and Validation of Prediction Models for the 5-year Risk of Type 2 Diabetes in a Japanese Population: Japan Public Health Center-based Prospective (JPHC) Diabetes Study |
| title_short | Development and Validation of Prediction Models for the 5-year Risk of Type 2 Diabetes in a Japanese Population: Japan Public Health Center-based Prospective (JPHC) Diabetes Study |
| title_sort | development and validation of prediction models for the 5 year risk of type 2 diabetes in a japanese population japan public health center based prospective jphc diabetes study |
| topic | diabetes risk score prediction model japanese population japan public health center-based prospective (jphc) study |
| url | https://www.jstage.jst.go.jp/article/jea/34/4/34_JE20220329/_pdf |
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