Should insulin resistance (HOMA-IR), insulin secretion (HOMA-β), and visceral fat area be considered for improving the performance of diabetes risk prediction models
Introduction Insulin resistance and defects in pancreatic beta cells are the two major pathophysiologic abnormalities that underlie type 2 diabetes. In addition, visceral fat area (VFA) is reported to be a stronger predictor for diabetes than body mass index (BMI). Here, we tested whether the perfor...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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BMJ Publishing Group
2024-02-01
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| Series: | BMJ Open Diabetes Research & Care |
| Online Access: | https://drc.bmj.com/content/12/1/e003680.full |
| _version_ | 1827572573732339712 |
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| author | Tohru Nakagawa Tetsuya Mizoue Huan Hu Toru Honda Shuichiro Yamamoto |
| author_facet | Tohru Nakagawa Tetsuya Mizoue Huan Hu Toru Honda Shuichiro Yamamoto |
| author_sort | Tohru Nakagawa |
| collection | DOAJ |
| description | Introduction Insulin resistance and defects in pancreatic beta cells are the two major pathophysiologic abnormalities that underlie type 2 diabetes. In addition, visceral fat area (VFA) is reported to be a stronger predictor for diabetes than body mass index (BMI). Here, we tested whether the performance of diabetes prediction models could be improved by adding HOMA-IR and HOMA-β and replacing BMI with VFA.Research design and methods We developed five prediction models using data from a cohort study (5578 individuals, of whom 94.7% were male, and 943 had incident diabetes). We conducted a baseline model (model 1) including age, sex, BMI, smoking, dyslipidemia, hypertension, and HbA1c. Subsequently, we developed another four models: model 2, predictors in model 1 plus fasting plasma glucose (FPG); model 3, predictors in model 1 plus HOMA-IR and HOMA-β; model 4, predictors in model 1 plus FPG, HOMA-IR, and HOMA-β; model 5, replaced BMI with VFA in model 2. We assessed model discrimination and calibration for the first 10 years of follow-up.Results The addition of FPG to model 1 obviously increased the value of the area under the receiver operating characteristic curve from 0.79 (95% CI 0.78, 0.81) to 0.84 (0.83, 0.85). Compared with model 1, model 2 also significantly improved the risk reclassification and discrimination, with a continuous net reclassification improvement index of 0.61 (0.56, 0.70) and an integrated discrimination improvement index of 0.09 (0.08, 0.10). Adding HOMA-IR and HOMA-β (models 3 and 4) or replacing BMI with VFA (model 5) did not further materially improve the performance.Conclusions This cohort study, primarily composed of male workers, suggests that a model with BMI, FPG, and HbA1c effectively identifies those at high diabetes risk. However, adding HOMA-IR, HOMA-β, or replacing BMI with VFA does not significantly improve the model. Further studies are needed to confirm our findings. |
| first_indexed | 2024-03-07T19:05:47Z |
| format | Article |
| id | doaj.art-dea887de70a64372860be1c3c2049327 |
| institution | Directory Open Access Journal |
| issn | 2052-4897 |
| language | English |
| last_indexed | 2024-03-07T19:05:47Z |
| publishDate | 2024-02-01 |
| publisher | BMJ Publishing Group |
| record_format | Article |
| series | BMJ Open Diabetes Research & Care |
| spelling | doaj.art-dea887de70a64372860be1c3c20493272024-03-01T09:25:08ZengBMJ Publishing GroupBMJ Open Diabetes Research & Care2052-48972024-02-0112110.1136/bmjdrc-2023-003680Should insulin resistance (HOMA-IR), insulin secretion (HOMA-β), and visceral fat area be considered for improving the performance of diabetes risk prediction modelsTohru Nakagawa0Tetsuya Mizoue1Huan Hu2Toru Honda3Shuichiro Yamamoto4Hitachi Health Care Center, Hitachi, Ltd, Hitachi, Ibaraki, JapanDepartment of Epidemiology and Prevention, Center for Clinical Sciences, National Center for Global Health and Medicine, Tokyo, JapanResearch Center for Prevention from Radiation Hazards of Workers, National Institute of Occupational Safety and Health, Kawasaki, Kanagawa, JapanHitachi Health Care Center, Hitachi, Ltd, Hitachi, Ibaraki, JapanHitachi Health Care Center, Hitachi, Ltd, Hitachi, Ibaraki, JapanIntroduction Insulin resistance and defects in pancreatic beta cells are the two major pathophysiologic abnormalities that underlie type 2 diabetes. In addition, visceral fat area (VFA) is reported to be a stronger predictor for diabetes than body mass index (BMI). Here, we tested whether the performance of diabetes prediction models could be improved by adding HOMA-IR and HOMA-β and replacing BMI with VFA.Research design and methods We developed five prediction models using data from a cohort study (5578 individuals, of whom 94.7% were male, and 943 had incident diabetes). We conducted a baseline model (model 1) including age, sex, BMI, smoking, dyslipidemia, hypertension, and HbA1c. Subsequently, we developed another four models: model 2, predictors in model 1 plus fasting plasma glucose (FPG); model 3, predictors in model 1 plus HOMA-IR and HOMA-β; model 4, predictors in model 1 plus FPG, HOMA-IR, and HOMA-β; model 5, replaced BMI with VFA in model 2. We assessed model discrimination and calibration for the first 10 years of follow-up.Results The addition of FPG to model 1 obviously increased the value of the area under the receiver operating characteristic curve from 0.79 (95% CI 0.78, 0.81) to 0.84 (0.83, 0.85). Compared with model 1, model 2 also significantly improved the risk reclassification and discrimination, with a continuous net reclassification improvement index of 0.61 (0.56, 0.70) and an integrated discrimination improvement index of 0.09 (0.08, 0.10). Adding HOMA-IR and HOMA-β (models 3 and 4) or replacing BMI with VFA (model 5) did not further materially improve the performance.Conclusions This cohort study, primarily composed of male workers, suggests that a model with BMI, FPG, and HbA1c effectively identifies those at high diabetes risk. However, adding HOMA-IR, HOMA-β, or replacing BMI with VFA does not significantly improve the model. Further studies are needed to confirm our findings.https://drc.bmj.com/content/12/1/e003680.full |
| spellingShingle | Tohru Nakagawa Tetsuya Mizoue Huan Hu Toru Honda Shuichiro Yamamoto Should insulin resistance (HOMA-IR), insulin secretion (HOMA-β), and visceral fat area be considered for improving the performance of diabetes risk prediction models BMJ Open Diabetes Research & Care |
| title | Should insulin resistance (HOMA-IR), insulin secretion (HOMA-β), and visceral fat area be considered for improving the performance of diabetes risk prediction models |
| title_full | Should insulin resistance (HOMA-IR), insulin secretion (HOMA-β), and visceral fat area be considered for improving the performance of diabetes risk prediction models |
| title_fullStr | Should insulin resistance (HOMA-IR), insulin secretion (HOMA-β), and visceral fat area be considered for improving the performance of diabetes risk prediction models |
| title_full_unstemmed | Should insulin resistance (HOMA-IR), insulin secretion (HOMA-β), and visceral fat area be considered for improving the performance of diabetes risk prediction models |
| title_short | Should insulin resistance (HOMA-IR), insulin secretion (HOMA-β), and visceral fat area be considered for improving the performance of diabetes risk prediction models |
| title_sort | should insulin resistance homa ir insulin secretion homa β and visceral fat area be considered for improving the performance of diabetes risk prediction models |
| url | https://drc.bmj.com/content/12/1/e003680.full |
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