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A Risk Score with Additional Four Independent Factors to Predict the Incidence and Recovery from Metabolic Syndrome: Development and Validation in Large Japanese Cohorts
BACKGROUND: Although many risk factors for Metabolic syndrome (MetS) have been reported, there is no clinical score that predicts its incidence. The purposes of this study were to create and validate a risk score for predicting both incidence and recovery from MetS in a large cohort. METHODS: Subjec...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4521863/ https://www.ncbi.nlm.nih.gov/pubmed/26230621 http://dx.doi.org/10.1371/journal.pone.0133884 |
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author | Obokata, Masaru Negishi, Kazuaki Ohyama, Yoshiaki Okada, Haruka Imai, Kunihiko Kurabayashi, Masahiko |
author_facet | Obokata, Masaru Negishi, Kazuaki Ohyama, Yoshiaki Okada, Haruka Imai, Kunihiko Kurabayashi, Masahiko |
author_sort | Obokata, Masaru |
collection | PubMed |
description | BACKGROUND: Although many risk factors for Metabolic syndrome (MetS) have been reported, there is no clinical score that predicts its incidence. The purposes of this study were to create and validate a risk score for predicting both incidence and recovery from MetS in a large cohort. METHODS: Subjects without MetS at enrollment (n = 13,634) were randomly divided into 2 groups and followed to record incidence of MetS. We also examined recovery from it in rest 2,743 individuals with prevalent MetS. RESULTS: During median follow-up of 3.0 years, 878 subjects in the derivation and 757 in validation cohorts developed MetS. Multiple logistic regression analysis identified 12 independent variables from the derivation cohort and initial score for subsequent MetS was created, which showed good discrimination both in the derivation (c-statistics 0.82) and validation cohorts (0.83). The predictability of the initial score for recovery from MetS was tested in the 2,743 MetS population (906 subjects recovered from MetS), where nine variables (including age, sex, γ-glutamyl transpeptidase, uric acid and five MetS diagnostic criteria constituents.) remained significant. Then, the final score was created using the nine variables. This score significantly predicted both the recovery from MetS (c-statistics 0.70, p<0.001, 78% sensitivity and 54% specificity) and incident MetS (c-statistics 0.80) with an incremental discriminative ability over the model derived from five factors used in the diagnosis of MetS (continuous net reclassification improvement: 0.35, p < 0.001 and integrated discrimination improvement: 0.01, p<0.001). CONCLUSIONS: We identified four additional independent risk factors associated with subsequent MetS, developed and validated a risk score to predict both incident and recovery from MetS. |
format | Online Article Text |
id | pubmed-4521863 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-45218632015-08-06 A Risk Score with Additional Four Independent Factors to Predict the Incidence and Recovery from Metabolic Syndrome: Development and Validation in Large Japanese Cohorts Obokata, Masaru Negishi, Kazuaki Ohyama, Yoshiaki Okada, Haruka Imai, Kunihiko Kurabayashi, Masahiko PLoS One Research Article BACKGROUND: Although many risk factors for Metabolic syndrome (MetS) have been reported, there is no clinical score that predicts its incidence. The purposes of this study were to create and validate a risk score for predicting both incidence and recovery from MetS in a large cohort. METHODS: Subjects without MetS at enrollment (n = 13,634) were randomly divided into 2 groups and followed to record incidence of MetS. We also examined recovery from it in rest 2,743 individuals with prevalent MetS. RESULTS: During median follow-up of 3.0 years, 878 subjects in the derivation and 757 in validation cohorts developed MetS. Multiple logistic regression analysis identified 12 independent variables from the derivation cohort and initial score for subsequent MetS was created, which showed good discrimination both in the derivation (c-statistics 0.82) and validation cohorts (0.83). The predictability of the initial score for recovery from MetS was tested in the 2,743 MetS population (906 subjects recovered from MetS), where nine variables (including age, sex, γ-glutamyl transpeptidase, uric acid and five MetS diagnostic criteria constituents.) remained significant. Then, the final score was created using the nine variables. This score significantly predicted both the recovery from MetS (c-statistics 0.70, p<0.001, 78% sensitivity and 54% specificity) and incident MetS (c-statistics 0.80) with an incremental discriminative ability over the model derived from five factors used in the diagnosis of MetS (continuous net reclassification improvement: 0.35, p < 0.001 and integrated discrimination improvement: 0.01, p<0.001). CONCLUSIONS: We identified four additional independent risk factors associated with subsequent MetS, developed and validated a risk score to predict both incident and recovery from MetS. Public Library of Science 2015-07-31 /pmc/articles/PMC4521863/ /pubmed/26230621 http://dx.doi.org/10.1371/journal.pone.0133884 Text en © 2015 Obokata et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Obokata, Masaru Negishi, Kazuaki Ohyama, Yoshiaki Okada, Haruka Imai, Kunihiko Kurabayashi, Masahiko A Risk Score with Additional Four Independent Factors to Predict the Incidence and Recovery from Metabolic Syndrome: Development and Validation in Large Japanese Cohorts |
title | A Risk Score with Additional Four Independent Factors to Predict the Incidence and Recovery from Metabolic Syndrome: Development and Validation in Large Japanese Cohorts |
title_full | A Risk Score with Additional Four Independent Factors to Predict the Incidence and Recovery from Metabolic Syndrome: Development and Validation in Large Japanese Cohorts |
title_fullStr | A Risk Score with Additional Four Independent Factors to Predict the Incidence and Recovery from Metabolic Syndrome: Development and Validation in Large Japanese Cohorts |
title_full_unstemmed | A Risk Score with Additional Four Independent Factors to Predict the Incidence and Recovery from Metabolic Syndrome: Development and Validation in Large Japanese Cohorts |
title_short | A Risk Score with Additional Four Independent Factors to Predict the Incidence and Recovery from Metabolic Syndrome: Development and Validation in Large Japanese Cohorts |
title_sort | risk score with additional four independent factors to predict the incidence and recovery from metabolic syndrome: development and validation in large japanese cohorts |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4521863/ https://www.ncbi.nlm.nih.gov/pubmed/26230621 http://dx.doi.org/10.1371/journal.pone.0133884 |
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