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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

Citation

Obokata, M and Negishi, K and Ohyama, Y and Okada, H and Imai, K and Kurabayashi, M, A risk score with additional four independent factors to predict the incidence and recovery from Metabolic Syndrome: development and validation in large Japanese cohorts, PLoS One, 10, (7) Article e0133884. ISSN 1932-6203 (2015) [Refereed Article]


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Licensed under Creative Commons Attribution 4.0 International (CC BY 4.0) http://creativecommons.org/licenses/by/4.0/

DOI: doi:10.1371/journal.pone.0133884

Abstract

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.

Item Details

Item Type:Refereed Article
Keywords:metabolic syndrome
Research Division:Medical and Health Sciences
Research Group:Cardiorespiratory Medicine and Haematology
Research Field:Cardiology (incl. Cardiovascular Diseases)
Objective Division:Health
Objective Group:Clinical Health (Organs, Diseases and Abnormal Conditions)
Objective Field:Cardiovascular System and Diseases
Author:Negishi, K (Dr Kazuaki Negishi)
ID Code:102184
Year Published:2015
Web of Science® Times Cited:3
Deposited By:Menzies Institute for Medical Research
Deposited On:2015-08-03
Last Modified:2017-11-02
Downloads:175 View Download Statistics

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