Development of predictive equation and score for 5-year metabolic syndrome incidence in Japanese adults

by Anwar Ahmed Salim, Shin Kawasoe, Takuro Kubozono, Satoko Ojima, Takeko Kawabata, Hiroshi Hashiguchi, Yoshiyuki Ikeda, Masaaki Miyata, Hironori Miyahara, Koichi Tokushige, Yoshihiko Nishio, Mitsuru Ohishi

Background

Predicting metabolic syndrome (MetS) is important for identifying high-risk cardiovascular disease individuals and providing preventive interventions. We aimed to develop and validate an equation and a simple MetS score according to the Japanese MetS criteria.

Methods

In total, 54,198 participants (age, 54.5±10.1 years; men, 46.0%), with baseline and 5-year follow-up data were randomly assigned to ‘Derivation’ and ‘Validation’ cohorts (ratio: 2:1). Multivariate logistic regression analysis was performed in derivation cohort and scores were assigned to factors corresponding to β-coefficients. We evaluated predictive ability of the scores using area under the curve (AUC), then applied them to validation cohort to assess reproducibility.

Results

The primary model ranged 0–27 points had an AUC of 0.81 (sensitivity: 0.81, specificity: 0.81, cut-off score: 14), and consisted of age, sex, blood pressure (BP), body mass index (BMI), serum lipids, glucose measurements, tobacco smoking, and alcohol consumption. The simplified model (excluding blood tests) ranged 0–17 points with an AUC of 0.78 (sensitivity: 0.83, specificity: 0.77, cut-off score: 15) and included: age, sex, systolic BP, diastolic BP, BMI, tobacco smoking, and alcohol consumption. We classified individuals with a score <15 and ≥15 points as low- and high-risk MetS, respectively. Furthermore, the equation model generated an AUC of 0.85 (sensitivity: 0.86, specificity: 0.55). Analysis of the validation and derivation cohorts yielded similar results.

Conclusion

We developed a primary score, an equation model, and a simple score. The simple score is convenient, well-validated with acceptable discrimination, and could be used for early detection of MetS in high-risk individuals.