The Importance of Metabolic Syndrome in Patient Progression to Type 2 Diabetes Mellitus

Introduction: Type 2 diabetes mellitus (T2DM) is a common chronic condition associated with significant risk of morbidity and mortality. Metabolic syndrome (MetS) is a chronic prevalent condition, but rarely documented in administrative data. A positive MetS finding comes from tracking five clinical dimensions, and employing a minimum three condition threshold. The aim of this study was to validate a new administrative data MetS algorithm by showing its relevance in tracking progression to T2DM.

Methods: A cohort of 1,321,314 persons enrolled for 3 years in a Medicare Advantage health and wellness company with no evidence of diabetes in the first year were tracked in the subsequent 2 years. Demographic information along with evidence of prediabetes from administrative claims and lab data were documented for the first year. Algorithms to detect MetS and Charlson Comorbidity Index (CCI) were applied to the first year data. For the subsequent 2 years, ICD-10 diagnostic information from administrative data was tracked to identify individuals who progressed into T2DM. Descriptive statistics and Poisson regression analysis were used to assess correlation between first year data and subsequent relative risk for T2DM.

Results: The study population was 87.3% white, 56.4% female, mean age of 70.6, and an overall T2DM progression rate of 8.63%. In the first year, 79.3% had no MetS and no prediabetes (NMNP), 6.9% had MetS but no prediabetes (MNP), 6.8% had no MetS but with prediabetes (NMP), and 7.1% had MetS with prediabetes (MP). Compared to NMNP, the MNP group had an elevated risk of progression to T2DM (RR 1.63 | 95% CL: 1.60, 1.67), as did NMP (1.73 | 1.70, 1.76), and MP (2.47 | 2.43, 2.51). Nonwhite races (1.31 to 1.52), male (1.21), and higher CCI scores (1.02 to 1.45) all were associated with elevated and significant relative risk of T2DM.

Conclusion: Our findings reveal that use of MetS diagnosis and consideration of patient demographics and CCI risk score yield valuable information regarding risk of T2DM.