Including selective metabolic components in current diagnostic criteria does not improve discriminative validity for metabolic syndrome: a risk score approach

Abstract

Objective To examine whether including additional metabolic components to the current five-marker system can improve the discriminative validity for diagnosing metabolic syndrome (MetS). Methods This longitudinal cohort study included data from subjects that had completed at least three health examinations during a 5-year period. The study outcome was the onset of MetS. Sociodemographic and biochemical variables were recorded for all subjects so that the adjusted relative risks (ARRs) could be calculated for 11 metabolic components. Risk scores for the development of MetS based on the ARR values were determined. The sums of the risk scores of different component combinations were used to conduct a receiver operating characteristic (ROC) curve analysis of MetS diagnosis. Results A total of 3368 individuals with complete data was analysed. The ARRs of the 11 metabolic components were all statistically significant. According to ROC analysis, although good discriminative validity (area under the curve [AUC] range, 0.954–0.976) could be achieved for MetS diagnosis by using either all 11 or combinations of six metabolic components (the five current components plus one extra component), the current five metabolic components used for diagnosis had the best discriminative validity (AUC = 0.977). Conclusion The current five metabolic components used for the diagnosis of MetS still represent the best combination with the highest discriminative validity.

Association between metabolic syndrome and uric acid: a systematic review and meta-analysis

“… Author, year, country Study design STROBE reporting guidelines 24 Age of participants No. of subjects MetS+/MetS− MetS criteria Aims/conclusions Ahmadnezhad et al, 2018, Iran 55 Cohort study 19 49.5 ± 8.1 MetS+ 47.1 ± 8.1 MetS− 2481/4727 Total 7208 IDF Aim: association between serum prooxidant antioxidant balance (PAB), AU and hs-CRP in 7208 participants in the MASHAD study cohort Conclusion: PAB, UA and hs-CRP are independently associated with the presence of MetS Akboga et al, 2016, Turkey 27 Cross-sectional study 19 57.2 ± 8.7 MetS+ 55.2 ± 8.9 MetS− 114/63 Total 177 NCEP ATP III Aim: The aim of the study was to assess the association of serum YKL-40 levels with the presence and severity of MetS Conclusion: Serum levels of YKL-40 are significantly associated with the presence of MetS Ali et al, 2020, Bangladesh 28 Cross-sectional study 20 39.5 ± 14.1 MetS+ 27.8 ± 10.4 MetS− 93/327 Total 420 NCEP ATP III Aim: To assess the relationship of SUA with MetS and its components in Bangladeshi adults Conclusion: Elevated SUA is significantly associated with the prevalence of MetS and its components Chang et al, 2019, Taiwan 29 Longitudinal cohort study 20 ≥ 30 years 409/2959 Total 3368 NCEP ATP III Aim: to examine whether the inclusion of additional metabolic components to the current five markers can improve the discriminative validity for MetSdiagnosis Conclusion: The five current metabolic markers used for MetSdiagnosis represent the best combination with the highest discriminative validity Chen Y et al, 2017,Taiwan 30 …”

“…Studies with similar methodologies but with discrepancies in quality may have biased results. Among all the papers included in this review, only ten studies 29 , 35 , 38 , 41 , 42 , 50 , 56 , 63 , 65 , 68 had performed this step correctly. The quality of the evidence obtained is "very low" since observational studies have been analysed where there is a high risk of bias and, in addition, they present a very high inconsistency (heterogeneity).…”

Association between metabolic syndrome and uric acid: a systematic review and meta-analysis.

“…Of the included papers, 26 directly associated UA with MetS [28][29][30]33,35,36,38,[40][41][42][43][44][45][46][48][49][50]56,57,[59][60][61]63,65,66,72 , and 17 reports collected data indirectly 27,31,32,34,37,39,47,[51][52][53]57,58,64,[68][69][70]74 , i.e. they study parameters related to MetS and collect data associated with UA.…”