Glycated albumin in diabetes mellitus: a meta-analysis of diagnostic test accuracy

Objectives Guidelines recommend the diagnosis of diabetes should be based on either plasma glucose or glycated hemoglobin (HbA(1C)) findings. However, lately studies have advocated glycated albumin (GA) as a useful alternative to HbA(1c). We conducted a systematic review and meta-analysis to determine the overall diagnostic accuracy of GA for the diagnosis of diabetes. Content We searched for articles of GA diabetes diagnostic accuracy that were published up to August 2021. Studies were selected if reported an oral glucose tolerance test as a reference test, measured GA levels by enzymatic methods, and had data necessary for 2 x 2 contingency tables. A bivariate model was used to calculate the pooled estimates. This meta-analysis included nine studies, totaling 10,007 individuals. Of those, 3,106 had diabetes. The studies showed substantial heterogeneity caused by a non-threshold effect and reported different GA optimal cut-offs for diagnosing diabetes. The pooled diagnostic odds ratio (DOR) was 15.93 and the area under the curve (AUC) was 0.844, indicating a good level of overall accuracy for the diagnosis of diabetes. The effect of the GA threshold on diagnostic accuracy was reported at 15.0% and 17.1%. The optimal cut-off for diagnosing diabetes with GA was estimated as 17.1% with a pooled sensitivity of 55.1% (95% CI 36.7%-72.2%) and specificity of 94.4% (95% CI 85.3%-97.9%). Outlook GA has good diabetes diagnostic accuracy. A GA threshold of 17.1% may be considered optimal for diagnosing diabetes in previously undiagnosed individuals.

Automated summary

Glycated albumin (GA) shows good overall diagnostic accuracy for diabetes, with an optimal threshold of 17.1% for diagnosing previously undiagnosed individuals.