News and Trends • Published July 3, 2026
CGM May Complement Standard Tests for Prediabetes Detection
Continuous glucose monitoring (CGM) metrics may help identify early abnormalities in glucose regulation and provide information complementary to conventional laboratory tests used to classify prediabetes, according to a study published in Diabetes Research and Clinical Practice.
Researchers noted that prediabetes classifications based on hemoglobin A1C (HbA1c) and fasting plasma glucose (FPG) are frequently inconsistent, potentially complicating the early identification of individuals at increased metabolic risk.
The cross-sectional analysis evaluated whether CGM metrics could effectively classify prediabetes and how their performance compared with HbA1c and FPG.
The study included data from 1,883 participants in the Human Phenotype Project who had concurrent CGM, HbA1c, and FPG measurements.
Researchers evaluated individual CGM metrics using four American Diabetes Association–based laboratory reference definitions of prediabetes. They also assessed a combined model incorporating six clinically selected CGM measures. Discriminative performance was evaluated using the area under the receiver operating characteristic curve (AUC).
The results showed substantial disagreement between HbA1c- and FPG-based classifications, with only 9.5% of participants meeting both criteria for prediabetes.
Several CGM metrics demonstrated discriminatory performance comparable to conventional laboratory markers, with AUC values ranging from 0.645 to 0.677. Classification performance improved when prediabetes was defined using both laboratory criteria, although no individual CGM metric demonstrated strong discriminatory performance on its own.
Based on the findings, the researchers concluded that CGM metrics can provide classification performance comparable to conventional laboratory markers while offering additional insight into glucose regulation.
The authors suggested that CGM may be most useful as an adjunct to, rather than a replacement for, conventional laboratory testing, particularly when HbA1c and FPG results are discordant. They also emphasized the need for prospective studies incorporating oral glucose tolerance testing and longitudinal clinical outcomes.
The content contained in this article is for informational purposes only. The content is not intended to be a substitute for professional advice.
Researchers noted that prediabetes classifications based on hemoglobin A1C (HbA1c) and fasting plasma glucose (FPG) are frequently inconsistent, potentially complicating the early identification of individuals at increased metabolic risk.
The cross-sectional analysis evaluated whether CGM metrics could effectively classify prediabetes and how their performance compared with HbA1c and FPG.
The study included data from 1,883 participants in the Human Phenotype Project who had concurrent CGM, HbA1c, and FPG measurements.
Researchers evaluated individual CGM metrics using four American Diabetes Association–based laboratory reference definitions of prediabetes. They also assessed a combined model incorporating six clinically selected CGM measures. Discriminative performance was evaluated using the area under the receiver operating characteristic curve (AUC).
The results showed substantial disagreement between HbA1c- and FPG-based classifications, with only 9.5% of participants meeting both criteria for prediabetes.
Several CGM metrics demonstrated discriminatory performance comparable to conventional laboratory markers, with AUC values ranging from 0.645 to 0.677. Classification performance improved when prediabetes was defined using both laboratory criteria, although no individual CGM metric demonstrated strong discriminatory performance on its own.
Based on the findings, the researchers concluded that CGM metrics can provide classification performance comparable to conventional laboratory markers while offering additional insight into glucose regulation.
The authors suggested that CGM may be most useful as an adjunct to, rather than a replacement for, conventional laboratory testing, particularly when HbA1c and FPG results are discordant. They also emphasized the need for prospective studies incorporating oral glucose tolerance testing and longitudinal clinical outcomes.
The content contained in this article is for informational purposes only. The content is not intended to be a substitute for professional advice.
