The cutoffs and performance of glycated hemoglobin for diagnosing diabetes and prediabetes in a young and middle-aged population and in an elderly population

Optimal Glycated Hemoglobin Cutoff for Diagnosis of Diabetes and Prediabetes in Chinese Breast Cancer Women

Purpose

Glycated hemoglobin (HbA1c) is widely used in diabetes management and now recommended for diagnosis and risk assessment. Our research focused on investigating the optimal cutoff points of HbA1c for diagnosis of diabetes and prediabetes in Chinese breast cancer women, aiming to enhance early detection and tailor treatment strategies.

Patients and Methods

This study involved 309 breast cancer women without diabetes history in China. Patients were categorized into groups of newly diagnosed diabetes, prediabetes, and normal glucose tolerance using oral glucose tolerance test (OGTT) according to the 2010 ADA criteria. HbA1c data were collected from all patients. Receiver operating characteristic (ROC) curve analysis was used to assess the effectiveness of the HbA1c screening.

Results

Among the 309 breast cancer women without diabetes history, 96 (31.0%) were identified with diabetes and 130 (42.1%) had prediabetes according to OGTT, and the incidence of normal glucose tolerance was only 26.9% (83). ROC curve analysis, using OGTT as a reference, revealed that the area under the curve of 0.903 (P<0.001, 95% CI, 0.867-0.938) for HbA1c alone, indicating high accuracy. The optimal HbA1c cutoff for identifying diabetes was determined to be 6.0%, with a sensitivity of 78.1% and specificity of 86.4%. For prediabetes, the ROC curve for HbA1c alone showed that the area under the ROC curve of 0.703 (P<0.001, 95% CI, 0.632-0.774), with an optimal cutoff of 5.5% (sensitivity of 76.9% and specificity of 51.8%).

Conclusion

The prevalence of undiagnosed diabetes is very high in breast cancer women without diabetes history in China. The optimal cutoff points of HbA1c for identifying diabetes and prediabetes are 6.0% and 5.5% in Chinese breast cancer women, respectively.

Which Is the Most Appropriate Cut-Off of HbA1c for Prediabetes Screening in Caucasian Youths with Overweight or Obesity?

This cross-sectional study aimed to assess the best cut-off of HbA1c for detection of impaired fasting glucose (IFG), impaired glucose tolerance (IGT), beta-cell impairment and cardiometabolic risk (CMR) profile in overweight or obese (OW/OB) Caucasian youths. Two-hour oral glucose tolerance test was available in 1549 youths, one-hour glucose (G₆₀) in 1430 youths and disposition index (DI) in 972 youths. Insulin resistance (IR) was calculated as Homeostatic Model Assessment for IR and insulin sensitivity (IS) as 1/fasting insulin. High G₆₀ was defined by a value ≥ 133 mg/dL. The best cut-off of HbA1c for IFG or IGT was 5.5%. The frequency of individuals with HbA1c ≥ 5.5% was 32.5%, compared to 16.3% with HbA1c ≥ 5.7% (as proposed by the American Diabetes Association). HbA1c ≥ 5.5% showed higher sensitivity and lower specificity with respect to HbA1c ≥ 5.7% for all the abnormalities examined (IFG, IGT, high G₆₀, IR, low IS, DI and CMR factors). In conclusion, this lower cut-off might represent a more appropriate screening marker of glucose dysmetabolism in youths with OW/OB. Prospective studies are needed to validate this cut-off for predicting prediabetes/diabetes in youths with OW/OB.

The bidirectional association of C-peptide with cardiovascular risk in nondiabetic adults and patients with newly diagnosed type 2 diabetes mellitus: a retrospective cohort study

Background

Recent literature reported the biological role of C-peptide, but this role is still controversial and unclear. The primary aim of this study was to investigate associations between C-peptide and cardiovascular biomarkers as well as events.

Methods

A total of 55636 participants who had a health examination from 2017 to 2021 were included. Of them, 6727 participants visited the hospital at least twice. Cardiovascular biomarkers like high-sensitivity C-reactive protein (hs-CRP) and high-sensitivity cardiac troponin T (hs-cTnT) were measured and their relationships with fasting C-peptide were evaluated for all participants. Cardiovascular events were obtained during the last visit and their associations with C-peptide were evaluated for those participants who visited the hospital at least twice.

Results

Among the included participants, 11.1% had a previous type 2 diabetes mellitus (T2DM). In the participants without previous T2DM, the relationships between fasting C-peptide and hs-CRP and hs-cTnT were negative if the value of fasting C-peptide was < 1.4 ng/mL and positive if the value was ≥ 1.4 ng/mL. These relationships remained significant after adjusting for hemoglobin A1c, insulin resistance index, and its interaction with C-peptide, even if the participants were stratified by glucose metabolism status or levels of insulin resistance index. Hazard ratios of cardiovascular events were first decreased and then increased with the increasing of baseline C-peptide levels, though these associations became unsignificant using the multivariate Cox regression model. Unlike the participants without previous T2DM, the associations of C-peptide with cardiovascular biomarkers and events were not significant in the patients with previous T2DM.

Conclusions

The associations of C-peptide with cardiovascular biomarkers and events were different between the participants without previous T2DM and those with previous T2DM. The effect of C-peptide on cardiovascular risk may be bidirectional, play a benefit role at a low level, and play a harmful role at a high level in the nondiabetic adults and the patients with newly diagnosed T2DM.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12933-022-01636-z.

Biomolecular Surface Functionalization and Stabilization Method to Fabricate Quantum Dots Nanobeads for Accurate Biosensing Detection

The surface functionalization of quantum dots (QDs) is essential for their application as a label material in a biological field. Here, a protein surface functionalization approach was introduced to combine with silica encapsulation for the sustainable and stable synthesis of QDs nanobeads for biomarker detection. The formation of QDs nanobeads was achieved by multiple mercapto groups in bovine serum albumin (BSA) macromolecules as multidentate ligands to replace hydrophobic ligands on the surface of QDs and decompression. The resulting QDs nanobeads exhibited 20 times more photoluminescence than the corresponding hydrophobic QDs and presented excellent stability under physiological conditions due to the protection of BSA and silica. The nanobeads served as a robust signal-generating reagent to construct the lateral flow immunoassay (LFIA) biosensor for the detection of glycosylated hemoglobin (HbA1c). The concentration of HbA1c was determined within 10 min with high specificity using only 60 μL of whole blood samples collected clinically. The nanobeads-based LFIA biosensor exhibited linear detection of HbA1c from 4.2% to 13.6%. The accuracy and stability of this approach in clinical utility was demonstrated by the detection of HbA1c after a long-term storage of test strips. This protein surface modification technology provides a new way for improving the biological properties of QDs in clinical diagnosis.

Comparison of Various Indices in Identifying Insulin Resistance and Diabetes in Chronic Spinal Cord Injury

The purpose of this screening and diagnostic study was to examine the accord among indices of glucose metabolism, including the Homeostatic Model Assessment for Insulin Resistance (HOMA), HOMA2, Matsuda Index, Quantitative Insulin-sensitivity Check Index (QUICKI), hemoglobin A1C (HbA1C), and fasting plasma glucose (FPG) against intravenous glucose tolerance test-measured insulin sensitivity (Si) in individuals with chronic motor complete SCI. Persons with chronic (≥12-months post-injury) SCI (n = 29; 79% men; age 42.2 ± 11.4; body mass index 28.6 ± 6.4 kg/m2; C4-T10) were included. Measures were compared using adjusted R2 from linear regression models with Akaike information criterion (AIC, a measure of error). QUICKI had the greatest agreement with Si (adjusted R2 = 0.463, AIC = 91.1, p = 0.0001), followed by HOMA (adjusted R2 = 0.378, AIC = 95.4, p = 0.0008), HOMA2 (adjusted R2 = 0.256, AIC = 99.7, p = 0.0030), and the Matsuda Index (adjusted R2 = 0.356, AIC = 95.5, p = 0.0004). FPG (adjusted R2 = 0.056, AIC = 107.5, p = 0.1799) and HbA1C (adjusted R2 = 0.1, AIC = 106.1, p = 0.0975) had poor agreement with Si. While HbA1C and FPG are commonly used for evaluating disorders of glucose metabolism, QUICKI demonstrates the best accord with Si compared to the other measures.

Patterns of changes in fasting plasma glucose, hemoglobin A1c and the area under the curve during oral glucose tolerance tests in prediabetic subjects: results from a 16-year prospective cohort study among first-degree relatives of type 2 diabetic patients

AIM

This study aimed to identify the patterns of changes in glycemic indices over time in prediabetics and to classify these subjects as either having a high or low risk for developing diabetes in future.

METHODS

This prospective 16-year cohort study was conducted among 1228 prediabetic subjects. Three measurements including first visit, mean values during the follow-up period, and last visit from fasting plasma glucose (FPG), glycosylated hemoglobin (HbA1_C), and area under the curve during an oral glucose tolerance test (OGTT AUC) were used to evaluate the patterns of changes by using the latent Markov model (LMM).

RESULTS

The mean (standard deviation) age of subjects was 44.0 (6.8) years, and 73.6% of them were female. The LMM identified 2 latent states of subjects in terms of changes in FPG, HbA1c, OGTT AUC, and the combination of these glycemic measures: a low tendency to progress diabetes and a high tendency to progress diabetes with the latent state sizes (87, 13%), (94, 6%), (57, 43%), and (84, 16%), respectively. The LMM showed that the probability of transitioning from a low tendency to a high tendency to progress diabetes was higher than the probability of transitioning in the opposite direction.

CONCLUSION

Based on a long-term evaluation of patterns of changes in glycemic indices, we classified prediabetic subjects into 2 groups (high or low risk to progress diabetes states in future). Also, the method used enabled us to estimate the transition probabilities from low- to high-risk states and vice versa. Our results reemphasized the values of all 3 glycemic measures in clinical settings for identifying prediabetic people with a high risk of progressing diabetes and the need for more effective prevention strategies, which should be conducted as urgently in prediabetic life as high-risk subjects.

One-hour plasma glucose concentration can identify elderly Chinese male subjects at high risk for future type 2 diabetes mellitus: A 20-year retrospective and prospective study

AIM

There have been few reports regarding the association between 1 h-PG concentration and type 2 diabetes mellitus (T2DM) in the elderly. This study was performed to assess the efficacy of 1 h-PG and 2 h-PG values in predicting future risk of T2DM in elderly.

METHODS

The study population consisted of 928 male volunteers ≥ 55 years old without diabetes who were involved in a retrospective-prospective cohort study over 20 years with a baseline fasting plasma glucose (FPG) and OGTT that included measurement of 1 h-PG and 2 h-PG. The predictive capabilities of FPG and 1 h-PG, 2 h-PG values obtained during OGTT alone and added to a clinical prediction model consisting of traditional diabetes risk factors were assessed.

RESULTS

Overall, 577 of all the 928 study participants (62%) developed T2DM over the 20-year follow-up. 1 h-PG and 2 h-PG values predicted T2DM and remained independent predictors of T2DM after adjusting for various traditional risk factors [HR = 1.269 (95% CI = 1.214-1.327), P < 0.001; HR = 1.269 (95% CI = 1.179-1.366), P < 0.001, respectively]. C-statistics for 1-h PG (C-statistics 0.794 [95% CI 0.765-0.823]) was significantly greater than that for 2-h PG (C-statistic 0.747 [95% CI 0.716-0.779]) in models adjusting for various traditional risk factors. 1 h-PG had the greatest area under the ROC curve (AUC, 0.766), which was greater than that of 2 h-PG (0.719).

CONCLUSIONS

1 h-PG is useful as a predictor of future development of T2DM independently of traditional risk factors in an elderly Chinese male population.

Comparison of "burden of disease" in elderly and non-elderly patients with pre-diabetes: A cross-sectional study

OBJECTIVE:

There are a lot of studies comparing elderly and adult patients with diabetes but not pre-diabetes systematically. We aimed to compare the discrepancies of clinical status and burden of disease in elderly (≥60 years old) versus non-elderly (18–59 years old) adult pre-diabetics.

METHODS:

A total of 126 pre-diabetic patients were included in the study and were compared as two groups; the elderly (n=32) and non-elderly (n=94). Fasting plasma glucose (FPG) and glycated hemoglobin (HbA1c) levels, body mass index (BMI), the homeostasis model assessment of insulin resistance (HOMA-IR), health-related quality of life using the short form-36 (SF-36) questionnaire, and disability using the health assessment questionnaire (HAQ) were evaluated.

RESULTS:

Gender, BMI, the presence of obesity, the ratio of HOMA-IR, FPG, and plasma glucose in the 2^nd h oral glucose tolerance test were similar in non-elderly patients with pre-diabetes compared to the elderly ones. However, HbA1c levels were higher in elderly subjects in our study. According to the SF-36 questionnaire and HAQ score, there were no significant differences between groups. The median total HAQ scores were 0.125 (non-elderly) and 0.250 (elderly) for groups and there was no significant difference (p=0.099).

CONCLUSION:

In the similar gender and BMI groups, pre-diabetes in the elderly gives different outcomes according to HbA1c. Since SF-36 questionnaire and HAQ scores were not statistically different in both pre-diabetic groups, the burden of disease is thought to be basically due to the presence of the disease rather than aging.

Reconsidering the HbA1c Cutoff for Diabetes Diagnosis Based on a Large Chinese Cohort

INTRODUCTION

The HbA1c has been considered as the 'gold standard' in diabetes diagnosis and management, however, age, gender and body mass index (BMI) might have certain effects on HbA1c. We are aiming to further investigate the correlation between age and HbA1c, and whether it was affected by gender and BMI.

METHODS

A cross-sectional survey including 135,893 nondiabetic individuals who took the physical examination between 2013 and 2017 was conducted. The subjects were grouped by gender, age and BMI, and the interactive and independent effects of the 3 factors on the HbA1c were detected. The median and 95% confidence interval (CI) of HbA1c levels were calculated.

RESULTS

The HbA1c levels gradually increased along with age, both in female and male, and there is a positive association between BMI and the HbA1c. The difference on HbA1c in gender was associated with both age and BMI, the age-related increase in HbAlc was accentuated in the subgroup with higher BMI, and there was a marked accentuation of the positive association between BMI and HbA1c as age increased. In almost all the young and middle-aged (aged 20-59) subgroups, the 97.5^th percentiles of HbA1c levels were lower than 6.5%, suggesting that the single HbA1c cutoff value is probably not applicable to the young and middle-aged population.

CONCLUSIONS

We recommend that the effects of age, gender and BMI should be taken into consideration when using HbA1c for the diagnosis and management of diabetes, especially in the young and middle-aged population.

A Comparison of Biomarkers in the Assessment of Glycemic Control in Diabetes: Reviewing the Evidence

BACKGROUND

Diabetes Mellitus (DM) is a chronic life-long progressive multisystem heterogeneous metabolic disorder with complex pathogenesis.

INTRODUCTION

Hyperglycemia is not only one of the classical signs of DM, but it also serves as the pivotal prerequisite for the diagnosis of the disease. However, with the advancement in the field of analytical biochemistry, a number of alternative and specific biomarkers have been discovered which can be used for better diagnosis of the DM. In this review, we have discussed various aspects of DM and different biomarkers used in assessing glycemia.

METHODOLOGY

A thorough literature survey was conducted to identify various studies that reported the use of conventional and non-conventional markers for the assessment of glycemia in DM patients.

CONCLUSION

The accurate detection and hence diagnosis of DM has become easy and more specific with the use of various biomarkers.

Optimal Glycated Hemoglobin Cutoff Point for Diagnosis of Type 2 Diabetes in Iranian Adults

OBJECTIVES

The aim of this study was to evaluate the capability of glycated hemoglobin (A1C) levels to be a tool for identifying Iranian adults with diabetes and prediabetes.

METHODS

In a cross-sectional population-based study, 1,813 adults, men and women 35 to 75 years of age and without a history of diabetes and hemoglobinopathies, were included. Fasting blood glucose and A1C levels were obtained. According to the criteria of the American Diabetes Association, participants were categorized into 3 groups: newly diagnosed diabetes, prediabetes and healthy subjects. The optimal cutoff point for A1C in diabetes and prediabetes diagnosis was determined by studying the sensitivity and specificity of different cutoff points for A1C, while using different levels of fasting blood glucose as the gold standard.

RESULTS

Participants with newly diagnosed diabetes were significantly older than subjects with prediabetes and healthy subjects (mean [± SD] 47.3±12.9, 44.6±13.0 and 39.2±14.1 years, respectively) and also had higher body mass indexes. As expected, the levels of fasting blood glucose (8.79±2.24, 6.01±0.38 and 4.97±0.4 mmol/L) and A1C (6.55±1.4%, 5.61±0.61% and 5.28±0.59%) were significantly different in the groups (p<0.001). The optimal cutoff point for A1C to predict prediabetes was 5.5% (sensitivity of 60.5% and specificity of 63.1%) and for diabetes was 5.9% (sensitivity of 66.7% and specificity of 81.2%). ADA cutoff points for prediabetes and diabetes detection yielded a sensitivity of 45.2% and 39.8%, respectively.

CONCLUSIONS

The findings suggest the necessity of determining the A1C cutoffs for detecting diabetes or prediabetes in each region's population. They also suggest that the combination of these A1C cutoffs with fasting blood glucose levels are required to determine diabetes and prediabetes more accurately.

A Consensus of Key Opinion Leaders on the Management of Pre-diabetes in the Asia-Pacific Region

The Asia-Pacific region carries a high disease burden, with over half of the global diabetic population residing in this region. Increasing evidence shows that without targeted intervention, the progression from impaired glucose tolerance (IGT) to type 2 diabetes occurs more frequently in Asians compared with Caucasians. Furthermore, IGT is independently associated with an increased risk of cardiovascular disease, and should be managed as early as possible. Because diabetes is now a major public health issue, strategies aimed at prevention and treatment are urgently required. Lifestyle modification, including weight loss, dietary changes and increased physical activity, play a major role in controlling the disease. Significant evidence also supports the effectiveness of a combination of lifestyle modification and pharmacologic therapy, such as metformin, in delaying the onset of diabetes. Although the importance of lifestyle interventions is well recognized throughout Asia, many countries do not have formal recommendations to guide the diagnosis and management of individuals at risk of progression to diabetes. At a recent regional meeting, experts from the Asian region convened to develop consensus recommendations to guide clinicians in the management of Asian patients with pre-diabetes. These consensus recommendations provide a clear and concise approach to the management of individuals with IGT based on the available evidence and current best clinical practice.

PERFORMANCE OF A1C VERSUS OGTT FOR THE DIAGNOSIS OF PREDIABETES IN A COMMUNITY-BASED SCREENING

OBJECTIVE

Reliable identification of individuals at risk for developing diabetes is critical to instituting preventative strategies. Studies suggest that the accuracy of using hemoglobin A1c as a sole diagnostic criterion for diabetes may be variable across different ethnic groups. We postulate that there will be lack of concordance between A1c and the oral glucose tolerance test (OGTT) for diagnosing prediabetes across Hispanic and non-Hispanic white (NHW) populations.

METHODS

A total of 218 asymptomatic adults at risk for type 2 diabetes (T2D) were assessed with A1c and OGTT for the diagnosis of prediabetes. Glucose homeostasis status was assigned as no diabetes (A1c <5.7% [39 mmol/mol]), prediabetes (A1c 5.7 to 6.4% [46 mmol/mol]), and T2D (A1c >6.4% [46 mmol/mol]). Inclusion criteria were age >18 years and at least one of the following: a family history of diabetes, a history of gestational diabetes, Hispanic ethnicity, non-Caucasian race, or obesity. Subjects received a fasting 75-g OGTT and A1c on the same day. Bowker's test of symmetry was employed to determine agreement between the tests.

RESULTS

Data from 99 Hispanic patients and 79 NHW patients were analyzed. There was no concordance between A1c and OGTT for Hispanic (P = .002) or NHW individuals (P = .003) with prediabetes.

CONCLUSION

A1c is discordant with OGTT among Hispanic and NHW subjects for the diagnosis of prediabetes. Sole use of A1c to designate glycemic status will result in a greater prevalence of prediabetes among Hispanic and NHW New Mexicans.

ABBREVIATIONS

A1c = hemoglobin A1c BMI = body mass index CDC = Centers for Disease Control CI = confidence interval FPG = fasting plasma glucose NHW = non-Hispanic white OGTT = oral glucose tolerance test T2D = type 2 diabetes WHO = World Health Organization.

Update on pre-diabetes: Focus on diagnostic criteria and cardiovascular risk

Pre-diabetes, which is typically defined as blood glucose concentrations higher than normal but lower than the diabetes threshold, is a high-risk state for diabetes and cardiovascular disease development. As such, it represents three groups of individuals: Those with impaired fasting glucose (IFG), those with impaired glucose tolerance (IGT) and those with a glycated haemoglobin (HbA_1c) between 39-46 mmol/mol. Several clinical trials have shown the important role of IFG, IGT and HbA_1c-pre-diabetes as predictive tools for the risk of developing type 2 diabetes. Moreover, with regard to cardiovascular disease, pre-diabetes is associated with more advanced vascular damage compared with normoglycaemia, independently of confounding factors. In view of these observations, diagnosis of pre-diabetes is mandatory to prevent or delay the development of the disease and its complications; however, a number of previous studies reported that the concordance between pre-diabetes diagnoses made by IFG, IGT or HbA_1c is scarce and there are conflicting data as to which of these methods best predicts cardiovascular disease. This review highlights recent studies and current controversies in the field. In consideration of the expected increased use of HbA_1c as a screening tool to identify individuals with alteration of glycaemic homeostasis, we focused on the evidence regarding the ability of HbA_1c as a diagnostic tool for pre-diabetes and as a useful marker in identifying patients who have an increased risk for cardiovascular disease. Finally, we reviewed the current evidence regarding non-traditional glycaemic biomarkers and their use as alternatives to or additions to traditional ones.