Mini Review

Revisiting HbA1c in type 2 diabetes: Strengths, pitfalls, and emerging alternatives

Manal Tashkandi ^1,2*

¹ Department of Biochemistry, College of Science, University of Jeddah, Jeddah-21589 Saudi Arabia.

* Correspondence: matashkandi@uj.edu.sa (M.T.)

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Citation: Tashkandi, M. Revisiting HbA1c in type 2 diabetes: Strengths, pitfalls, and emerging alternatives. Glob. Jour. Bas. Sci. 2025, 1(10). 1-5.

Received: June 21, 2025

Revised: July 29, 2025

Accepted: August 23, 2025

Published: August 29, 2025

doi: 10.63454/jbs20000055

ISSN: 3049-3315

Volume 1; Issue 10

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Abstract:  Glycated hemoglobin (HbA1c) has long been established as the cornerstone biomarker for diagnosis, monitoring, and prognostication of type 2 diabetes mellitus (T2DM). It reflects average glycemic exposure over the preceding two to three months and correlates strongly with the risk of microvascular complications. Despite its widespread clinical utility, HbA1c has several biological and analytical limitations that may compromise its accuracy in certain populations and clinical conditions. Emerging glycemic markers and continuous glucose monitoring technologies are increasingly being explored as complementary or alternative tools. This mini-review revisits the strengths and limitations of HbA1c in T2DM and discusses emerging alternatives that may enhance personalized diabetes care..

Keywords: HbA1c; type 2 diabetes mellitus; glycemic control; biomarkers; continuous glucose monitoring

1. Introduction

Type 2 diabetes mellitus (T2DM) represents a profound and escalating global health challenge. The condition is fundamentally defined by a state of chronic hyperglycemia, stemming from a dual pathogenesis of insulin resistance in peripheral tissues and a progressive relative deficiency in insulin secretion from pancreatic beta-cells. The sustained elevation of blood glucose is a key driver of systemic damage, making the accurate assessment of long-term glycemic control a critical objective in clinical management. Precise measurement is essential not only for diagnostic clarity but also for tailoring therapeutic interventions, evaluating their efficacy, and, most importantly, for mitigating the elevated risk of devastating diabetes-related complications affecting the microvascular and macrovascular systems.

Since its standardization and introduction into routine clinical practice in the late 20th century, glycated hemoglobin (HbA1c) has emerged as the preeminent biomarker for this purpose. Its adoption revolutionized diabetes care by providing a single, integrative metric that reflects average glycemic exposure over the preceding two to three months, effectively smoothing out daily fluctuations [1]. Due to this robust utility and strong epidemiological correlation with complication risk, HbA1c has received formal endorsement from major international professional organizations, including the American Diabetes Association (ADA) and the World Health Organization (WHO), serving as a cornerstone for both the diagnosis and the ongoing monitoring of T2DM [2].  

Nevertheless, a growing body of clinical evidence underscores significant and inherent limitations of HbA1c. Its accuracy can be compromised by a variety of clinical conditions unrelated to glycemia, such as disorders affecting red blood cell turnover (e.g., anemia, hemolysis), hemoglobinopathies, renal insufficiency, and advancing age. Furthermore, as a static average, HbA1c conveys no information on glycemic variability, the frequency of hypoglycemic events, or postprandial glucose excursions—all factors now recognized as clinically significant. These constraints can lead to potential misclassification in diagnosis or a misleading representation of control in certain individuals. Consequently, there is a renewed and vigorous interest within the scientific and clinical communities in exploring alternative and adjunctive glycemic markers and monitoring technologies. This exploration aims to address the gaps left by HbA1c and to pave the way for a more comprehensive, precise, and personalized approach to diabetes management.

This review provides a comprehensive synthesis of human microbiome metagenomics. We detail its methodological foundations, summarize its contributions to understanding health and disease, and evaluate its translational potential in clinical medicine. Finally, we discuss current limitations and outline future research directions, including the integration of multi-omics data, artificial intelligence, and synthetic biology, which are poised to drive the next generation of microbiome-based interventions [11].

2. Biochemical basis of HbA1c 

The formation of glycated hemoglobin (HbA1c) is a quintessential example of a non-enzymatic biochemical process known as the Maillard reaction, which occurs within circulating red blood cells (erythrocytes). This irreversible reaction involves the covalent bonding between circulating glucose in the plasma and specific amino acid residues on the hemoglobin protein. The primary site for this glycation is the N-terminal valine of the beta-globin chain, resulting in a stable ketoamine adduct designated as HbA1c. 

The concentration of HbA1c in the blood is a direct function of two key variables: the magnitude and duration of ambient blood glucose exposure, and the lifespan of the erythrocyte itself, which averages approximately 120 days [3]. Since glycation is a continuous, time- and concentration-dependent process, erythrocytes accumulate higher levels of glycated hemoglobin when exposed to persistently elevated glucose concentrations throughout their lifespan. Consequently, the measured HbA1c value provides a time-integrated average of plasma glucose levels, effectively smoothing out daily and weekly fluctuations.

While the HbA1c level reflects average glycemia over the full erythrocyte life cycle, it does not represent a linear average of the preceding three to four months. The contribution of glucose exposure is weighted more heavily toward the most recent  period—approximately the prior 8 to 12 weeks—due to the natural senescence and turnover of red blood cells [4]. This means that recent glycemic changes have a proportionally greater impact on the HbA1c result compared to glucose levels from three to four months prior, making it a responsive, though not instantaneous, indicator of glycemic trends.

3. Clinical strengths of HbA1c

3.1 Indicator of long-term glycemic control
The principal clinical advantage of HbA1c is its provision of a stable, integrated overview of chronic glycemic exposure. Unlike fasting or postprandial glucose measurements, which represent a single point in time, HbA1c synthesizes information over an extended period (Figure 1). This eliminates the need for patient fasting and reduces the impact of daily stress  or acute illness on the result, offering unparalleled convenience and reducing pre-test variability for both patients and clinicians [5]. This characteristic solidifies its role as a foundational metric in the longitudinal management of diabetes.

Figure 1. HbA1c in type 2 diabetes. This illustrates the strengths of HbA1c in T2D/T2DM, its limitations, and emerging alternatives for assessing glycemic control.

 

 

 

3.2 Predictor of diabetic complications
The prognostic value of HbA1c is robustly validated by large-scale epidemiological and interventional studies. Seminal trials, most notably the United Kingdom Prospective Diabetes Study (UKPDS), established a continuous, log-linear relationship between HbA1c levels and the risk of developing specific microvascular complications. This evidence demonstrated that for every percentage point reduction in HbA1c, there was a corresponding, significant decrease in the incidence of retinopathy, nephropathy, and neuropathy [6]. This strong correlation forms the bedrock of evidence-based treatment targets aimed at complication prevention.

3.3 Standardization and reproducibility
Widespread clinical reliance on HbA1c has been enabled by rigorous international standardization efforts. Programs led by entities such as the National Glycohemoglobin Standardization Program (NGSP) in the United States and the International Federation of Clinical Chemistry (IFCC) have established universal reference methods and stringent certification criteria for laboratories and assay manufacturers. This harmonization ensures that a reported HbA1c value of, for instance, 7.0%, is analytically comparable across different testing sites and over time, which is critical for consistent diagnosis and reliable monitoring of treatment efficacy [7].

4. Pitfalls and limitations of HbA1c

4.1 Conditions affecting red blood cell turnover
The accuracy of HbA1c is fundamentally dependent on a normal erythrocyte lifespan. Numerous clinical conditions that alter red blood cell kinetics can therefore lead to clinically significant misinterpretation. For example, hemolytic anemia or recent blood transfusions shorten erythrocyte exposure to glucose, potentially causing a falsely low HbA1c. Conversely, iron-deficiency anemia or splenectomy may prolong red cell life, leading to a falsely elevated reading. Furthermore, hemoglobin variants (e.g., HbS, HbC) can interfere with some assay methodologies. Chronic kidney disease and pregnancy are also states where HbA1c may not reliably reflect mean glycemia due to complex physiological changes [8].

4.2 Ethnic and interindividual variability
Population studies have identified differences in HbA1c levels across ethnic groups that persist after adjustment for measured blood glucose levels. This suggests the presence of biological or genetic factors—potentially related to differences in erythrocyte glycation rates or lifespan—that create variability independent of true glycemic control. Such differences raise concerns about the potential for systematic misdiagnosis or underestimation of risk in certain populations when using universal HbA1c diagnostic thresholds [9].

4.3 Lack of glycemic variability assessment
A critical shortcoming of HbA1c is its nature as a composite average. It conveys no data on the stability of glucose control. Two patients with an identical HbA1c of 7.0% can have vastly different glycemic profiles: one with stable glucose readings and another with extreme swings between hyperglycemia and hypoglycemia. HbA1c fails to capture these short-term fluctuations, the frequency and severity of hypoglycemic events, and postprandial glucose spikes, all of which have independent associations with oxidative stress, endothelial dysfunction, and patient quality of life [10].

4.4 Limited utility in acute glycemic changes
Due to its dependence on the slow turnover of red blood cells, HbA1c is an inherently lagging indicator. It is insensitive to rapid changes in glycemic status following the initiation of a new therapy, after a major lifestyle intervention, or during an episode of acute illness. In such dynamic clinical scenarios, HbA1c provides delayed feedback, limiting its usefulness for making timely therapeutic adjustments [11].

5. Emerging alternatives and adjuncts to HbA1c

5.1 Fructosamine and glycated albumin
These serum markers measure the glycation of circulating proteins, primarily albumin. With a half-life of approximately 2-3 weeks, they reflect a shorter-term glycemic snapshot than HbA1c. Their principal utility lies in clinical situations where HbA1c is known to be unreliable, such as in hemodialysis patients, those with hemoglobinopathies, or during pregnancy. They offer a valuable alternative for assessing medium-term glycemic trends when erythrocyte-based measures are invalid [12].

5.2 1,5-Anhydroglucitol (1,5-AG)
1,5-AG is a monosaccharide reabsorbed in the renal tubules. Its reabsorption is competitively inhibited by glucosuria. Therefore, serum levels of 1,5-AG drop sharply during periods of hyperglycemia exceeding the renal threshold. It serves as a sensitive, inverse marker of short-term (days to a week) hyperglycemic excursions, particularly postprandial spikes, offering complementary data to the average glucose picture provided by HbA1c [13].

5.3 Continuous glucose monitoring (CGM)
CGM technology represents a paradigm shift by providing a high-resolution, real-time profile of interstitial glucose levels. It generates actionable metrics beyond an average, including:

• Time-in-range (TIR): The percentage of time spent within a target glucose range (typically 70-180 mg/dL).
• Glycemic variability: Measures such as standard deviation or coefficient of variation that quantify glucose swings.
• Hypoglycemia burden: The frequency and duration of low glucose events.
  These metrics offer a nuanced, dynamic, and comprehensive assessment of daily glycemic patterns that HbA1c alone cannot reveal [14].

5.4 Estimated average glucose (eAG) and time-in-range
The eAG is a calculated value derived from HbA1c, expressed in familiar glucose units (mg/dL or mmol/L) to aid patient understanding. More importantly, CGM-derived TIR is now recognized as a strong predictor of microvascular complications, with studies showing a significant correlation between lower TIR and increased risk. As a result, TIR is increasingly advocated as a co-primary endpoint in clinical trials and a key goal in personal therapy [15].

6. Integrating HbA1c with emerging tools

The future of glycemic assessment is not the replacement of HbA1c, but its intelligent integration within a multi-parameter toolkit. An individualized approach would strategically combine the validated, long-term risk perspective of HbA1c with the dynamic insights from shorter-term markers (like glycated albumin) and the real-time pattern analysis from CGM. For instance, a patient with a stable HbA1c but frequent hypoglycemia (identified by CGM) requires a different therapeutic strategy than one with the same HbA1c and stable glucose readings. This integrated model enables more precise, personalized, and proactive diabetes management [16].

The landscape of diabetes management is rapidly evolving with advances in digital health, sophisticated wearable sensors, and artificial intelligence. Future strategies will likely move beyond a one-size-fits-all HbA1c target toward personalized glycemic goals that also optimize time-in-range and minimize variability. The integration of data from CGMs, other biomarkers, and potentially non-invasive monitors into unified digital platforms will empower both clinicians and patients. Furthermore, regulatory and clinical guideline bodies are expected to increasingly adopt CGM-based metrics as standardized outcomes for both routine care and clinical research, driving a more holistic and effective approach to diabetes care [17].

8. Conclusions
Glycated hemoglobin (HbA1c) has rightfully maintained its status as the cornerstone biomarker for the management of type 2 diabetes mellitus (T2DM) for decades. Its enduring clinical value is anchored in its unique combination of practical simplicity, international analytical standardization, and a robust, evidence-based correlation with the long-term risk of microvascular complications. As a single, integrated measure of average glycemic exposure over approximately three months, it provides an indispensable foundation for establishing diagnoses, setting treatment targets, and monitoring therapeutic efficacy at a population level.

Despite these considerable strengths, a comprehensive review of the evidence underscores that HbA1c is not an infallible metric. Its interpretation requires critical awareness of significant biological and analytical limitations. Conditions affecting erythropoiesis or erythrocyte survival—such as anemia, hemoglobinopathies, and chronic kidney disease—can lead to misleadingly high or low values. Furthermore, HbA1c’s nature as a static average renders it blind to critical dimensions of dysglycemia, including glycemic variability, hypoglycemic burden, and postprandial excursions, all of which have independent clinical significance for both complications and quality of life.

Consequently, the evolving landscape of diabetes care is increasingly characterized by a paradigm of complementary assessment. Emerging tools, most notably continuous glucose monitoring (CGM), offer a transformative, high-resolution view of daily glucose patterns, providing actionable metrics like time-in-range and glycemic variability. Similarly, short-term circulating biomarkers such as glycated albumin and 1,5-anhydroglucitol serve as valuable adjuncts in clinical scenarios where HbA1c is known to be unreliable.  Therefore, the future of optimal diabetes management lies not in discarding HbA1c, but in strategically integrating it within a multimodal framework. A truly personalized approach will judiciously combine the validated long-term prognostic power of HbA1c with the dynamic, real-time insights from CGM and the targeted utility of alternative biomarkers. This balanced, patient-centered strategy empowers clinicians to move beyond a one-dimensional glycemic average, enabling more precise, proactive, and effective care tailored to the individual pathophysiology and life circumstances of each person living with T2DM.

Author Contributions: Conceptualization, M.T.; methodology, M.T.; software, M.T.; formal analysis, M.T.; investigation, M.T.; resources, M.T.; data curation, M.T.; writing—original draft preparation, M.T.; writing—review and editing, M.T.; visualization, M.T.; supervision, M.T.; project administration, M.T.; funding acquisition, M.T. The authors have read and agreed to the published version of the manuscript.

Funding: Not applicable.

Acknowledgments: We are grateful to the Department of Biochemistry, College of Science, University of Jeddah, Jeddah-21589 Saudi Arabia for providing us all the facilities to carry out the entire work.

Conflicts of Interest: The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Institutional Review Board Statement: We have already mentioned in details in the method section.

Informed Consent Statement: We have already mentioned in details in the method section.

Data Availability Statement: All the related data are supplied in this work or have been referenced properly.

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