Continuous glucose monitoring (CGM) has become an essential tool in modern diabetes management, providing insight into glucose patterns and variability not captured by glycated hemoglobin (HbA1c) alone.¹ Current evidence indicates that glycemic assessment must extend beyond HbA1c, particularly for individuals with type 2 diabetes (T2D) who face an elevated risk of microvascular and cardiometabolic complications.¹ Evolving clinical guidance supports a multidimensional approach to glycemia, positioning CGM as a critical instrument for therapy selection, titration, treatment intensification, and individualized lifestyle modification.¹ At ATTD-ASIA 2025, Dr. Daphne Gardner from Singapore General Hospital highlighted the practical benefits of CGM in T2D management, emphasizing its role in detecting glycemic excursions, guiding therapy adjustments, and supporting patient-centered care.¹

Recent updates from the American Diabetes Association (ADA) 2026 Standards of Care continue to emphasize established targets, including HbA1c <7% and recommended time-in-range (TIR) thresholds.¹ The guidelines increasingly prioritize comorbidities such as atherosclerotic cardiovascular disease (ASCVD), heart failure (HF), chronic kidney disease (CKD), and metabolic dysfunction-associated steatotic liver disease (MASLD).¹ Glucagon-like peptide-1 (GLP-1) receptor agonists and sodium-glucose cotransporter 2 (SGLT2) inhibitors are now featured prominently due to their broad benefits across these domains.¹ Notably, therapy-intensification algorithms are beginning to reference “glycemia” rather than HbA1c specifically, reflecting an increased recognition that HbA1c alone does not provide adequate direction for treatment adjustments.¹

This shift is supported by multiple datasets showing that while HbA1c correlates with mean glucose, it does not reliably predict hypoglycemia.¹ Studies demonstrate a non-linear and weak relationship between HbA1c and time below range (TBR).¹ Individuals with similar HbA1c values may have markedly different glycemic variability (GV), and GV is a major determinant of both hypoglycemia and goal attainment.¹ CGM-derived coefficient of variation (CV) is therefore essential: lower CV (<20%) is consistently associated with higher TIR independent of mean glucose.¹ Consequently, treatment decisions based solely on HbA1c may result in inappropriate intensification or missed opportunities for de-intensification.¹

The clinical implications for therapy selection are significant.¹ As patients approach HbA1c targets, hypoglycemia risk is less determined by the absolute HbA1c level and more by underlying GV.¹ Many glucose-lowering medications reduce mean glucose, but only CGM can distinguish whether GV is the barrier to achieving TIR, rather than inadequate dosing.¹ This differentiation directly influences decisions between basal insulin titration, initiation of prandial insulin, or introducing a GLP-1 agonist.¹

A clinical case demonstrates the utility of CGM-informed therapeutic decision-making.¹ A 55-year-old man with long-standing T2D, established coronary disease, fatty liver, and multiple oral antihyperglycemic agents presented with an HbA1c of 8.7% despite fasting SMBG values consistently ranging from 5-7mmol/L.¹ Standard treatment pathways would typically prompt further basal insulin titration or the introduction of prandial insulin.¹ CGM profiling, however, identified well-controlled fasting and nocturnal glucose levels, with substantial post-prandial hyperglycemia driving the elevated glycemia.¹ Additional basal insulin in this setting would likely have increased nocturnal hypoglycemia risk without addressing the predominant driver.¹ Subsequent initiation of a GLP-1 receptor agonist yielded marked improvements, including decreased GMI, increased TIR, stabilized GV, reduced post-prandial excursions, weight, HbA1c, decreased basal insulin requirements, and discontinuation of diamicron.¹ This case illustrates the precision achievable through CGM-guided therapeutic adjustment compared with reliance on HbA1-based assumptions.¹

CGM also provides powerful support for dietary and behavioral modification.¹ Another patient with T2D for 20 years and HbA1c of 13.5% demonstrated substantial improvement through real-time CGM-guided behavioral changes.¹ Without intensifying pharmacotherapy beyond minimal titration of basal insulin, CGM-guided self-reflection enabled significant improvement in glycemic metrics within three months.¹ These changes occurred entirely through dietary adjustment and meal-pattern awareness prompted by sensor data.¹ Analyses further indicate that greater sensor wear correlates with improved HbA1c, with meaningful benefit observed at approximately 70% usage, providing a practical benchmark to maintain ongoing behavioral benefit.¹

In resource-constrained environments, identifying individuals who derive the greatest benefit from CGM is essential.¹ Local datasets show that patients treated with sulfonylureas, premixed insulin, or basal-bolus regimens tend to exhibit higher GV and therefore achieve lower TIR at a given HbA1c.¹ These individuals may particularly benefit from CGM for both intensification and safe de-intensification, including identifying nocturnal hypoglycemia and excessive prandial excursions.¹ Conversely, patients treated with non-secretagogue oral agents generally show lower variability.¹ Prioritizing CGM for those with higher GV may therefore maximize clinical value in primary care settings.¹

Collectively, the evidence supports a paradigm in which optimal glycemic management extends beyond HbA1c to incorporate TIR and GV.¹ CGM facilitates more precise therapeutic decision-making, improves hypoglycemia detection, enables safer and targeted insulin titration, while informing individualized dietary modification.¹ Taken together, these capabilities position CGM as a critical component of structured and scalable patient-centered management for individuals with T2D.¹