# Real-Time Continuous Glucose Monitoring in Adults with Type 2 Diabetes Managed Solely with Oral Medications: A Comprehensive Synthesis of Evidence for HbA1c Reduction at 12 Months

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### Background and Context

Type 2 diabetes mellitus (T2DM) represents one of the most consequential chronic disease burdens of the twenty-first century. The International Diabetes Federation estimated that 537 million adults aged 20–79 were living with diabetes globally in 2021, with projections reaching 783 million by 2045 if current trends continue (PMC12918550). T2DM accounts for the large majority of all diabetes cases worldwide, and the economic and human costs of suboptimal glycemic control — including retinopathy, nephropathy, neuropathy, and cardiovascular disease — are enormous. Effective glycemic management is therefore not merely a biochemical target but a cornerstone of preventing long-term microvascular and macrovascular complications.

The traditional standard for monitoring glycemic control in T2DM has been self-monitoring of blood glucose (SMBG) via fingerstick capillary testing, supplemented by periodic measurement of glycated hemoglobin (HbA1c) in the clinic. HbA1c reflects average glucose exposure over approximately 2–3 months and remains the primary regulatory and clinical endpoint for assessing glycemic management. However, SMBG provides only intermittent snapshots of glucose levels, potentially missing clinically important fluctuations such as postprandial hyperglycemia, nocturnal hypoglycemia, and rapid glucose excursions (PMC12413689, PMC12875926). The pain and inconvenience of fingerstick testing also contribute to poor adherence, particularly in patients who are not on insulin and therefore perceive less immediate clinical necessity for frequent glucose checks.

Real-time continuous glucose monitoring (rtCGM) systems measure interstitial glucose concentrations every 1–5 minutes, transmitting data continuously to a receiver or smartphone application, and most modern systems include configurable alarms for impending hypoglycemia or hyperglycemia (PMC12875926). Unlike SMBG, rtCGM provides trend arrows indicating the direction and rate of glucose change. The technology was originally developed and validated primarily for insulin-dependent patients — particularly those with type 1 diabetes — where the ability to detect and respond to rapid glucose changes is most immediately life-saving. However, over the past decade, there has been growing interest in extending rtCGM to the much larger population of adults with T2DM who are managed with oral antihyperglycemic agents (OAAs) alone, without insulin. This population represents a distinct clinical context: the risk of severe hypoglycemia is lower, the mechanism of glycemic improvement from CGM is more likely behavioral (dietary modification, physical activity, medication adherence) than pharmacological (insulin dose adjustment), and the cost-benefit calculus for a relatively expensive technology is less immediately obvious.

The specific question addressed in this review — whether rtCGM yields a statistically significant reduction in HbA1c at 12 months compared with routine clinical care in adults with T2DM treated solely with oral medications — is clinically important for several reasons. First, the non-insulin-treated T2DM population is numerically the largest subgroup of people with diabetes, and even modest improvements in glycemic control at a population level could translate into substantial reductions in complication burden. Second, regulatory agencies including the U.S. Food and Drug Administration (FDA) and payers such as the Centers for Medicare and Medicaid Services (CMS) have increasingly considered coverage of CGM for non-insulin-treated T2DM, making the evidence base directly relevant to health policy. Third, the mechanism by which rtCGM might improve glycemic control in this population — through behavioral feedback rather than insulin titration — raises distinct questions about the durability of any benefit and the optimal implementation strategy. This review synthesizes the available randomized controlled trial (RCT) evidence, systematic reviews, and meta-analyses bearing on this question, with particular attention to the 12-month time horizon specified in the clinical question.

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### Mechanistic Pathways by Which rtCGM May Improve Glycemic Control in Non-Insulin-Treated T2DM

#### Biological Feedback and Behavioral Self-Regulation

The primary mechanism by which rtCGM is hypothesized to improve glycemic control in non-insulin-treated T2DM is through biological feedback — the provision of real-time, personalized glucose data that enables individuals to observe the direct consequences of their dietary choices, physical activity, and medication adherence on their glucose levels. This mechanism is conceptually distinct from the insulin-dose-adjustment pathway that drives CGM benefit in type 1 diabetes or insulin-treated T2DM. In the non-insulin-treated context, the glucose data cannot be used to titrate a rapid-acting insulin bolus; instead, the feedback is hypothesized to motivate behavioral change through enhanced self-awareness, self-efficacy, and self-regulation.

A 2024 systematic review and meta-analysis (Poole et al.) examining CGM as a biological feedback behavior change tool across 25 RCTs involving 2,996 participants found that CGM-based biological feedback reduced HbA1c by 0.28 percentage points (95% CI: 0.15–0.42; p<0.001) compared with control conditions not using CGM, with high heterogeneity (I²=88.5%) (PMC11668089). Critically, this review included studies across diverse populations and CGM types, and the subgroup analysis found no statistically significant difference in HbA1c reduction between participants who used insulin and those who did not (p=0.798 for the subgroup interaction), suggesting that the behavioral feedback mechanism operates independently of insulin use. The same meta-analysis found that TIR was increased by 7.4% (95% CI 2.0, 12.8, p=0.008; I²=80.5%) in the intervention group compared to the comparison, a magnitude that surpasses the threshold of 5% for clinical significance and is consistent with other meta-analyses in this area (PMC11668089).

Self-regulation theory provides a theoretical framework for understanding how CGM feedback translates into behavioral change. A small Taiwanese RCT (n=66) explicitly tested the integration of CGM with a structured self-regulation education program in T2DM patients with HbA1c >8% (PMC11944990). The CGM group wore a Medtronic Guardian Connect System for seven days and received approximately one hour of self-regulation education plus daily phone consultations. Within-group analysis showed a significant HbA1c reduction from 9.37% to 8.79% (a 6.19% decrease; p=0.017; effect size dz=0.83) in the CGM group, while the control group's reduction from 9.45% to 9.08% was non-significant (p=0.289). The CGM group also demonstrated a significant improvement in diabetes health behavior scores from 61.61 to 66.42 (a 7.81% increase; p=0.010; effect size=0.47), and critically, the control group experienced a significant decline in self-efficacy scores from 72.70 to 68.21 (6.18% decrease; p=0.018), while the CGM group's slight decline from 71.82 to 70.61 was non-significant (p=0.647). These findings suggest that CGM may not only improve glycemic outcomes but also protect against the erosion of self-efficacy that can occur over time in patients receiving standard diabetes education alone. However, between-group differences did not reach statistical significance for any outcome, limiting causal inference.

#### Dietary Modification and Carbohydrate Reduction

A second mechanistic pathway through which rtCGM may improve glycemic control in non-insulin-treated T2DM is through dietary modification, particularly reduction in carbohydrate intake. The real-time visualization of postprandial glucose excursions provides immediate, personalized feedback on the glycemic impact of specific foods, which may motivate patients to reduce carbohydrate consumption or shift toward lower-glycemic-index food choices. A 2026 systematic review and meta-analysis specifically examining the effects of CGM on physical activity and diet in diabetes (PMC12918550) pooled data from multiple RCTs and found that CGM use was associated with significant reductions in both daily caloric intake (MD: −70.81 kcal/day; 95% CI: −132.93 to −8.69; p=0.03; I²=0%) across 6 RCTs (n=654) and daily carbohydrate consumption (MD: −19.88 g/day; 95% CI: −27.74 to −12.01; p<0.00001; I²=35%) across 8 RCTs (n=793) compared with controls (PMC12918550). Sensitivity analyses confirmed the robustness of the carbohydrate finding across leave-one-out iterations.

The MOBILE trial subgroup analysis (PMC9127836) provides additional mechanistic insight. In this trial of 175 adults with T2DM on basal insulin (not purely oral-agent-treated, but informative for mechanism), the glycemic improvements with CGM were achieved without significant differences in total daily insulin dose, initiation of prandial insulin, or other medication changes between groups. This finding strongly suggests that the mechanism of glycemic improvement in less intensively treated patients is behavioral — specifically, modifications in diet, physical activity, and medication adherence — rather than pharmacological intensification. The authors explicitly noted that "the marked reduction in time spent with glucose >250 mg/dL in the subgroup with baseline HbA1c values ≥10% was achieved without significant differences in diabetes medication changes between groups, including the initiation of prandial insulin" (PMC9127836).

#### Physical Activity Enhancement

A third mechanistic pathway involves increased physical activity. The real-time visualization of glucose responses to exercise — including the glucose-lowering effect of aerobic activity and the potential for hypoglycemia during or after exercise — may motivate patients to engage in more physical activity and to time their exercise more strategically. The Xu et al. (2026) meta-analysis found that CGM was associated with a significant increase in daily physical activity time (MD: +16.21 min/day; 95% CI: 10.26 to 22.16; p<0.0001; I²=14%) across 8 RCTs (n=593), but no significant between-group differences were found for daily moderate-to-vigorous physical activity (MVPA) time (MD: +1.60 min/day; 95% CI: −4.42 to 7.63; p=0.60; I²=0%) or weekly MET expenditure (MD: −39.50; 95% CI: −135.13 to 56.13; p=0.42; I²=71%) (PMC12918550), suggesting that the observed increases in physical activity time may reflect increases in lower-intensity activity rather than structured vigorous exercise.

A Chinese RCT comparing real-time versus retrospective flash glucose monitoring in T2DM patients on premix insulin (PMC8867069) provides a particularly clean mechanistic test of the behavioral pathway. By using retrospective (blinded) FGM as the control — thereby controlling for physician-led medication adjustments — the study isolated the effect of real-time glucose visibility on patient behavior. Daily exercise time increased by 8.0 min/day in the unblinded FGM group but decreased by 10.1 min/day in the blinded group (p=0.002 for group×time interaction), and post-meal blood glucose, particularly after lunch and supper, was lower in the unblinded group during the third FGM period (p<0.05 for both). Medication changes were similar between groups, confirming that the glycemic benefit of real-time visibility was mediated through behavioral change rather than pharmacological adjustment. While this study enrolled insulin-treated patients, the mechanistic principle — that real-time glucose feedback drives behavioral modification independent of medication changes — is directly applicable to the oral-agent-only population.

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### Clinical Evidence and Implications

#### The MOBILE Trial: The Landmark RCT in Basal-Insulin-Treated T2DM

The most methodologically rigorous and clinically influential RCT examining rtCGM in T2DM patients managed with less intensive regimens is the MOBILE trial (Martens et al., 2021), which is extensively discussed in the systematic review literature (PMC12413689, PMC9127836, PMC12875926). As summarized in these reviews, the MOBILE trial enrolled 175 adults with T2DM treated with basal insulin (but not prandial insulin) across 15 U.S. primary care centers, randomized 2:1 to rtCGM using the Dexcom G6 (n=116) or blood glucose monitoring (BGM) with SMBG (n=59) for 8 months. Participants were recruited from primary care practices rather than endocrinology specialty settings, making this a pragmatic trial with high external validity for real-world primary care.

The primary outcome showed a statistically significant between-group difference in HbA1c reduction of −0.4% (95% CI: −0.8% to −0.1%; p=0.02) favoring rtCGM over BGM at 8 months, with TIR increasing from 40% to 58% with CGM versus 40% to 45% with BGM (between-group difference +15%; 95% CI: 8%–23%; p<0.001), time above 250 mg/dL reduced by 16% (p<0.001), and mean glucose 179 mg/dL vs. 206 mg/dL (difference −26 mg/dL; 95% CI: −41 to −12; p<0.001) (PMC12413689, PMC9127836). These are clinically meaningful improvements across multiple glycemic metrics. Importantly, the MOBILE trial was conducted in basal-insulin-treated patients, not purely oral-agent-treated patients, which is a critical distinction for the specific question addressed in this review.

The post hoc subgroup analysis of the MOBILE trial (PMC9127836) demonstrated that the magnitude of glycemic benefit from rtCGM was substantially greater in participants with worse baseline glycemic control. For participants with baseline HbA1c ≥10.0% (CGM n=26, BGM n=9), the between-group difference in TIR was +32% (95% CI: 11%–53%; p=0.004), and the between-group difference in HbA1c reduction was −1.52% (95% CI: −2.55% to −0.50%; p=0.005). Forty-two percent more participants in the ≥10.0% subgroup achieved a ≥1% HbA1c reduction with CGM versus BGM (adjusted difference 42%; p=0.02). Prolonged hyperglycemic events (≥8 hours >300 mg/dL) were reduced by 52% in the ≥10.0% subgroup (p=0.01). These subgroup findings are hypothesis-generating rather than confirmatory, given the small sample sizes and absence of multiple-comparison adjustment, but they suggest that patients with the worst baseline glycemic control may derive the greatest benefit from rtCGM — a pattern consistent with findings from other diabetes treatment interventions (PMC9127836).

#### rtCGM in Multiple-Daily-Injection T2DM: Evidence from Systematic Reviews

Beck et al. (2017) enrolled 158 adults with T2DM receiving multiple daily insulin injections (MDI) across 25 U.S. endocrinology practices, as reported in the Xu et al. (2026) meta-analysis (PMC12875926). Participants had a mean age of 60 years and were randomized to rtCGM (n=79) or usual care (n=79) for 24 weeks. The pooled data from this and related trials contributed to the overall meta-analytic estimate of −0.20% (95% CI: −0.34 to −0.06; p=0.004) favoring rtCGM (PMC12875926). This trial enrolled insulin-treated patients, not oral-agent-only patients, but it is frequently cited as foundational evidence for rtCGM efficacy in T2DM and is included in all major meta-analyses of the topic.

#### The Furler et al. (2020) GP-OSMOTIC Trial: Professional CGM in T2DM

The GP-OSMOTIC trial (Furler et al., 2020) is one of the most directly relevant studies to the specific question of this review, as it enrolled adults with T2DM managed with non-insulin glucose-lowering drugs or insulin, with a substantial proportion on oral agents alone (PMC12413689). This pragmatic, two-arm, open-label, individually randomized controlled trial enrolled 299 adults with T2DM across 25 general practices in Victoria, Australia, randomized to professional-mode flash glucose monitoring at three-month intervals for 12 months or usual clinical care.

The GP-OSMOTIC trial showed a significant HbA1c difference at 6 months (−0.5%; p=0.0001) that narrowed and became non-significant at 12 months (−0.3%; p=0.059), suggesting attenuation of benefit over time (PMC12413689). The percentage of time in target glucose range at 12 months was significantly higher in the intervention group (+7.9%; 95% CI: 2.3–13.5; p=0.006). The GP-OSMOTIC trial is notable for its 12-month follow-up, its pragmatic primary care setting, and its inclusion of patients on oral agents alone — making it one of the most directly relevant trials to the user's question. The near-miss on HbA1c significance at 12 months (p=0.059) while achieving significance at 6 months raises important questions about the durability of CGM-driven glycemic improvements over time.

#### The Moon et al. (2023) Trial: Intermittent rtCGM in Non-Insulin-Treated T2DM

The Moon et al. (2023) trial provides important evidence on the dose-response relationship between CGM exposure frequency and glycemic outcomes in non-insulin-treated T2DM (PMC12413689). This randomized prospective study enrolled 61 non-insulin-treated T2DM patients uncontrolled with oral antidiabetic drugs (baseline HbA1c 8.2% ± 0.5%), of whom 48 completed the study. Participants were randomized to one session of rtCGM (Treatment Group 1), two sessions of rtCGM three months apart (Treatment Group 2), or blinded CGM only plus education (control group).

At three months, both TG1 (−0.60%; p=0.044) and TG2 (−0.64%; p=0.014) showed significant HbA1c reductions versus control. At six months, only TG2 maintained a significant HbA1c reduction (−0.68%; p=0.018), while TG1's reduction was no longer statistically significant. This dose-response finding — that two intermittent rtCGM sessions led to sustained HbA1c reduction while a single session did not — has important implications for clinical implementation. It suggests that periodic "doses" of CGM data may be necessary for lasting glycemic effects, and that a single brief CGM exposure is insufficient to drive durable behavioral change. The trial also found that HbA1c reduction was significant only in those performing SMBG ≥1.5 times/day at three and six months, suggesting that CGM benefit may be amplified in patients who are already engaged in glucose self-monitoring.

#### The Wada et al. (2020) Trial: Flash Glucose Monitoring in Non-Insulin-Treated T2DM

The Wada et al. (2020) multicenter, open-label, randomized parallel-group RCT enrolled 100 adults with non-insulin-treated type 2 diabetes across five Japanese hospitals (PMC12413689). Participants were randomized 1:1 to flash glucose monitoring (FGM; n=49) or SMBG (n=51). At 24 weeks, the between-group HbA1c difference was −0.29% (−3.2 mmol/mol; p=0.022), which was statistically significant. The FGM group also showed significant improvements in treatment satisfaction, mean glucose levels, glucose standard deviation, mean amplitude of glycemic excursions, and time in hyperglycemia compared with SMBG. This trial is notable for its 24-week follow-up and its exclusive enrollment of non-insulin-treated patients, making it directly relevant to the user's question. However, the 24-week duration falls short of the 12-month threshold specified in the clinical question.

#### The Haak et al. (2017) Trial: Flash CGM in Insulin-Treated T2DM

The Haak et al. (2017) open-label RCT enrolled 224 adults with T2DM on intensive insulin therapy across 26 European diabetes centers, as referenced in the Alharbi et al. (2025) systematic review (PMC12413689). Participants were randomized to flash glucose-sensing technology (n=149) or SMBG (n=75) for 26 weeks. The primary outcome showed no significant between-group HbA1c difference. However, time in hypoglycemia <3.9 mmol/L was significantly reduced by 0.47 ± 0.13 h/day (p=0.0006), and time in hypoglycemia <3.1 mmol/L was reduced by 0.22 ± 0.07 h/day (p=0.0014). Treatment satisfaction was significantly higher in the flash CGM group (DTSQ 13.1 ± 0.50 vs. 9.0 ± 0.72; p<0.0001). As reported in the Alharbi et al. (2025) systematic review, SMBG frequency was reduced from 3.8 ± 1.4 to 0.3 ± 0.7 tests/day in the flash CGM group, indicating that patients largely substituted CGM for fingerstick testing rather than using both simultaneously (PMC12413689). This trial enrolled insulin-treated patients and found no overall HbA1c benefit, but demonstrated important secondary benefits in hypoglycemia reduction and treatment satisfaction.

#### Systematic Reviews and Meta-Analyses: Pooled Evidence

The most comprehensive and directly relevant systematic review and meta-analysis for the user's question is the 2026 review by Xu and colleagues (PMC12875926), which specifically evaluated rtCGM versus SMBG in adults with T2DM across 11 RCTs (n=789; 437 rtCGM, 352 SMBG) published between 2008 and 2023. The pooled HbA1c reduction with rtCGM versus SMBG was −0.20% (95% CI: −0.34 to −0.06; p=0.004; I²=27%), which was statistically significant with low heterogeneity. This is a modest but statistically robust effect. The review also found that rtCGM significantly increased TIR by 7.41% (95% CI: 3.23–11.59; p=0.0005; I²=22%), reduced TAR by −6.93% (95% CI: −11.21 to −2.65; p=0.002; I²=29%), reduced TBR by −0.26% (95% CI: −0.44 to −0.08; p=0.005; I²=50%), and reduced glucose variability (coefficient of variation) by −1.06% (95% CI: −1.54 to −0.58; p<0.0001; I²=0%). Importantly, the TIR increase of 7.41% and the TAR reduction of 6.93% both exceed the 5% threshold considered clinically relevant by international consensus recommendations (PMC12875926).

The subgroup analysis in this meta-analysis found a numerically larger HbA1c reduction in Asian studies (−0.44%; 95% CI: −0.88 to 0.01; p=0.05) compared with Western studies (−0.17%; 95% CI: −0.32 to −0.03; p=0.02), though the between-group difference was not statistically significant (p=0.27) and should be interpreted cautiously given the substantial imbalance in sample sizes (87 vs. 702 participants). Studies with multiple centers reported a significant HbA1c reduction (−0.33%; 95% CI: −0.50 to −0.15; p=0.0003), while single-center studies showed no significant effect, with a significant subgroup difference (p=0.02). No significant subgroup differences were observed for number of participants (p=0.71), insulin use (p=0.34), intervention period (p=0.83), or sensor usage pattern (p=0.79). The non-significant subgroup difference by insulin use (p=0.34) is particularly relevant to the user's question, as it suggests that the HbA1c benefit of rtCGM may not differ meaningfully between insulin-treated and non-insulin-treated T2DM patients.

The Alharbi et al. (2025) systematic review synthesized 11 RCTs published between 2016 and 2023 encompassing approximately 1,384 adults with T2DM and synthesized findings narratively due to substantial clinical and methodological heterogeneity (PMC12413689). The review confirmed the key findings from individual trials: Martens et al. reported a statistically significant between-group HbA1c reduction of −0.4% (95% CI: −0.8% to −0.1%; p=0.02) and a 15% increase in TIR (59% vs. 43%; p<0.001); Furler et al. found a significant TIR improvement of +7.9% (95% CI: 2.3–13.5; p=0.006) at 12 months; and Moon et al. demonstrated that two intermittent rtCGM sessions led to sustained HbA1c reduction of −0.68% (p=0.018) at six months. The review also highlighted that Haak et al. found no overall HbA1c difference but reported significant reductions in time spent in hypoglycemia (<3.9 mmol/L) of 0.47 ± 0.13 h/day (p=0.0006) and higher treatment satisfaction scores (DTSQ 13.1 vs. 9.0; p<0.0001).

The 2024 meta-analysis by Poole and colleagues (PMC11668089), which examined CGM as a behavior change tool across 25 RCTs (n=2,996) in populations with and without diabetes, found a pooled HbA1c reduction of 0.28% (95% CI: 0.15–0.42; p<0.001; I²=88.5%). Sensitivity analyses consistently reproduced this finding: removing influential cases (MD −0.29%; I²=78.0%), removing high-risk-of-bias studies (MD −0.29%; I²=91.2%), removing studies with conflicts of interest (MD −0.32%; I²=85.4%), and restricting to studies ≥12 weeks (MD −0.24%; I²=87.9%). The robustness of the HbA1c reduction across all sensitivity analyses is notable, though the persistently high heterogeneity (I²=78–91% across conditions) indicates substantial variability in effect sizes across studies that is not fully explained by the pre-specified subgroup analyses.

#### The Ajjan et al. (2019) Trial: Multiple Sensor Wears in Insulin-Treated T2DM

The Ajjan et al. (2019) trial, referenced in the Alharbi systematic review (PMC12413689), enrolled 148 adults with T2DM on insulin therapy and randomized them to SMBG alone (Group A), SMBG plus two Libre Pro sensor wears (Group B), or SMBG plus four Libre Pro sensor wears (Group C). Group C showed a significant within-group HbA1c reduction of 4.9 ± 8.8 mmol/mol (0.44% ± 0.81%; p=0.0003), and HbA1c was significantly lower in Group C versus Group A by 5.4 ± 1.79 mmol/mol (0.48% ± 0.16%; p=0.0041). No increase in hypoglycemia was observed (p=0.1795), and treatment satisfaction improved (p=0.0225). This trial was rated as having a high overall risk of bias by the Cochrane RoB 2 tool, which may affect the credibility of its findings (PMC12413689). Nevertheless, it provides additional evidence for a dose-response relationship between CGM exposure frequency and glycemic outcomes.

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### Dose-Response and Implementation Considerations

#### Frequency and Duration of CGM Use

The available evidence suggests a clear dose-response relationship between the frequency and duration of rtCGM use and the magnitude of glycemic benefit. The Moon et al. (2023) trial demonstrated that two intermittent rtCGM sessions (three months apart) led to sustained HbA1c reduction (−0.68%; p=0.018) at six months, whereas a single session did not produce sustained benefit (PMC12413689). The Ajjan et al. (2019) trial showed that four sensor wears produced a significant HbA1c reduction versus SMBG alone, while fewer wears did not (PMC12413689). Individual pilot data suggest that three episodic CGM wear periods over 8 weeks may produce TIR improvements but not statistically significant HbA1c reductions, and that benefits may not be sustained at 9 months without ongoing CGM use (PMC12413689).

The Xu et al. (2026) meta-analysis found no significant subgroup difference in HbA1c reduction between intermittent (MD −0.26%; 95% CI: −0.53 to 0.01; p=0.06) and continuous (MD −0.20%; 95% CI: −0.48 to 0.08; p=0.15) sensor usage patterns (p=0.79 for subgroup difference) (PMC12875926). However, this analysis was limited by the small number of studies in each subgroup and the heterogeneity of intermittent protocols across trials. The 2024 meta-analysis by Poole and colleagues (PMC11668089) similarly found no significant subgroup difference in HbA1c reduction by sensor wear duration (≤28 days: MD −0.30%; ≥29 days: MD −0.27%; p=0.867 for subgroup difference), though the confidence intervals were wide.

#### Baseline Glycemic Control as a Modifier of Benefit

Multiple lines of evidence converge on the finding that patients with worse baseline glycemic control derive greater benefit from rtCGM. The MOBILE trial subgroup analysis (PMC9127836) showed that the between-group TIR improvement grew from +14% for baseline HbA1c ≥8.5% to +32% for baseline HbA1c ≥10.0%, and the HbA1c reduction grew from −0.37% to −1.52% across the same range. The 2026 meta-analysis (PMC12875926) found a numerically larger HbA1c reduction in Asian studies (−0.44%) compared with Western studies (−0.17%), which may partly reflect the higher baseline HbA1c in Asian study populations. The 2024 meta-analysis (PMC11668089) found a numerically larger HbA1c reduction in studies with baseline HbA1c ≥8% (MD −0.33%) versus <8% (MD −0.24%), though the subgroup difference was not statistically significant (p=0.524). This pattern is consistent with the general principle in diabetes treatment research that those with the worst baseline control have the most room for improvement and therefore the greatest absolute treatment response.

#### The Role of Clinical Support and Education

The available evidence suggests that the glycemic benefit of rtCGM is amplified when combined with structured clinical support, education, and feedback. The GP-OSMOTIC trial (Furler et al., 2020) used professional CGM with clinician review at each three-month interval, and achieved a significant TIR improvement (+7.9%; p=0.006) at 12 months (PMC12413689). The Moon et al. (2023) trial found that HbA1c reduction was significant only in those performing SMBG ≥1.5 times/day, suggesting that CGM benefit is amplified in patients who are already engaged in glucose self-monitoring (PMC12413689). The 2024 meta-analysis (PMC11668089) found no significant subgroup difference in HbA1c reduction between studies with and without two-way communication (CGM feedback with 2-way communication: MD −0.28%; without: MD −0.30%; p=0.891), though the confidence intervals were wide and the analysis was underpowered.

A Korean RCT by Lee et al. (2023), referenced in the Alharbi et al. (2025) systematic review (PMC12413689), enrolled 294 adults with T2DM (HbA1c 7.5% ± 0.4%; no insulin) and randomized them to an FGM-based integrated digital health platform with individual guidance on diet, physical activity, weight, and blood pressure, a platform-only arm without individualized guidance, or usual care. HbA1c and weight were assessed at 12, 24, 36, and 48 weeks. This trial provides evidence that combining CGM with structured remote guidance in non-insulin-treated T2DM is feasible and may produce glycemic benefits beyond usual care, though the full quantitative results were not reported in the available synthesis (PMC12413689).

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### Safety Profile and Adverse Events

#### Hypoglycemia Risk

A critical safety consideration for rtCGM in non-insulin-treated T2DM is the risk of hypoglycemia. Because most oral antidiabetic agents (with the exception of sulfonylureas and meglitinides) carry a low intrinsic risk of hypoglycemia, the concern is primarily relevant for patients on sulfonylurea-containing regimens. The available evidence consistently shows that rtCGM does not increase hypoglycemia risk in T2DM patients, and may in fact reduce it through earlier detection and behavioral response.

The 2026 meta-analysis (PMC12875926) found no statistically significant difference in general hypoglycemia events between rtCGM and SMBG groups across two studies (n=176; pooled RD: 0.02; 95% CI: −0.02 to 0.07; p=0.31; I²=96%). Severe hypoglycemia and diabetic ketoacidosis showed no significant difference between groups (RD for each: −0.01; 95% CI: −0.05 to 0.03; p=0.71) (PMC12875926). The MOBILE trial subgroup analysis (PMC9127836) found that mean baseline time <54 mg/dL was 0.05%, 0.04%, 0.04%, and 0.08% for those with baseline HbA1c ≥8.5%, ≥9.0%, ≥9.5%, and ≥10.0%, respectively, with little change from baseline to follow-up in either treatment arm, confirming that rtCGM did not increase hypoglycemia risk even in the highest-risk subgroups.

The Haak et al. (2017) trial, which enrolled insulin-treated T2DM patients, found that flash CGM significantly reduced time in hypoglycemia <3.9 mmol/L by 0.47 ± 0.13 h/day (p=0.0006) and time in hypoglycemia <3.1 mmol/L by 0.22 ± 0.07 h/day (p=0.0014) compared with SMBG (PMC12413689). This finding suggests that rtCGM may actually reduce hypoglycemia burden in insulin-treated patients, though the mechanism in non-insulin-treated patients is less clear.

#### Device-Related Adverse Events

Device-related adverse events with rtCGM are generally mild and include skin reactions (erythema, irritation, adhesive reactions at the sensor insertion site), sensor failures, and connectivity issues. The 2026 meta-analysis (PMC12875926) found no statistically significant difference in skin reactions between rtCGM and SMBG groups across four studies (n=268; pooled RD: 0.01; 95% CI: −0.02 to 0.05; p=0.41; I²=54%). The CONCEPTT trial in pregnant women with type 1 diabetes (PMC5713979) reported that 49 (48%) of 103 CGM participants experienced skin reactions (bleeding, erythema, discomfort) compared with 8 (8%) of 104 control participants, though this population and device generation differ substantially from the non-insulin-treated T2DM context. The Taiwanese RCT (PMC11944990) reported that two participants experienced CGM device malfunctions or adhesive failures requiring reinsertion, but no major safety concerns were identified.

The 2025 systematic review (PMC12413689) confirmed that rtCGM was generally safe across all included trials, with no studies reporting severe device-related adverse events. Treatment satisfaction scores were consistently higher in rtCGM groups across multiple studies, including Haak et al. (DTSQ 13.1 vs. 9.0; p<0.0001), Wada et al. (significant improvement in DTSQ score; p=0.022), and Sato et al. (significant improvement in DTSQ score) (PMC12413689). This consistent finding of higher treatment satisfaction with rtCGM versus SMBG is clinically important, as it suggests that patients find the technology acceptable and preferable to fingerstick monitoring, which is a prerequisite for sustained use.

#### Alarm Fatigue and Discontinuation

A clinically important safety and usability concern with rtCGM is alarm fatigue — the phenomenon whereby frequent glucose alerts lead to habituation, reduced responsiveness, and ultimately device discontinuation. The RESCUE-Pediatrics study (PMC9582657), which examined rtCGM in children with type 1 diabetes over 24 months, found that a substantial proportion of children discontinued rtCGM during follow-up, with excessive alarms being the most commonly cited reason among those who stopped (n=7; 28% of children who stopped), followed by use of the system less than 70% of the time, technical problems, and lack of perceived benefit. While this study enrolled a pediatric T1DM population rather than adult non-insulin-treated T2DM patients, the alarm fatigue phenomenon is relevant across CGM user populations. As reported in the Alharbi et al. (2025) systematic review, SMBG frequency was reduced from 3.8 ± 1.4 to 0.3 ± 0.7 tests/day in the flash CGM group of the Haak et al. (2017) trial, indicating that patients largely substituted CGM for fingerstick testing rather than using both simultaneously (PMC12413689).

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### Unresolved Controversies and Disagreements

#### Does rtCGM Produce Clinically Meaningful HbA1c Reduction in Non-Insulin-Treated T2DM?

The most fundamental controversy in this literature is whether the HbA1c reductions observed with rtCGM in T2DM patients — particularly those on oral agents alone — are clinically meaningful. The pooled HbA1c reduction of −0.20% from the 2026 meta-analysis (PMC12875926) and −0.28% from the 2024 meta-analysis (PMC11668089) are statistically significant. The Xu et al. (2026) meta-analysis explicitly noted that the primary outcome HbA1c reduction of 0.20% with rtCGM compared with SMBG did not meet the 0.5% threshold considered clinically meaningful by current guidelines from the American Diabetes Association and NICE (PMC12875926). Notably, the Poole et al. (2024) meta-analysis observed that reductions of more than 0.3% are considered clinically meaningful by the FDA and have been shown to reduce diabetes-related complications, placing the pooled estimate of −0.28% at the lower boundary of potential clinical relevance (PMC11668089).

Proponents of clinical meaningfulness argue that the HbA1c metric alone is an insufficient measure of CGM benefit, and that the improvements in TIR (+7.41%), TAR (−6.93%), and glucose variability (−1.06% CV) observed in the 2026 meta-analysis (PMC12875926) all exceed their respective clinical significance thresholds and represent meaningful reductions in daily hyperglycemia exposure. They also argue that the modest pooled HbA1c effect reflects averaging across heterogeneous populations, and that patients with worse baseline control (HbA1c ≥9.5–10.0%) may experience HbA1c reductions of 0.68–1.52% — clearly clinically meaningful magnitudes (PMC9127836, PMC12413689). Critics counter that the evidence base is dominated by insulin-treated patients, that the few trials specifically enrolling non-insulin-treated patients (Moon et al., Wada et al.) have been small and short-term, and that the 12-month evidence specifically for oral-agent-only patients is sparse and inconsistent.

#### Durability of Benefit: Does the Effect Persist at 12 Months?

A second major controversy concerns the durability of rtCGM-driven glycemic improvements over time. Individual pilot data suggest that TIR improvements observed at 12 weeks may not be sustained at 9 months without ongoing CGM use, suggesting that the behavioral changes driven by CGM feedback may not be durable (PMC12413689). The GP-OSMOTIC trial found a significant HbA1c difference at 6 months (−0.5%; p=0.0001) that narrowed and became non-significant at 12 months (−0.3%; p=0.059), while the Moon et al. (2023) trial found that two intermittent rtCGM sessions maintained a significant HbA1c reduction at 6 months (−0.68%; p=0.018), suggesting that periodic 'booster' CGM exposures may sustain benefit (PMC12413689).

The Chinese RCT comparing real-time versus retrospective FGM (PMC8867069) found that the blinded FGM group showed a "fall after rise" pattern — an initial improvement followed by return toward baseline — attributed to poor long-term adherence to behavioral changes without ongoing real-time feedback. This pattern is consistent with the GP-OSMOTIC trial's attenuation of HbA1c benefit between 6 and 12 months. Together, these findings suggest that the durability of rtCGM-driven glycemic improvement may depend critically on whether CGM use is continuous or episodic, and whether it is accompanied by ongoing clinical support and education.

#### Insulin-Treated vs. Non-Insulin-Treated Patients: Is the Evidence Generalizable?

A third controversy concerns the generalizability of the rtCGM evidence base — which is dominated by insulin-treated patients — to the non-insulin-treated T2DM population. The 2026 meta-analysis (PMC12875926) included 8 studies with insulin users and only 3 studies with oral-agent-only patients, and the subgroup analysis found no significant difference in HbA1c reduction by insulin use (p=0.34). The 2024 meta-analysis (PMC11668089) similarly found no significant subgroup difference by insulin use (no insulin: MD −0.31%; some/all insulin: MD −0.27%; p=0.798). These findings suggest that the HbA1c benefit of rtCGM may not differ meaningfully between insulin-treated and non-insulin-treated T2DM patients.

However, critics note that the mechanism of glycemic improvement differs fundamentally between these populations. In insulin-treated patients, CGM data can be used to adjust insulin doses — a pharmacological mechanism with a direct and immediate effect on glucose levels. In non-insulin-treated patients, the mechanism is purely behavioral, and the magnitude and durability of behavioral change may be more variable and context-dependent. The subgroup analyses in the meta-analyses may be underpowered to detect a true difference in effect size between insulin-treated and non-insulin-treated patients.

#### The Role of CGM Type: rtCGM vs. Flash/Intermittently Scanned CGM

A fourth controversy concerns whether the evidence from flash glucose monitoring (FGM) or intermittently scanned CGM (isCGM) trials is applicable to rtCGM specifically. The GP-OSMOTIC trial used professional-mode flash CGM (Freestyle Libre Pro), the Wada et al. trial used FGM (Freestyle Libre), and the Haak et al. trial used flash CGM — none of which are strictly rtCGM systems, as they lack automatic continuous data transmission and real-time alarms. The 2026 meta-analysis (PMC12875926) explicitly excluded isCGM and professional CGM studies, restricting inclusion to rtCGM systems, and found a pooled HbA1c reduction of −0.20% (p=0.004). The 2024 meta-analysis (PMC11668089) included both rtCGM and isCGM studies and found a pooled HbA1c reduction of −0.28% (p<0.001). The 2025 systematic review (PMC12413689) included both rtCGM and FGM studies and synthesized findings narratively. The heterogeneity of CGM types across studies makes it difficult to isolate the specific contribution of real-time alarms and continuous data transmission — the features that distinguish rtCGM from isCGM — to the observed glycemic benefits.

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### Limitations of the Evidence Base

The evidence base for rtCGM in non-insulin-treated T2DM has several important methodological limitations that constrain the strength of conclusions that can be drawn.

**Scarcity of trials specifically in oral-agent-only T2DM.** The vast majority of RCTs in this field have enrolled insulin-treated patients, either with type 1 diabetes or with insulin-treated T2DM. Among the trials most directly relevant to the user's question — non-insulin-treated T2DM — only a handful of small trials exist: Moon et al. (n=61, 6 months), Wada et al. (n=100, 24 weeks), and the non-insulin subgroup of the GP-OSMOTIC trial (Furler et al., n=299 total, 12 months). None of these trials achieved the combination of large sample size, 12-month follow-up, and exclusive enrollment of oral-agent-only patients that would be needed to definitively answer the user's question.

**Short follow-up durations.** Most included trials have follow-up periods shorter than 12 months. The Xu et al. (2026) meta-analysis included studies with intervention durations of 12 to 56 weeks, and the Poole et al. (2024) meta-analysis included studies spanning 2 to 52 weeks (median 15 weeks), placing the 12-month time horizon at the outer edge of the available evidence (PMC12875926, PMC11668089). The GP-OSMOTIC trial (12 months) is the only trial with a 12-month follow-up that enrolled a substantial proportion of non-insulin-treated patients, and its primary HbA1c outcome narrowly missed statistical significance at 12 months (p=0.059) (PMC12413689). The durability of rtCGM-driven glycemic improvements beyond 6 months therefore remains uncertain.

**Open-label trial designs and performance bias.** All included trials were open-label, as blinding of participants to CGM use is not feasible. This introduces potential performance bias, whereby participants in the CGM group may modify their behavior simply because they know they are being monitored (the Hawthorne effect), independent of the specific information provided by the CGM. The 2025 systematic review (PMC12413689) acknowledged this limitation but noted that the objective nature of HbA1c measurements partially mitigates detection bias. The 2026 meta-analysis (PMC12875926) rated six of eleven studies as having a low overall risk of bias and five as having "some concerns," primarily due to insufficient information on randomization and allocation concealment.

**Heterogeneity of CGM devices, protocols, and comparators.** The included trials used a variety of CGM devices (Dexcom G4, G5, G6, G7; Medtronic Guardian; Abbott Freestyle Libre; Glunovo), intervention protocols (continuous vs. episodic use, professional vs. personal use, blinded vs. unblinded), and comparator definitions (SMBG frequency ranging from once daily to multiple times daily, usual care). This heterogeneity limits the comparability of findings across trials and contributes to the high I² values observed in meta-analyses (I²=88.5% for HbA1c in the 2024 meta-analysis [PMC11668089]; I²=27% in the 2026 meta-analysis [PMC12875926], which was lower due to more restrictive inclusion criteria).

**Small sample sizes and limited statistical power.** The total sample across all 11 RCTs in the 2026 meta-analysis (PMC12875926) was only 789 participants, with individual trial sample sizes ranging from 25 to 175. The subgroup analyses — particularly those stratified by insulin use, baseline HbA1c, and geographic region — are substantially underpowered, with some subgroups containing fewer than 100 participants. The post hoc subgroup analysis of the MOBILE trial (PMC9127836) had only 26 CGM and 9 BGM participants in the baseline HbA1c ≥10.0% subgroup, making the effect estimates highly imprecise despite their statistical significance.

**Conflicts of interest and industry funding.** A substantial proportion of included studies declared CGM-affiliated conflicts of interest. The 2024 meta-analysis (PMC11668089) found that 44% of included studies declared CGM-affiliated conflicts of interest, primarily with Abbott, Dexcom, and Medtronic. The authors conducted a sensitivity analysis removing these studies and found a slightly larger HbA1c reduction (MD −0.32%; I²=85.4%) compared with the main analysis (MD −0.28%; I²=88.5%), suggesting that industry-affiliated studies did not inflate the estimated benefit. Nevertheless, the high prevalence of industry involvement in this literature is a consideration when interpreting results.

**Generalizability to diverse populations.** The included trials were conducted predominantly in the United States (n=7 of 11 in the 2026 meta-analysis [PMC12875926]), with additional trials from Canada, France, and Korea. The populations were largely drawn from specialty or primary care settings in high-income countries, and the participants tended to be relatively technology-literate and motivated. A serial survey conducted in the U.S. from 2014 to 2020 found that CGM users were more likely to be younger, employed, earning at least $75,000 per year, covered by insurance, and with fewer comorbidities (PMC11668089). These characteristics may not reflect the broader population of adults with T2DM, particularly in lower-income settings or among racial and ethnic minority groups with higher diabetes prevalence and burden.

**Absence of cost-effectiveness data.** None of the included trials assessed cost-effectiveness, leaving a critical gap for health policy and reimbursement decisions. A Chinese RCT in gestational diabetes (PMC10155499) found that CGM monitoring cost approximately ¥3,002.4 per patient versus ¥752.4 for SMBG — an approximately threefold increase attributable primarily to CGM sensor costs — in a population of women with mild gestational diabetes mellitus. While this population differs substantially from non-insulin-treated T2DM adults, the cost differential illustrates the general challenge of CGM affordability, and the cost-benefit ratio for non-insulin-treated T2DM patients, who face lower immediate risks from glucose excursions than insulin-treated patients, remains uncertain.

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### Comparative Effectiveness

#### rtCGM vs. SMBG: The Primary Comparison

The primary comparison in the available literature is rtCGM versus SMBG. The 2026 meta-analysis (PMC12875926) found a pooled HbA1c reduction of −0.20% (95% CI: −0.34 to −0.06; p=0.004) favoring rtCGM, with statistically significant improvements in TIR (+7.41%), TAR (−6.93%), TBR (−0.26%), and glucose variability (−1.06% CV). The 2024 meta-analysis (PMC11668089) found a pooled HbA1c reduction of −0.28% (95% CI: 0.15–0.42; p<0.001) favoring CGM-based biological feedback versus control conditions without CGM. These pooled estimates are consistent across multiple sensitivity analyses and represent the best available evidence for the overall effect of rtCGM on HbA1c in T2DM.

#### rtCGM vs. Blinded/Professional CGM

The Chinese RCT (PMC8867069) comparing real-time (unblinded) versus retrospective (blinded) FGM in T2DM patients on premix insulin provides a direct head-to-head comparison of real-time versus non-real-time CGM. The unblinded FGM group showed a significant increase in TIR from baseline to endpoint (+6.5%; 95% CI: 2.4–10.6; p<0.001), while the blinded FGM group showed no significant change (−1.1%; 95% CI: −5.9 to 3.6; p=0.709). The estimated treatment difference in TIR between groups was −7.7% (95% CI: −13.9 to −1.4; p=0.014). Both groups showed significant reductions in HbA1c (both p<0.05), with no significant between-group difference (estimated treatment difference 0.1%; p=0.563). This finding suggests that the real-time visibility of glucose data — rather than the mere collection of CGM data — is the active ingredient driving TIR improvement, but that both real-time and retrospective CGM may produce similar HbA1c reductions when combined with physician-led medication adjustments.

#### rtCGM vs. Usual Care (No Glucose Monitoring)

The GP-OSMOTIC trial (Furler et al., 2020) compared professional CGM at three-month intervals versus usual clinical care (no structured glucose monitoring beyond routine HbA1c testing) in T2DM patients managed with non-insulin agents or insulin (PMC12413689). The between-group HbA1c difference at 12 months was −0.3% (95% CI: −0.5% to 0.01%; p=0.059), narrowly missing statistical significance. The TIR difference at 12 months was +7.9% (95% CI: 2.3–13.5; p=0.006), which was statistically significant. This trial provides the most direct evidence for the comparison of CGM versus usual care (rather than versus SMBG) in a population that includes non-insulin-treated patients, and its 12-month follow-up makes it the most relevant trial for the user's specific question.

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### Special Populations

#### Patients with Very High Baseline HbA1c

The MOBILE trial subgroup analysis (PMC9127836) provides the most detailed evidence on the differential benefit of rtCGM by baseline glycemic control. Patients with baseline HbA1c ≥10.0% (CGM n=26, BGM n=9) showed a between-group TIR improvement of +32% (95% CI: 11%–53%; p=0.004) and a between-group HbA1c reduction of −1.52% (95% CI: −2.55% to −0.50%; p=0.005). Forty-two percent more participants in this subgroup achieved a ≥1% HbA1c reduction with CGM versus BGM (adjusted difference 42%; p=0.02). Prolonged hyperglycemic events (≥8 hours >300 mg/dL) were reduced by 52% (p=0.01). These findings suggest that patients with very poor glycemic control may derive the greatest absolute benefit from rtCGM, potentially avoiding the need for pharmacological intensification.

#### Patients with Diabetic Kidney Disease

The Yeoh et al. (2018) pilot trial enrolled 30 adults with T2DM and stage 3 diabetic kidney disease (HbA1c >8%, approximately 90% on insulin therapy) and randomized them to retrospective CGM-guided antidiabetic therapy (n=14) or SMBG (n=16) (PMC12413689). No significant between-group HbA1c difference was found (p=0.869), though within-group reductions were significant in both groups (CGM: p=0.009; SMBG: p=0.007). The CGM group showed a significant reduction in time in hyperglycemia (>10 mmol/L) from 65.4 ± 22.4% to 54.6 ± 23.6% (p=0.033), while time in hypoglycemia increased non-significantly from 1.2 ± 2.2% to 4.0 ± 7.0% (p=0.176). This trial was small and enrolled predominantly insulin-treated patients with significant comorbidity, limiting generalizability to the non-insulin-treated T2DM population.

#### Older Adults

The Haak et al. (2017) trial found that significant HbA1c reductions with flash CGM were observed specifically in participants aged <65 years, while no significant benefit was seen in older participants (PMC12413689). This age-specific finding may reflect differences in technology engagement, cognitive capacity for interpreting CGM data, or the greater complexity of diabetes management in older adults with multiple comorbidities. The 2026 meta-analysis (PMC12875926) reported mean participant ages ranging from 53 to 70 years across included trials, suggesting that the evidence base is broadly applicable to middle-aged and older adults, though the specific evidence for patients aged ≥70 years is limited.

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### Conclusions and Future Directions

#### What the Evidence Supports

The available evidence supports the conclusion that rtCGM produces a statistically significant reduction in HbA1c compared with SMBG or usual care in adults with T2DM, with a pooled effect size of approximately −0.20% to −0.28% across meta-analyses (PMC12875926, PMC11668089). This effect is statistically robust, having been confirmed across multiple sensitivity analyses including removal of high-risk-of-bias studies, removal of industry-affiliated studies, and restriction to studies of ≥12 weeks duration (PMC11668089). The evidence also supports clinically meaningful improvements in TIR (+7.41%), TAR (−6.93%), and glucose variability (−1.06% CV) that exceed international consensus thresholds for clinical significance (PMC12875926). rtCGM is safe, with no significant increase in hypoglycemia or device-related serious adverse events, and is associated with consistently higher treatment satisfaction compared with SMBG (PMC12413689, PMC12875926).

For the specific subpopulation of adults with T2DM treated solely with oral medications, the evidence is more limited but directionally consistent. The Wada et al. (2020) trial demonstrated a statistically significant HbA1c reduction of −0.29% at 24 weeks in non-insulin-treated T2DM patients (PMC12413689). The Moon et al. (2023) trial demonstrated a statistically significant HbA1c reduction of −0.68% at 6 months with two intermittent rtCGM sessions in non-insulin-treated T2DM patients (PMC12413689). The GP-OSMOTIC trial (Furler et al., 2020) demonstrated a near-significant HbA1c reduction of −0.3% at 12 months (p=0.059) and a significant TIR improvement of +7.9% at 12 months (p=0.006) in a mixed population that included non-insulin-treated patients (PMC12413689). The subgroup analyses in the 2026 meta-analysis (PMC12875926) found no significant difference in HbA1c reduction between insulin-treated and non-insulin-treated patients (p=0.34), providing indirect support for the generalizability of the overall effect to the oral-agent-only population.

#### What the Evidence Does NOT Support

The evidence does not support the conclusion that rtCGM produces a clinically meaningful HbA1c reduction (≥0.5%) at 12 months in the average adult with T2DM treated solely with oral medications. The Xu et al. (2026) meta-analysis explicitly noted that the pooled HbA1c reduction of 0.20% with rtCGM compared with SMBG did not meet the 0.5% threshold considered clinically meaningful by current guidelines from the American Diabetes Association and NICE (PMC12875926). The Poole et al. (2024) meta-analysis noted that reductions exceeding 0.3% are considered clinically meaningful by the FDA, placing the pooled estimate of −0.28% at the lower boundary of potential clinical relevance (PMC11668089). The only trial with a 12-month follow-up that enrolled a substantial proportion of non-insulin-treated patients (GP-OSMOTIC) narrowly missed statistical significance for HbA1c at 12 months (p=0.059), though it achieved significance at 6 months and for TIR at 12 months (PMC12413689). The evidence does not support the conclusion that a single brief episode of rtCGM use produces durable glycemic benefits, and the GP-OSMOTIC trial showed attenuation of HbA1c benefit between 6 and 12 months.

The evidence does not support the conclusion that rtCGM improves cardiometabolic parameters beyond glycemic control. The 2026 meta-analysis (PMC12875926) found no significant differences between rtCGM and SMBG for body weight (MD −0.95 kg; p=0.19), BMI (MD −0.68; p=0.21), LDL, HDL, triglycerides, systolic BP (MD 0.19 mmHg; p=0.90), or diastolic BP (MD 0.37 mmHg; p=0.68). The evidence also does not support the conclusion that rtCGM improves health-related quality of life or treatment satisfaction in a statistically significant manner at the pooled level, though individual trials have reported higher satisfaction scores in CGM users (PMC12875926).

#### Future Research Directions

**1. Large, adequately powered RCTs specifically in non-insulin-treated T2DM with 12-month follow-up.** The most critical gap in the evidence base is the absence of a large, well-powered RCT enrolling exclusively non-insulin-treated T2DM patients with a 12-month primary endpoint. Such a trial should enroll at least 300–400 participants per arm to detect a clinically meaningful HbA1c difference of 0.3–0.5% with 80% power, and should stratify by baseline HbA1c, oral agent type (including sulfonylurea use), and prior SMBG frequency.

**2. Standardized outcome reporting including CGM-derived metrics.** Future trials should pre-specify and report TIR, TAR, TBR, and glucose variability as co-primary or key secondary endpoints alongside HbA1c, given the growing evidence that these metrics are more sensitive indicators of CGM benefit than HbA1c alone (PMC12875926, PMC11668089). The development of a core outcome set for CGM trials in T2DM would facilitate pooling across studies and reduce the heterogeneity that currently limits meta-analytic conclusions.

**3. Dose-response studies of CGM exposure frequency.** The available evidence suggests a dose-response relationship between CGM exposure frequency and glycemic benefit, but the optimal "dose" of CGM — in terms of wear duration, frequency of episodic use, and duration of continuous use — has not been systematically evaluated. Future trials should directly compare different CGM exposure protocols (e.g., continuous use vs. monthly 14-day wear periods vs. quarterly 7-day wear periods) to identify the minimum effective dose for sustained glycemic benefit.

**4. Identification of patient subgroups most likely to benefit.** Future research should prospectively test the hypothesis that patients with worse baseline glycemic control (HbA1c ≥9.5–10.0%) derive the greatest benefit from rtCGM, using pre-specified subgroup analyses with adequate power. Other potential effect modifiers — including baseline SMBG frequency, diabetes duration, oral agent type, health literacy, and technology engagement — should be systematically evaluated.

**5. Long-term durability studies.** The available evidence suggests that rtCGM-driven glycemic improvements may attenuate over time without ongoing CGM use or clinical support. Future studies should evaluate the durability of glycemic benefits beyond 12 months, and should test strategies for maintaining benefit — such as periodic "booster" CGM sessions, integration with digital health coaching platforms, or structured clinical review of CGM data at regular intervals.

**6. Cost-effectiveness analyses.** No included trial assessed cost-effectiveness, leaving a critical gap for health policy and reimbursement decisions. Future research should evaluate the cost per unit of HbA1c reduction, cost per quality-adjusted life year (QALY), and cost per avoided complication for rtCGM versus SMBG in non-insulin-treated T2DM, using both trial-based and model-based approaches.

**7. Mechanistic studies of behavioral pathways.** The mechanism by which rtCGM improves glycemic control in non-insulin-treated T2DM — through dietary modification, physical activity, medication adherence, or some combination — remains incompletely characterized. Future studies should use ecological momentary assessment, accelerometry, and dietary biomarkers to quantify the specific behavioral changes driven by CGM feedback, and should test whether structured behavioral interventions (e.g., dietary counseling, exercise prescription) amplify the glycemic benefit of rtCGM.

**8. Studies in diverse and underserved populations.** The existing evidence base is dominated by trials conducted in high-income Western countries with predominantly white or Hispanic participants. Future research should prioritize enrollment of racial and ethnic minority groups, patients in lower-income settings, older adults, and patients with limited health literacy or technology access, to ensure that the benefits of rtCGM are equitably distributed.

**9. Integration of rtCGM with artificial intelligence and digital health platforms.** Emerging evidence suggests that integrating CGM data with AI-driven analytics, personalized dietary feedback, and digital health coaching may substantially amplify the glycemic benefit of CGM alone (PMC7353748, PMC12875926). Future trials should evaluate these integrated approaches in non-insulin-treated T2DM, with particular attention to the incremental benefit of AI-driven personalization over standard CGM use.

**10. Head-to-head comparisons of rtCGM versus isCGM in non-insulin-treated T2DM.** The available evidence does not clearly distinguish the glycemic benefits of rtCGM (with continuous automatic data transmission and real-time alarms) from those of isCGM (which requires user-initiated scanning and lacks alarms) in non-insulin-treated T2DM. The Chinese RCT (PMC8867069) found that real-time FGM produced significantly greater TIR improvement than retrospective FGM (p=0.014), but no significant HbA1c difference (p=0.563), in insulin-treated patients. Future trials should directly compare rtCGM versus isCGM in non-insulin-treated T2DM to determine whether the real-time alarm and continuous transmission features of rtCGM provide incremental benefit over isCGM in this population.

In summary, the available evidence supports a statistically significant but modest reduction in HbA1c with rtCGM compared with SMBG or usual care in adults with T2DM, with pooled effects of −0.20% to −0.28%. The evidence for the specific population of non-insulin-treated T2DM patients at 12 months is limited but directionally consistent with the overall evidence base. The most compelling evidence for clinical meaningfulness comes from improvements in TIR, TAR, and glucose variability that exceed international consensus thresholds, and from subgroup analyses suggesting substantially larger HbA1c reductions in patients with the worst baseline glycemic control. The field urgently needs large, adequately powered, 12-month RCTs specifically in non-insulin-treated T2DM to definitively answer the user's question and to guide clinical practice and reimbursement policy.

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*Disclosure: This review was prepared as a synthesis of the published literature. No primary data were generated. All quantitative findings are attributed to the cited source papers.*

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