Daily Endocrinology Research Analysis
Across endocrinology, three papers stand out: a nationwide cohort shows SGLT2 inhibitors reduce primary macro- and microvascular events in type 2 diabetes; a large propensity-matched analysis finds no increased thyroid cancer risk with long-term GLP-1 receptor agonist therapy; and a Diabetes Care study demonstrates a patient-specific algorithm that improves inpatient CGM accuracy to meet clinical decision-support thresholds.
Summary
Across endocrinology, three papers stand out: a nationwide cohort shows SGLT2 inhibitors reduce primary macro- and microvascular events in type 2 diabetes; a large propensity-matched analysis finds no increased thyroid cancer risk with long-term GLP-1 receptor agonist therapy; and a Diabetes Care study demonstrates a patient-specific algorithm that improves inpatient CGM accuracy to meet clinical decision-support thresholds.
Research Themes
- Primary prevention with SGLT2 inhibitors in type 2 diabetes
- Long-term safety of GLP-1 receptor agonists (thyroid cancer risk)
- Algorithmic accuracy optimization for inpatient CGM
Selected Articles
1. SGLT2 inhibitors for primary prevention of macrovascular and major microvascular complications in type 2 diabetes: an island-wide cohort study.
In a nationwide, propensity-matched cohort from Taiwan, SGLT2 inhibitors were associated with lower risks of incident CAD, HF, cardiovascular death, dialysis, vision-threatening retinopathy, amputation, and all-cause mortality versus DPP-4 inhibitors, sulfonylureas, and GLP-1 RAs in patients without established macro/microvascular disease. Findings support SGLT2i for primary prevention across cardio-renal-retinal endpoints.
Impact: This is one of the largest real-world analyses of primary prevention with SGLT2 inhibitors, using multiple active comparators and showing broad risk reductions across clinically meaningful endpoints.
Clinical Implications: For T2D patients without established complications, SGLT2 inhibitors should be strongly considered early to reduce incident cardiovascular, renal, ophthalmic events and mortality, particularly in populations similar to those studied.
Key Findings
- Propensity-matched comparisons showed lower risk of CAD with SGLT2i vs DPP-4i, SU, GLP-1RA (HRs ~0.80, 0.78, 0.74).
- Heart failure risk was substantially reduced (HRs 0.44, 0.56, 0.66 vs DPP-4i, SU, GLP-1RA).
- Lower risks for cardiovascular death (HRs 0.47, 0.47, 0.68) and all-cause mortality (HRs 0.42, 0.39, 0.68).
- Major microvascular outcomes improved: dialysis (HRs 0.03, 0.13, 0.16), vision-threatening retinopathy (HRs 0.58, 0.59, 0.78), and amputation (HRs 0.29, 0.28, 0.61).
Methodological Strengths
- Nationwide population-based cohort with very large sample size
- Active-comparator, propensity score–matched design across multiple drug classes
Limitations
- Observational retrospective design with potential residual confounding and misclassification
- Lack of granular clinical data (e.g., lifestyle factors) inherent to claims databases
Future Directions: Pragmatic randomized trials in primary prevention and external validation across diverse non-Asian populations; mechanistic studies on microvascular protection; cost-effectiveness analyses.
OBJECTIVE: This study aimed to evaluate the different risks of developing cardiovascular disease and major microvascular complications between sodium-glucose cotransporter-2 inhibitors (SGLT2i) and non-SGLT2i users in patients with type 2 diabetes (T2D) who do not have existing macrovascular or microvascular diseases. DESIGN: This study employed a retrospective, population-based cohort study design. SETTING: Data were obtained from Taiwan's National Health Insurance Research Database, covering the period from January 1, 2008, to December 31, 2021. Propensity score matching was used to identify 91,327 matched pairs of SGLT2 inhibitor and dipeptidyl peptidase-4 (DPP-4) inhibitor users, 91,673 pairs of SGLT2 inhibitor and sulfonylurea users, and 20,857 pairs of SGLT2 inhibitor and glucagon-like peptide-1 receptor agonist (GLP-1 RA) users. PARTICIPANTS: The study included 1,145,035 patients diagnosed with T2D from the NHIRD. MAIN OUTCOME MEASURES: Cox proportional hazard models were used to assess the risk of outcomes. RESULTS: SGLT2i users showed a lower risk of coronary artery disease (0.80 (0.73-0.87), 0.78 (0.72-0.85) and 0.74 (0.64-0.86)), heart failure (0.44 (0.38-0.49), 0.56 (0.50-0.62) and 0.66 (0.55-0.78)), cardiovascular death (0.47 (0.40-0.56), 0.47 (0.40-0.55) and 0.68 (0.53-0.87)), dialysis (0.03 (0.02-0.05), 0.13 (0.10-0.17) and 0.16 (0.11-0.23)), vision-threatening retinopathy (0.58 (0.51-0.67), 0.59 (0.51-0.67) and 0.78 (0.62-0.98)), amputation (0.29 (0.20-0.41), 0.28 (0.21-0.38) and 0.61 (0.46-0.89)) and all-cause mortality (0.42 (0.39-0.445), 0.39 (0.37-0.42) and 0.68 (0.61-0.76]))when compared to DPP-4 inhibitors, sulfonylureas, and GLP-1 RA users, respectively. CONCLUSIONS: This study showed that SGLT2i use was associated with a lower risk of incident cardiovascular diseases, major microvascular complications and mortality compared with the use of DPP-4 inhibitors, sulfonylureas and GLP-1 RA in patients with T2D, who did not have macrovascular and microvascular diseases.
2. Advancing Continuous Glucose Monitoring for Inpatient Clinical Decision Support: Individual Algorithmic Mean Absolute Relative Difference.
A retrospective paired analysis (n=226) found initial CGM MARD of 10.30% with 99.02% of points in Clarke zones A/B. A patient-specific algorithm (time-lag correction and linear modeling) reduced MARD by 4.33% retrospectively and by 5.58% intrapersonally in a second inpatient cohort (n=24), supporting CGM use in hospital decision support.
Impact: Methodological innovation directly addresses regulatory-grade accuracy needs for inpatient CGM, a key barrier to hospital adoption.
Clinical Implications: Hospitals can consider patient-specific CGM post-processing to enhance accuracy for insulin dosing and decision support, potentially expanding CGM use beyond ICU/outpatient settings.
Key Findings
- Initial inpatient CGM MARD was 10.30% with 99.02% of paired values in Clarke Error Grid zones A/B.
- Patient-specific algorithm reduced MARD by 4.33% in retrospective analysis.
- In a second cohort (n=24), intrapersonal MARD decreased by 5.58% within clinical workflow.
Methodological Strengths
- Paired CGM and point-of-care measurements with multiple accuracy metrics (MARD, Clarke Error Grid, FDA rule)
- Validation within real clinical workflow in a second cohort
Limitations
- Retrospective design and single-center setting
- Small size of the second cohort (n=24) and potential device-specific generalizability
Future Directions: Prospective multicenter trials linking algorithmic accuracy gains to clinical outcomes (hypo/hyperglycemia, insulin dosing errors) and regulatory validation across devices.
OBJECTIVE: Continuous glucose monitoring (CGM) is widely used to monitor glucose levels in patients with diabetes and guide insulin dosing in outpatients. In inpatient care, special regulatory requirements necessitate CGM accuracy as a prerequisite for its integration into clinical decision support. RESEARCH DESIGN AND METHODS: To meet the specific demands of in-hospital care, CGM accuracy was retrospectively evaluated in 226 patients using paired CGM and point-of-care glucose measurements, assessed via mean absolute relative difference (MARD), Clarke Error Grid (CEG) analysis, and a modified version of the U.S. Food and Drug Administration agreement rule. A dynamic, patient-specific algorithm incorporating time lag correction and linear modeling was developed to minimize MARD and applied in a second cohort of 24 patients within the clinical workflow. RESULTS: Data analysis showed an initial MARD of 10.30%, with 99.02% of data points located in zones A and B of the CEG. The application of the patient-specific optimization algorithm improved the MARD by 4.33%. Evaluation of the patient-specific algorithm on the second inpatient cohort demonstrated a 5.58% reduction in intrapersonal MARD, indicating its potential applicability within clinical workflows. CONCLUSIONS: Patient-specific algorithmic refinements of CGM data demonstrate the potential to adequately address the unique demands of inpatient diabetes care by reducing intrapersonal MARD, paving the way for the adoption of CGM systems into hospital environments.
3. Long-Term Glucagon-Like Peptide 1 Receptor Agonist Use Is Not Associated With Increased Risk of Thyroid Cancer in Adults With Type 2 Diabetes.
In 89,646 adults with T2D followed a median 4.5 years, long-term GLP-1RA use was not associated with increased thyroid cancer risk compared with multiple active comparators, while achieving greater HbA1c reduction. Results were consistent across subgroups and sensitivity analyses.
Impact: Addresses a prominent safety concern for a cornerstone therapy in diabetes/obesity with a large, well-controlled real-world dataset.
Clinical Implications: Clinicians can be reassured that long-term GLP-1RA therapy does not appear to elevate thyroid cancer risk, supporting continued use when indicated.
Key Findings
- Propensity-matched cohort of 89,646 GLP-1RA users with median 4.5 ± 2.3 years follow-up.
- No increased thyroid cancer risk versus insulin, metformin, SGLT2i, DPP-4i, sulfonylureas, or thiazolidinediones.
- GLP-1RA associated with greater HbA1c reduction; findings consistent across sex, age, obesity, glycemic control, GLP-1RA type, and sensitivity analyses.
Methodological Strengths
- Large-scale EHR-based cohort with active comparators and propensity score matching
- Multiple subgroup and sensitivity analyses including negative control outcome
Limitations
- Observational design with potential residual confounding and outcome misclassification
- Histologic subtypes and calcitonin screening not detailed in the abstract
Future Directions: Longer-term follow-up to assess very-late risks, evaluation by thyroid cancer subtypes, and linkage with cancer registries for adjudicated outcomes.
BACKGROUND: Glucagon-like peptide-1 receptor agonists (GLP-1RAs) are widely used for type 2 diabetes (T2DM) and obesity, but their potential association with thyroid cancer remains a concern. This study assessed thyroid cancer risk with long-term GLP-1RA use in a large real-world cohort. METHODS: We conducted a propensity score matched cohort study using electronic health records from TriNetX, including 89,646 adults with T2DM who initiated GLP-1RA therapy between 2014 and 2020, and demonstrated continued use for at least 1 year. Active comparator controls included users of insulin, metformin, sodium-glucose transporter-2 inhibitors, dipeptidyl peptidase-4 inhibitors, sulfonylureas, and thiazolidinediones. The primary outcome was the incidence of thyroid cancer. RESULTS: During a median follow-up of 4.5 ± 2.3 years, GLP-1RA use was not associated with an increased risk of thyroid cancer compared with any of the other antidiabetic medications. As expected, GLP-1RA use was associated with a greater reduction in HbA1c levels, while the negative control outcome remained unaffected. Findings remained consistent across subgroups stratified by sex, age, obesity-status, glycaemic-control, and GLP-1RA type and in multiple sensitivity analyses. CONCLUSIONS: In this large real-world cohort study, long-term GLP-1RA use was not associated with an increased risk of thyroid cancer. These findings provide reassurance for the safety of GLP-1RAs and support their continued evidence-based use in clinical practice.