Daily Endocrinology Research Analysis
A cluster randomized clinical trial in rural Bangladesh showed that a faith-integrated, mosque-based lifestyle program significantly reduced 12‑month type 2 diabetes incidence among adults with prediabetes. A network meta-analysis of 87 RCTs compared cancer risks across antidiabetic drug classes and suggested potential cancer risk reductions for several classes without an overall increase in cancer risk. Multi-omics data identified IL‑18/IL‑18R1 signaling as a candidate biomarker predicting resp
Summary
A cluster randomized clinical trial in rural Bangladesh showed that a faith-integrated, mosque-based lifestyle program significantly reduced 12‑month type 2 diabetes incidence among adults with prediabetes. A network meta-analysis of 87 RCTs compared cancer risks across antidiabetic drug classes and suggested potential cancer risk reductions for several classes without an overall increase in cancer risk. Multi-omics data identified IL‑18/IL‑18R1 signaling as a candidate biomarker predicting response to SGLT2 inhibitors, advancing precision therapeutics in type 2 diabetes.
Research Themes
- Culturally tailored, community-based diabetes prevention
- Cancer safety profiles across antidiabetic drug classes
- Precision medicine biomarkers for SGLT2 inhibitor response
Selected Articles
1. Faith-Based Lifestyle Intervention for Diabetes Prevention Among Adults in Bangladesh: A Cluster Randomized Clinical Trial.
In a cluster RCT of 8 mosque clusters and 799 high‑risk adults with prediabetes, a 12‑month faith-integrated lifestyle program reduced type 2 diabetes incidence from 17.1% to 9.8% (absolute risk reduction 7.3 percentage points; HR 0.75; P=.02), with an NNT of 14. Secondary outcomes, including weight, BMI, glycemic markers, lipids, activity, and quality of life, improved more in the intervention group.
Impact: This rigorous community-based trial demonstrates a scalable, culturally tailored prevention model that significantly reduces diabetes incidence in a low-resource setting.
Clinical Implications: Integrating faith-based, community-delivered lifestyle education into primary prevention could reduce diabetes conversion among high-risk adults, informing public health strategies in similar settings.
Key Findings
- 12-month cumulative T2D incidence was 9.8% vs 17.1% (absolute risk reduction 7.3 percentage points; NNT=14).
- Adjusted Cox model showed HR 0.75 (95% CI, 0.60–0.95; P=.02), indicating a 25% risk reduction.
- Secondary outcomes (weight, BMI, fasting and 2-hour glucose, HbA1c, lipid profiles, knowledge, physical activity, and QoL) improved more in the intervention arm.
Methodological Strengths
- Cluster randomized design with intention-to-treat analysis and clustering adjustment
- Validated risk screening and OGTT confirmation; trial registration (ISRCTN91564707)
Limitations
- Only 8 clusters, which may limit statistical power and generalizability
- Follow-up limited to 12 months; sustainability and long-term outcomes are unknown
Future Directions: Evaluate multi-year sustainability, cost-effectiveness, and scale-up across diverse geographies and faith settings; test integration with primary care and digital support.
IMPORTANCE: The incidence of type 2 diabetes (T2D) is increasing in low- and middle-income countries. Effective, culturally tailored interventions are needed for diabetes prevention. OBJECTIVE: To evaluate the effectiveness of a 12-month, mosque-based, faith-integrated lifestyle intervention in reducing T2D incidence among adults with prediabetes in rural Bangladesh. DESIGN, SETTING, AND PARTICIPANTS: This parallel-group, cluster randomized clinical trial (RCT) was conducted from April 2022 to April 2023 across 8 rural mosque clusters in 5 districts of Bangladesh, with a 12-month follow-up. Adults (aged 25-65 years) were screened using a validated diabetes risk score. Individuals with high risk scores underwent oral
2. Association between antidiabetic drugs and cancer risk in patients with type 2 diabetes mellitus: A systematic review and network meta-analysis.
Across 87 RCTs (216,106 participants), antidiabetic drugs did not increase overall cancer risk versus placebo. Network meta-analysis suggested potential reductions in specific cancers by several drug classes (e.g., GLP‑1 RAs for prostate/uterine/hepatocellular/renal/hematologic; SGLT2i for lung/bronchial; DPP‑4i for thyroid/rectal), though heterogeneity and indirectness warrant cautious interpretation.
Impact: Provides a cross-class, RCT-based synthesis of cancer risks that could influence drug selection for patients with varying oncologic risk profiles.
Clinical Implications: While overall cancer risk does not appear elevated with antidiabetic drugs, clinicians may consider class-specific associations when treating patients with heightened risks for certain cancers, pending further validation.
Key Findings
- No increase in overall cancer risk versus placebo across antidiabetic classes in RCTs.
- Class-specific associations suggested: GLP-1 RAs (prostate, uterine, hepatocellular, renal, hematologic), SGLT2i (lung/bronchial), DPP-4i (thyroid/rectal), sulfonylureas (gastric/colon), biguanides (pancreatic), insulin (bladder), TZDs (breast).
- Applied a network meta-analytic framework with confidence in network meta-analysis to rate evidence credibility.
Methodological Strengths
- Network meta-analysis across 26 drugs and 7 classes with large cumulative sample size
- Restricted to RCTs with ≥1 year follow-up; PRISMA-style approach and evidence grading (confidence in NMA)
Limitations
- Indirect comparisons and heterogeneity across trials; many RCTs not powered or designed for cancer endpoints
- Potential multiple-testing issues and variable follow-up durations may influence site-specific findings
Future Directions: Prospective, adequately powered, long-term trials or high-quality real-world studies with standardized cancer adjudication are needed to confirm class-specific associations and mechanisms.
BACKGROUND: Current evidence suggests that commonly used antidiabetic drugs have varying effects on cancer risk. Some antidiabetics offer protective effects against cancer, whereas others may increase risk in specific populations. AIM: To comprehensively compare the effects of different antidiabetic drugs on the risk of various cancers in patients with type 2 diabetes mellitus (T2DM) through a systematic review and network meta-analysis. METHODS: Four databases (PubMed, EMBASE, Cochrane Library, and Web of Science) were searched from their inception until April 11, 2025. Published randomized controlled trials that enrolled at least 100 participants and had an intervention duration of at least 1 year were included. The inclusion criteria were studies involving adult patients with T2DM and interventions that compared different classes of antidiabetic drugs with a placebo or another antidiabetic drug. Network meta-analysis was conducted using Stata 17.0 software. Confidence in network meta-analysis was used to assess the quality of evidence regarding the risk of cancer associated with different antidiabetic drugs. RESULTS: A total of 13535 articles were identified. After applying the inclusion and exclusion criteria, 87 high-quality studies involving 216106 patients and 26 different drugs across seven classes were included in this study. Indirect evidence from network meta-analysis revealed some heterogeneity; however, this did not affect the reliability of the results. The results indicated that antidiabetic drugs did not increase the overall risk of cancer compared with placebo. In contrast, some antidiabetic medications demonstrated a more pronounced advantage in reducing cancer risk, such as dipeptidyl peptidase-4 inhibitors for thyroid and rectal cancers; sodium-glucose co-transporter type 2 inhibitors for lung and bronchial cancers; sulfonylureas for gastric and colon cancers; biguanides for pancreatic cancer; insulin for bladder cancer; glucagon-like peptide-1 receptor agonists for prostate, uterine, hepatocellular, renal, and hematologic cancers; and thiazolidinediones for breast cancer. CONCLUSION: Antidiabetic drugs reduce cancer risk in patients with T2DM. However, given the limitations in the number and quality of the included studies, our conclusions should be interpreted with caution. More large-scale, high-quality clinical trials are required to validate our findings towards the optimization of comprehensive cancer management strategies for patients with T2DM.
3. Identification of IL18/IL18R1 signaling as a predictive biomarker of SGLT2 inhibitor efficacy in type 2 diabetes.
In 70 patients initiating SGLT2 inhibitors, multi-omics profiling linked reductions in IL‑18R1 to improvements in glycemia, albuminuria, adiposity, and liver function. High baseline IL‑18/IL‑18R1 predicted overall therapeutic response (AUC ~0.75), suggesting a candidate biomarker for precision selection of SGLT2i therapy.
Impact: Introduces an inflammation-related biomarker that may predict multidomain benefits from SGLT2 inhibitors, enabling individualized therapy.
Clinical Implications: Baseline IL‑18/IL‑18R1 measurement could help identify likely responders to SGLT2 inhibitors across glycemic, renal, and metabolic outcomes; clinical adoption requires external validation and standardized assays.
Key Findings
- Proteomics identified IL‑18R1 reduction associated with improved HbA1c, albuminuria, fat mass, and liver function after SGLT2i initiation.
- High baseline IL‑18/IL‑18R1 predicted overall treatment response with ROC AUC ~0.75.
- Transcriptomic data supported anti-inflammatory shifts in mononuclear cells during therapy.
Methodological Strengths
- Prospective clinical phenotyping integrated with plasma proteomics and transcriptomics
- Multidomain outcome assessment (glycemia, renal, adiposity, BP, uric acid, body composition)
Limitations
- Single-cohort sample (n=70) without external validation; cutoffs and assay standardization not established
- Non-randomized design cannot exclude confounding; follow-up duration not detailed
Future Directions: Validate IL‑18/IL‑18R1 as a predictive biomarker in larger, diverse cohorts and RCTs; define clinical cutoffs and assay standards; test biomarker-guided SGLT2i allocation.
Sodium-glucose co-transporter 2 inhibitors (SGLT2i) are widely used to manage type 2 diabetes mellitus (T2DM) to ameliorate hyperglycemia, albuminuria, and obesity, with established cardiorenal benefits. However, predictive biomarkers for therapeutic responses remain limited. In this study, seventy patients initiating SGLT2i therapy were evaluated clinically and through plasma proteomics and transcriptomics. Treatment significantly improved HbA1c (71.2%), albuminuria (47.5%), and weight (58.6%), with benefits in insulin resistance, β-cell function, blood pressure, uric acid, and body composition. Proteomic analysis identified IL-18R1 reduction linked to improved glycemic control, albuminuria, fat mass, and liver function. Transcriptomic profiling revealed genetic alterations in blood mononuclear cells, reinforcing anti-inflammatory changes. Receiver operating characteristic analysis indicated high baseline IL-18/IL-18R1 predicted overall response (area under the curve: 0.75,