Potential Mediators for Treatment Effects of Novel Diabetes Medications on Cardiovascular and Renal Outcomes: A Meta-Regression Analysis.

BACKGROUND: Prior research suggests clinical effects of glucagon-like peptide-1 receptor agonists (GLP-1RAs) and sodium-glucose cotransporter-2 inhibitors (SGLT2is) are mediated by changes in glycated hemoglobin, body weight, systolic blood pressure, hematocrit, and urine albumin-creatinine ratio. We aimed to confirm these findings using a meta-analytic approach. METHODS AND RESULTS: We updated a systematic review of 9 GLP-1RA and 13 SGLT2i trials and summarized longitudinal mediator data. We obtained hazard ratios (HRs) for cardiovascular, renal, and mortality outcomes. We performed linear mixed-effects modeling of LogHRs versus changes in potential mediators and investigated differences in meta-regression associations among drug classes using interaction terms. HRs generally became more protective with greater glycated hemoglobin reduction among GLP-1RA trials, with average HR improvements of 20% to 30%, reaching statistical significance for major adverse cardiovascular events (ΔHR, 23%; P=0.02). Among SGLT2i trials, associations with HRs were not significant and differed from GLP1-RA trials for major adverse cardiovascular events (Pinteraction=0.04). HRs for major adverse cardiovascular events, myocardial infarction, and stroke became less efficacious (ΔHR, -15% to -34%), with more weight loss for SGLT2i but not for GLP-1RA trials (ΔHR, 4%-7%; Pinteraction<0.05). Among 5 SGLT2i trials with available data, HRs for stroke became less efficacious with larger increases in hematocrit (ΔHR, 123%; P=0.09). No changes in HRs by systolic blood pressure (ΔHR, -11% to 9%) and urine albumin-creatinine ratio (ΔHR, -1% to 4%) were found for any outcome. CONCLUSIONS: We confirmed increased efficacy findings for major adverse cardiovascular events with reduction in glycated hemoglobin for GLP1-RAs. Further research is needed on the potential loss of cardiovascular benefits with increased weight loss and hematocrit for SGLT2i.

Cardiovascular and Renal Benefits of Novel Diabetes Drugs by Baseline Cardiovascular Risk: A Systematic Review, Meta-analysis, and Meta-regression.

BACKGROUND: Eligibility for glucagon-like peptide 1 receptor agonists (GLP-1RA) and sodium-glucose cotransporter 2 inhibitors (SGLT2i) has been expanded to patients with diabetes at lower cardiovascular risk, but whether treatment benefits differ by risk levels is not clear. PURPOSE: To investigate whether patients with varying risks differ in cardiovascular and renal benefits from GLP-1RA and SGLT2i with use of meta-analysis and meta-regression. DATA SOURCES: We performed a systematic review using PubMed through 7 November 2022. STUDY SELECTION: We included reports of GLP-1RA and SGLT2i confirmatory randomized trials in adult patients with safety or efficacy end point data. DATA EXTRACTION: Hazard ratio (HR) and event rate data were extracted for mortality, cardiovascular, and renal outcomes. DATA SYNTHESIS: We analyzed 9 GLP-1RA and 13 SGLT2i trials comprising 154,649 patients. Summary HRs were significant for cardiovascular mortality (GLP-1RA 0.87 and SGLT2i 0.86), major adverse cardiovascular events (0.87 and 0.88), heart failure (0.89 and 0.70), and renal (0.84 and 0.65) outcomes. For stroke, efficacy was significant for GLP-1RA (0.84) but not for SGLT2i (0.92). Associations between control arm cardiovascular mortality rates and HRs were nonsignificant. Five-year absolute risk reductions (0.80-4.25%) increased to 11.6% for heart failure in SGLT2i trials in patients with high risk (Pslope < 0.001). For GLP1-RAs, associations were nonsignificant. LIMITATIONS: Analyses were limited by lack of patient-level data, consistency in end point definitions, and variation in cardiovascular mortality rates for GLP-1RA trials. CONCLUSIONS: Relative effects of novel diabetes drugs are preserved across baseline cardiovascular risk, whereas absolute benefits increase at higher risks, particularly regarding heart failure. Our findings suggest a need for baseline risk assessment tools to identify variation in absolute treatment benefits and improve decision-making.

A Diagnostic Gene Expression Signature for Bladder Cancer Can Stratify Cases into Prescribed Molecular Subtypes and Predict Outcome.

Bladder cancer is a biologically heterogeneous disease with variable clinical presentations, outcomes and responses to therapy. Thus, the clinical utility of single biomarkers for the detection and prediction of biological behavior of bladder cancer is limited. We have previously identified and validated a bladder cancer diagnostic signature composed of 10 biomarkers, which has been incorporated into a multiplex immunoassay bladder cancer test, Oncuria™. In this study, we evaluate whether these 10 biomarkers can assist in the prediction of bladder cancer clinical outcomes. Tumor gene expression and patient survival data from bladder cancer cases from The Cancer Genome Atlas (TCGA) were analyzed. Alignment between the mRNA expression of 10 biomarkers and the TCGA 2017 subtype classification was assessed. Kaplan-Meier analysis of multiple gene expression datasets indicated that high expression of the combined 10 biomarkers correlated with a significant reduction in overall survival. The analysis of three independent, publicly available gene expression datasets confirmed that multiplex prognostic models outperformed single biomarkers. In total, 8 of the 10 biomarkers from the Oncuria™ test were significantly associated with either luminal or basal molecular subtypes, and thus, the test has the potential to assist in the prediction of clinical outcome.