Effect of expanded dulaglutide weekly doses (3.0 mg and 4.5 mg) on cardiovascular disease risk factors in participants with type 2 diabetes at increased cardiovascular disease risk: a post hoc analysis of the AWARD-11 study.

AIMS: This post hoc analysis investigated the effect of dulaglutide on cardiovascular disease (CVD) risk factors in subgroups of participants at increased CVD risk in the AWARD-11 study. METHODS: Participants who received once weekly dulaglutide 1.5, 3.0 or 4.5 mg for 52 weeks were categorized according to their baseline Framingham CVD risk category [low (N = 295), medium (N = 481) and high (N = 1054) risk], as well as their baseline CVD risk according to the REWIND study eligibility criteria (N = 953). Serum lipids and vital signs were assessed at baseline and at 52 weeks. Data were analysed as least squares mean percentage change from baseline for lipids and least squares mean change from baseline for vital signs. RESULTS: Demographic and baseline clinical characteristics were balanced across doses within the CVD risk groups. In the high Framingham CVD risk and REWIND-like groups, dulaglutide resulted in dose-related decreases in total cholesterol (≤6.0%), non-high-density lipoprotein cholesterol (≤8.8%), very-low-density lipoprotein cholesterol (≤19.4%) and triglycerides (≤21.5%), with little change in low-density lipoprotein cholesterol and high-density lipoprotein cholesterol. Systolic and diastolic blood pressure decreased up to 5.6 mmHg and 1.6 mmHg, respectively, and heart rate increased up to 2 beats/min. CONCLUSIONS: This post hoc analysis suggests the magnitude of the favourable effects of dulaglutide 3.0 mg and 4.5 mg on several cardiometabolic CVD risk factors was similar to, if not greater than, those of dulaglutide 1.5 mg among participants with type 2 diabetes and increased CVD risk. CLINICALTRIALS: gov Identifier: NCT03495102.

Rationale and design of the EXenatide Study of Cardiovascular Event Lowering (EXSCEL) trial.

Exenatide once-weekly is an extended release formulation of exenatide, a glucagon-like peptide-1 receptor agonist, which can improve glycemic control, body weight, blood pressure, and lipid levels in patients with type 2 diabetes mellitus (T2DM). The EXenatide Study of Cardiovascular Event Lowering (EXSCEL) will compare the impact of adding exenatide once-weekly to usual care with usual care alone on major cardiovascular outcomes. EXSCEL is an academically led, phase III/IV, double-blind, pragmatic placebo-controlled, global trial conducted in 35 countries aiming to enrol 14,000 patients with T2DM and a broad range of cardiovascular risk over approximately 5 years. Participants will be randomized (1:1) to receive exenatide once-weekly 2 mg or matching placebo by subcutaneous injections. The trial will continue until 1,360 confirmed primary composite cardiovascular end points, defined as cardiovascular death, nonfatal myocardial infarction, or nonfatal stroke, have occurred. The primary efficacy hypothesis is that exenatide once-weekly is superior to usual care with respect to the primary composite cardiovascular end point. EXSCEL is powered to detect a 15% relative risk reduction in the exenatide once-weekly group, with 85% power and a 2-sided 5% alpha. The primary safety hypothesis is that exenatide once-weekly is noninferior to usual care with respect to the primary cardiovascular composite end point. Noninferiority will be concluded if the upper limit of the CI is <1.30. EXSCEL will assess whether exenatide once-weekly can reduce cardiovascular events in patients with T2DM with a broad range of cardiovascular risk. It will also provide long-term safety information on exenatide once-weekly in people with T2DM. ClinicalTrials.gov Identifier: NCT01144338.

Simulating the impact of targeting lower systolic blood pressure and LDL-cholesterol levels on type 2 diabetes complication rates.

AIMS: There are few data available on the incremental benefits of risk factor modification in type 2 diabetes mellitus (T2DM). We simulated the potential benefits of achieving lower systolic blood pressure (SBP) and LDL-cholesterol targets. METHODS: We used the UKPDS Outcomes Model v2.0 to estimate 10-year event rates for complications using baseline data from 5717 participants with T2DM in the Trial Evaluating Cardiovascular Outcomes with Sitagliptin Study. All risk factor values were held constant over 10 years. In separate analyses, different levels of SBP between 160 and 120 mm Hg and LDL-cholesterol between 5.0 and 1.0 mmol/l were imposed on the cohort. Cumulative relative risk reductions (CRRR) at each 10 mm Hg and 1.0 mmol/l decrements respectively were compared using Kruskal-Wallis tests. RESULTS: CRRRs for each 10 mm Hg SBP decrement from 160 mm Hg were 2.2%, 4.5%, 7.0% and 10.0% for myocardial infarction (MI); 12.5%, 24.8%, 35.6% and 44.9% for stroke; 5.4%, 10.9%, 16.2% and 20.9% for blindness; 7.4%, 14.7%, 21.6% and 27.4% for amputation, respectively. CRRRs for each 1.0 mmol/l LDL-cholesterol decrement from 5.0 mmol/l were 16.9%, 30.8%, 41.2% & 51.0% for MI; 9.2%, 19.7%, 29.6% & 38.8% for stroke (p < 0.001 in all cases). CONCLUSIONS: These simulated outcomes illustrate the potential benefits of targeting progressively lower SBP and LDL-cholesterol values.

Updated risk factors should be used to predict development of diabetes.

AIMS: Predicting incident diabetes could inform treatment strategies for diabetes prevention, but the incremental benefit of recalculating risk using updated risk factors is unknown. We used baseline and 1-year data from the Nateglinide and Valsartan in Impaired Glucose Tolerance Outcomes Research (NAVIGATOR) Trial to compare diabetes risk prediction using historical or updated clinical information. METHODS: Among non-diabetic participants reaching 1year of follow-up in NAVIGATOR, we compared the performance of the published baseline diabetes risk model with a "landmark" model incorporating risk factors updated at the 1-year time point. The C-statistic was used to compare model discrimination and reclassification analyses to demonstrate the relative accuracy of diabetes prediction. RESULTS: A total of 7527 participants remained non-diabetic at 1year, and 2375 developed diabetes during a median of 4years of follow-up. The C-statistic for the landmark model was higher (0.73 [95% CI 0.72-0.74]) than for the baseline model (0.67 [95% CI 0.66-0.68]). The landmark model improved classification to modest (<20%), moderate (20%-40%), and high (>40%) 4-year risk, with a net reclassification index of 0.14 (95% CI 0.10-0.16) and an integrated discrimination index of 0.01 (95% CI 0.003-0.013). CONCLUSIONS: Using historical clinical values to calculate diabetes risk reduces the accuracy of prediction. Diabetes risk calculations should be routinely updated to inform discussions about diabetes prevention at both the patient and population health levels.