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Background: EXSCEL (Exenatide Study of Cardiovascular Event Lowering) assessed the impact of once-weekly exenatide 2 mg versus placebo in patients with type 2 diabetes mellitus, while aiming for glycemic equipoise. Consequently, greater drop-in of open-label glucose-lowering medications occurred in the placebo group. Accordingly, we explored the potential effects of their unbalanced use on major adverse cardiovascular events (MACE), defined as cardiovascular death, nonfatal myocardial infarction or nonfatal stroke, and all-cause mortality (ACM), given that some of these agents are cardioprotective. Methods: Cox hazard models were performed by randomized treatment for drug classes where >5% open-label drop-in glucose-lowering medication occurred, and for glucagon-like peptide-1 receptor agonists (GLP-1 RAs; 3.0%) using three methodologies: drop-in visit right censoring, inverse probability for treatment weighting (IPTW), and applying drug class risk reductions. Results: Baseline glucose-lowering medications for the 14 752 EXSCEL participants (73.1% with previous cardiovascular disease) did not differ between treatment groups. During median 3.2 years follow-up, open-label drop-in occurred in 33.4% of participants, more frequently with placebo than exenatide (38.1% versus 28.8%), with metformin (6.1% versus 4.9%), sulfonylurea (8.7% versus 6.9%), dipeptidyl peptidase-4 inhibitors (10.6% versus 7.5%), SGLT-2i (10.3% versus 8.1%), GLP-1 RA (3.4% versus 2.4%), and insulin (13.8% versus 9.4%). The MACE effect size was not altered meaningfully by right censoring, but the favorable HR for exenatide became nominally significant in the sulfonylurea and any glucose-lowering medication groups, while the ACM HR and p-values were essentially unchanged. IPTW decreased the MACE HR from 0.91 (P=0.061) to 0.85 (P=0.008) and the ACM HR from 0.86 (P=0.016) to 0.81 (P=0.012). Application of literature-derived risk reductions showed no meaningful changes in MACE or ACM HRs or P values, although simulations of substantially greater use of drop-in cardioprotective glucose-lowering agents demonstrated blunting of signal detection. Conclusions: EXSCEL-observed HRs for MACE and ACM remained robust after right censoring or application of literature-derived risk reductions, but the exenatide versus placebo MACE effect size and statistical significance were increased by IPTW. Effects of open-label drop-in cardioprotective medications need to be considered carefully when designing, conducting, and analyzing cardiovascular outcome trials of glucose-lowering agents under the premise of glycemic equipoise. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT01144338.

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 1 year 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 1 year, and 2375 developed diabetes during a median of 4 years 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 ( 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. © 2017 Elsevier Inc.

Aim: To examine fracture incidence among participants in the Trial Evaluating Cardiovascular Outcomes with Sitagliptin (TECOS). Research design and methods: We used data from 14 671 participants in the TECOS study who were randomized double-blind to sitagliptin (n = 7332) or placebo (n = 7339). Cumulative fracture incidence rates were calculated and their association with study treatment assignment was examined using multivariable Cox proportional hazards regression. Results: The baseline mean (standard deviation) participant age was 65.5 (8.0) years, diabetes duration was 11.6 (8.1) years and glycated haemoglobin level was 7.2 (0.5)% [55.2 (5.5) mmol/mol], and 29.3% of participants were women and 32.1% were non-white. During 43 222 person-years’ follow-up, 375 (2.6%; 8.7 per 1000 person-years) had a fracture; 146 were major osteoporotic fractures (hip, n = 34; upper extremity, n = 81; and clinical spine, n = 31). Adjusted analyses showed fracture risk increased independently with older age (P

Objective To examine the degree to which use of β blockers, statins, and diuretics in patients with impaired glucose tolerance and other cardiovascular risk factors is associated with new onset diabetes.\ud \ud Design Reanalysis of data from the Nateglinide and Valsartan in Impaired Glucose Tolerance Outcomes Research (NAVIGATOR) trial.\ud \ud Setting NAVIGATOR trial.\ud \ud Participants Patients who at baseline (enrolment) were treatment naïve to β blockers (n=5640), diuretics (n=6346), statins (n=6146), and calcium channel blockers (n=6294). Use of calcium channel blocker was used as a metabolically neutral control.\ud \ud Main outcome measures Development of new onset diabetes diagnosed by standard plasma glucose level in all participants and confirmed with glucose tolerance testing within 12 weeks after the increased glucose value was recorded. The relation between each treatment and new onset diabetes was evaluated using marginal structural models for causal inference, to account for time dependent confounding in treatment assignment.\ud \ud Results During the median five years of follow-up, β blockers were started in 915 (16.2%) patients, diuretics in 1316 (20.7%), statins in 1353 (22.0%), and calcium channel blockers in 1171 (18.6%). After adjusting for baseline characteristics and time varying confounders, diuretics and statins were both associated with an increased risk of new onset diabetes (hazard ratio 1.23, 95% confidence interval 1.06 to 1.44, and 1.32, 1.14 to 1.48, respectively), whereas β blockers and calcium channel blockers were not associated with new onset diabetes (1.10, 0.92 to 1.31, and 0.95, 0.79 to 1.13, respectively).\ud \ud Conclusions Among people with impaired glucose tolerance and other cardiovascular risk factors and with serial glucose measurements, diuretics and statins were associated with an increased risk of new onset diabetes, whereas the effect of β blockers was non-significant.