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Aim We aimed to compare cardiovascular outcomes of patients with type 2 diabetes (T2D) who initiated GLP-1 receptor agonists (GLP-1RA) or basal insulin (BI) under routine care. Methods We accessed the administrative claims database of the Veneto Region (Italy) to identify new users of GLP-1RA or BI in 2014–2018. Propensity score matching (PSM) was implemented to obtain two cohorts of patients with superimposable characteristics. The primary endpoint was the 3-point major adverse cardiovascular events (3P-MACE). Secondary endpoints included 3P-MACE components, hospitalization for heart failure, revascularizations, and adverse events. Results From a background population of 5,242,201 citizens, 330,193 were identified as having diabetes. PSM produced two very well matched cohorts of 4063 patients each, who initiated GLP-1RA or BI after an average of 2.5 other diabetes drug classes. Patients were 63-year-old and only 15% had a baseline history of cardiovascular disease. During a median follow-up of 24 months in the intention-to-treat analysis, 3P-MACE occurred less frequently in the GLP-1RA cohort (HR versus BI 0.59; 95% CI 0.50–0.71; p Conclusions Patients with T2D who initiated a GLP-1RA experienced far better cardiovascular outcomes than did matched patients who initiated a BI in the same healthcare system. These finding supports prioritization of GLP-1RA as the first injectable regimen for the management of T2D.

Aims Glucagon like peptide-1 (GLP-1) receptor agonists (GLP-1RA) are effective to control type 2 diabetes (T2Ds) and can protect from adverse cardiovascular outcomes. GLP-1RA are based on the human GLP-1 or the exendin-4 sequence. We compared cardiovascular outcomes of patients with T2D who received human-based or exendin-based GLP-1RA in routine clinical practice. Methods and results We performed a retrospective study on the administrative database of T2D patients from the Veneto Region (North-East Italy). We identified patients who initiated a human-based or exendin-based GLP-1RA from 2011 to 2018. The primary outcome was occurrence of major adverse cardiovascular events (MACE). Secondary outcomes were individual MACE components, revascularization, hospitalization for heart failure, or for cardiovascular causes. From 330 193 patients with diabetes, 6620 were new users of GLP-1RA. After propensity score matching, we analysed 1098 patients in each group, who were on average 61 years old, 59.5% males, 13% with established cardiovascular disease, had an estimated diabetes duration of 8.4 years, and a baseline HbA1c of 7.9%. During a median follow-up of 18 months, patients treated with human-based GLP-1RA as compared to those treated with exendin-based GLP-1RA, showed lower rates of MACE [hazard ratio 0.61; 95% confidence interval (CI) 0.39–0.95], myocardial infarction (0.51; 95% CI 0.28–0.94), and hospitalization for cardiovascular causes (0.66; 95% CI 0.47–0.92). Conclusion We observed better cardiovascular outcomes among patients treated with human-based vs. exendin-based GLP-1RA under routine care. In the absence of comparative trials and in view of the limitations of retrospective studies, this finding provides a moderate level of evidence to guide clinical decision.

Because other coronaviruses enter the cells by binding to dipeptidyl-peptidase-4 (DPP-4), it has been speculated that DPP-4 inhibitors (DPP-4is) may exert an activity against severe acute respiratory syndrome coronavirus 2. In the absence of clinical trial results, we analysed epidemiological data to support or discard such a hypothesis. We retrieved information on exposure to DPP-4is among patients with type 2 diabetes (T2D) hospitalized for COVID-19 at an outbreak hospital in Italy. As a reference, we retrieved information on exposure to DPP-4is among matched patients with T2D in the same region. Of 403 hospitalized COVID-19 patients, 85 had T2D. The rate of exposure to DPP-4is was similar between T2D patients with COVID-19 (10.6%) and 14 857 matched patients in the region (8.8%), or 793 matched patients in the local outpatient clinic (15.4%), 8284 matched patients hospitalized for other reasons (8.5%), and when comparing 71 patients hospitalized for COVID-19 pneumonia (11.3%) with 351 matched patients with pneumonia of another aetiology (10.3%). T2D patients with COVID-19 who were on DPP-4is had a similar disease outcome as those who were not. In summary, we found no evidence that DPP-4is might affect hospitalization for COVID-19.

Aims We compared cardiovascular outcomes of patients with type 2 diabetes (T2D) receiving sodium glucose cotransporter-2 inhibitors (SGLT2i) or dipeptidyl peptidase-4 inhibitors (DPP4i) under routine care. Methods From an administrative claims database of >5.2M citizen, we identified patients with T2D who initiated SGLT2i or DPP4i from 2014 to 2018. Patients were matched by propensity scores. The primary outcome was the 3-point major adverse cardiovascular events (3P-MACE). Results After matching, we included 3216 patients/group, with mean age of 63 years, diabetes duration of 8.7 years, and 20% had cardiovascular disease. During a median follow-up of 18 months, the rate of 3P-MACE was lower among patients who initiated SGLT2i versus DPP4i (HR 0.74; 95 %C.I. 0.58–0.94). Initiators of SGLT2i also showed significantly lower rates of myocardial infarction (HR 0.75; 95 %C.I. 0.56–1.00), hospitalization for heart failure (HR 0.44; 95 %C.I. 0.25–0.95) or cardiovascular causes (HR 0.72; 95 %C.I. 0.60–0.87), and all-cause death (HR 0.49; 95 %C.I. 0.25–0.95). Renal failure was less common with SGLT2i than with DPP4i. Results were consistent to those obtained in a meta-analysis of 10 observational studies on ~1.5M patients. Conclusions Patients with T2D who initiated SGLT2i under routine care had better cardio-renal outcomes and lower all-cause mortality than similar patients who initiated DPP4i.

Background Cardiovascular outcome trials in high-risk patients showed that some GLP-1 receptor agonists (GLP-1RA), but not dipeptidyl-peptidase-4 inhibitors (DPP-4i), can prevent cardiovascular events in type 2 diabetes (T2D). Since no trial has directly compared these two classes of drugs, we performed a comparative outcome analysis using real-world data. Methods From a database of ~ 5 million people from North-East Italy, we retrospectively identified initiators of GLP-1RA or DPP-4i from 2011 to 2018. We obtained two balanced cohorts by 1:1 propensity score matching. The primary outcome was the 3-point major adverse cardiovascular events (3P-MACE; a composite of death, myocardial infarction, or stroke). 3P-MACE components and hospitalization for heart failure were secondary outcomes. Results From 330,193 individuals with T2D, we extracted two matched cohorts of 2807 GLP-1RA and 2807 DPP-4i initiators, followed for a median of 18 months. On average, patients were 63 years old, 60% male; 15% had pre-existing cardiovascular disease. The rate of 3P-MACE was lower in patients treated with GLP-1RA compared to DPP4i (23.5 vs. 34.9 events per 1000 person-years; HR: 0.67; 95% C.I. 0.53–0.86; p = 0.002). Rates of myocardial infarction (HR 0.67; 95% C.I. 0.50–0.91; p = 0.011) and all-cause death (HR 0.58; 95% C.I. 0.35–0.96; p = 0.034) were lower among GLP-1RA initiators. The as-treated and intention-to-treat approaches yielded similar results. Conclusions Patients initiating a GLP-1RA in clinical practice had better cardiovascular outcomes than similar patients who initiated a DPP-4i. These data strongly confirm findings from cardiovascular outcome trials in a lower risk population.

Aims Concerns have been raised that dipeptidyl-peptidase 4 inhibitors (DPP-4i) may increase the risk of pneumonia. We analysed observational data and clinical trials to explore whether use of DPP-4i modifies the risk of pneumonia. Methods We identified patients with diabetes in the Veneto Region administrative database and performed a propensity score matching (PSM) between new users of DPP-4 inhibitors and new users of other oral glucose lowering medications (OGLM). We compared the rate of hospitalization for pneumonia between matched cohorts using the Cox proportional hazard model. The same analysis was repeated using the database of a local diabetes outpatient clinic. We retrieved similar observational studies from the literature to perform a meta-analysis. Results from trials reporting pneumonia rates among patients randomized to DPP-4 inhibitors versus placebo/active comparator were also meta-analysed. Results In the Regional database, after matching 6495 patients/group, new users of DPP-4 inhibitors had a lower rate of hospitalization for pneumonia than new users of other OGLM (HR 0.76; 95% C.I. 0.61-0.95). In the outpatient database, after matching 867 patients/group, new users of DPP-4 inhibitors showed a non-significantly lower rate of hospitalization for pneumonia (HR 0.65; 95% C.I. 0.41-1.04). The meta-analysis of observational studies yielded an overall non-significant lower risk of hospitalization for pneumonia among DPP-4i users (RR 0.81; 95% C.I. 0.65-1.01). The meta-analysis of randomized controlled trials showed no overall effect of DPP-4i on pneumonia risk (RR 1.06; 95% C.I. 0.93-1.20). Conclusion Use of DPP-4i can be considered safe with regards to the risk of pneumonia. This article is protected by copyright. All rights reserved.

Due to the heterogeneity of existing European sources of observational healthcare data, data source-tailored choices are needed to execute multi-data source, multi-national epidemiological studies. This makes transparent documentation paramount. In this proof-of-concept study, a novel standard data derivation procedure was tested in a set of heterogeneous data sources. Identification of subjects with type 2 diabetes (T2DM) was the test case. We included three primary care data sources (PCDs), three record linkage of administrative and/or registry data sources (RLDs), one hospital and one biobank. Overall, data from 12 million subjects from six European countries were extracted. Based on a shared event definition, sixteeen standard algorithms (components) useful to identify T2DM cases were generated through a top-down/bottom-up iterative approach. Each component was based on one single data domain among diagnoses, drugs, diagnostic test utilization and laboratory results. Diagnoses-based components were subclassified considering the healthcare setting (primary, secondary, inpatient care). The Unified Medical Language System was used for semantic harmonization within data domains. Individual components were extracted and proportion of population identified was compared across data sources. Drug-based components performed similarly in RLDs and PCDs, unlike diagnoses-based components. Using components as building blocks, logical combinations with AND, OR, AND NOT were tested and local experts recommended their preferred data source-tailored combination. The population identified per data sources by resulting algorithms varied from 3.5% to 15.7%, however, age-specific results were fairly comparable. The impact of individual components was assessed: diagnoses-based components identified the majority of cases in PCDs (93-100%), while drug-based components were the main contributors in RLDs (81-100%). The proposed data derivation procedure allowed the generation of data source-tailored case-finding algorithms in a standardized fashion, facilitated transparent documentation of the process and benchmarking of data sources, and provided bases for interpretation of possible inter-data source inconsistency of findings in future studies. The research leading to these results has received support from the Innovative Medicines Initiative Joint Undertaking (http://www.imi.europa.eu/) under European Medical Information Framework grant agreement no. 115372, resources of which are composed of financial contribution from the European Union's Seventh Framework Programme (FP7/2007-2013) and European Federation of Pharmaceutical Industries and Association companies’ in kind contribution. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Pfizer Worldwide Research and Development, GlaxoSmithKline, Cegedim Strategic Data Medical Research Ltd and Janssen provided support in the form of salaries for AKL, PE, DA and MJS, respectively, but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section.