Browsing by Author "Bugden, Shawn C."

Now showing 1 - 2 of 2
  • Thumbnail Image
    ItemOpen Access
    Characteristics of new users of recent antidiabetic drugs in Canada and the United Kingdom
    (2022-09-29) Brunetti, Vanessa C.; St-Jean, Audray; Dell’Aniello, Sophie; Fisher, Anat; Yu, Oriana H. Y.; Bugden, Shawn C.; Daigle, Jean-Marc; Hu, Nianping; Alessi-Severini, Silvia; Shah, Baiju R.; Ronksley, Paul E.; Lix, Lisa M.; Ernst, Pierre; Filion, Kristian B.
    Abstract Background Characteristics of patients using newer 2nd and 3rd line antidiabetic drugs in a real-world setting are poorly understood. We described the characteristics of new users of sodium-glucose co-transporter-2 inhibitors (SGLT-2i), dipeptidyl peptidase-4 inhibitors (DPP-4i), and glucagon-like peptide-1 receptor agonists (GLP-1 RA) in Canada and the United Kingdom (UK) between 2016 and 2018. Methods We conducted a multi-database cohort study using administrative health databases from 7 Canadian provinces and the UK Clinical Practice Research Datalink. We assembled a base cohort of antidiabetic drug users between 2006 and 2018, from which we constructed 3 cohorts of new users of SGLT-2i, DPP-4i, and GLP-1 RA between 2016 and 2018. Results Our cohorts included 194,070 new users of DPP-4i, 166,722 new users of SGLT-2i, and 27,719 new users of GLP-1 RA. New users of GLP-1 RA were more likely to be younger (mean ± SD: 56.7 ± 12.2 years) than new users of DPP-4i (67.8 ± 12.3 years) or SGLT-2i (64.4 ± 11.1 years). In Canada, new users of DPP-4i were more likely to have a history of coronary artery disease (22%) than new users of SGLT-2i (20%) or GLP-1 RA (15%). Conclusion Although SGLT-2i, DPP-4i, and GLP-1 RAs are recommended as 2nd or 3rd line therapy for type 2 diabetes, important differences exist in the characteristics of users of these drugs. Contrary to existing guidelines, new users of DPP-4i had a higher prevalence of cardiovascular disease at baseline than new users of SGLT2i or GLP-1RA.
  • Thumbnail Image
    ItemOpen Access
    Validity of an algorithm to identify cardiovascular deaths from administrative health records: a multi-database population-based cohort study
    (2021-07-31) Lix, Lisa M.; Sobhan, Shamsia; St-Jean, Audray; Daigle, Jean-Marc; Fisher, Anat; Yu, Oriana H. Y.; Dell’Aniello, Sophie; Hu, Nianping; Bugden, Shawn C.; Shah, Baiju R.; Ronksley, Paul E.; Alessi-Severini, Silvia; Douros, Antonios; Ernst, Pierre; Filion, Kristian B.
    Abstract Background Cardiovascular death is a common outcome in population-based studies about new healthcare interventions or treatments, such as new prescription medications. Vital statistics registration systems are often the preferred source of information about cause-specific mortality because they capture verified information about the deceased, but they may not always be accessible for linkage with other sources of population-based data. We assessed the validity of an algorithm applied to administrative health records for identifying cardiovascular deaths in population-based data. Methods Administrative health records were from an existing multi-database cohort study about sodium-glucose cotransporter-2 (SGLT2) inhibitors, a new class of antidiabetic medications. Data were from 2013 to 2018 for five Canadian provinces (Alberta, British Columbia, Manitoba, Ontario, Quebec) and the United Kingdom (UK) Clinical Practice Research Datalink (CPRD). The cardiovascular mortality algorithm was based on in-hospital cardiovascular deaths identified from diagnosis codes and select out-of-hospital deaths. Sensitivity, specificity, and positive and negative predictive values (PPV, NPV) were calculated for the cardiovascular mortality algorithm using vital statistics registrations as the reference standard. Overall and stratified estimates and 95% confidence intervals (CIs) were computed; the latter were produced by site, location of death, sex, and age. Results The cohort included 20,607 individuals (58.3% male; 77.2% ≥70 years). When compared to vital statistics registrations, the cardiovascular mortality algorithm had overall sensitivity of 64.8% (95% CI 63.6, 66.0); site-specific estimates ranged from 54.8 to 87.3%. Overall specificity was 74.9% (95% CI 74.1, 75.6) and overall PPV was 54.5% (95% CI 53.7, 55.3), while site-specific PPV ranged from 33.9 to 72.8%. The cardiovascular mortality algorithm had sensitivity of 57.1% (95% CI 55.4, 58.8) for in-hospital deaths and 72.3% (95% CI 70.8, 73.9) for out-of-hospital deaths; specificity was 88.8% (95% CI 88.1, 89.5) for in-hospital deaths and 58.5% (95% CI 57.3, 59.7) for out-of-hospital deaths. Conclusions A cardiovascular mortality algorithm applied to administrative health records had moderate validity when compared to vital statistics data. Substantial variation existed across study sites representing different geographic locations and two healthcare systems. These variations may reflect different diagnostic coding practices and healthcare utilization patterns.