Cardiovascular risks and bleeding with non-vitamin K antagonist oral anticoagulant versus warfarin in patients with type 2 diabetes: a tapered matching cohort study

Abstract

Background We compared the risk of bleeding and cardiovascular disease (CVD) events between non-vitamin K antagonist oral anticoagulant (NOAC) and warfarin in people with type 2 diabetes (T2DM). Methods 862 Incident NOAC users and 626 incident warfarin users with T2DM were identified from within 40 UK general practice (1/4/2017–30/9/2018). Outcomes included incident hospitalisation for bleeding, CVD and re-hospitalisation for CVD within 12 months since first anticoagulant prescription, identified from linked hospitalisation data. A tapered matching method was applied to form comparison cohorts: coarsened exact matching restricted the comparison to areas of sufficient overlap in missingness and characteristics: (i) demographic characteristics; (ii) clinical measurements; (iii) prior bleeding and CVD history; (iv) prescriptions with bleeding; (v) anti-hypertensive treatment(s); (vi) anti-diabetes treatment(s). Entropy balancing sequentially balanced NOAC and warfarin users on their distribution of (i–vi). Weighted logistic regression modelling estimated outcome odds ratios (ORs), using entropy balancing weights from steps i–vi. Results The 12-month ORs of bleeding with NOAC (n = 582) vs matched/balanced warfarin (n = 486) were 1.93 (95% confidence interval 0.97–3.84), 2.14 (1.03–4.44), 2.31 (1.10–4.85), 2.42 (1.14–5.14), 2.41 (1.12–5.18), and 2.51 (1.17–5.38) through steps i–vi. ORs for CVD re-hospitalisation was increased with NOAC treatment through steps i–vi: 2.21 (1.04–4.68), 2.13 (1.01–4.52), 2.47 (1.08–5.62), 2.46 (1.02–5.94), 2.51 (1.01–6.20), and 2.66 (1.02–6.94). Conclusions Incident NOAC use among T2DM is associated with increased risk of bleeding hospitalisation and CVD re-hospitalisation compared with incident warfarin use. For T2DM, caution is required in prescribing NOACs as first anticoagulant treatment. Further large-scale replication studies in external datasets are warranted.

Time-to-event comparative effectiveness of NOACs vs VKAs in newly diagnosed non-valvular atrial fibrillation patients

“…This finding agrees with other secondary analyses of treatment effect heterogeneity from clinical trials [19], [12], but not with Pancholy et al [14], who found NOAC to be superior for women (but not men). Small treatment effect heterogeneities associated with patient's sex [5], age [15], and type 2 diabetes status [23] have been reported in observational studies. However, these effects tended to be small and not confirmed by other studies.…”

Ethnic differences in 25-year risk of incident chronic kidney disease among people with type 2 diabetes in New Zealand

“…Furthermore, there is increasing evidence for the role of biochemical markers to measure the multiple pathogenic mechanisms of DKD, which include tubulointerstitial injury due to hyper-reabsorption stress, chronic endothelial damage, disruption of the endothelial glycocalyx, and hyperfiltration-induced podocytopathy 35–37. There is also an increasing need to explore the social determinants of the unexplained differences in DKD outcomes, which include issues such as healthcare access, differential treatment, adherence to treatments, food security, health literacy, systemic racism, and more specific socioeconomic factors 20 3839…”

“…Another key strength of our work was the use of a novel, tapered matching method to form quasi-trial comparative cohorts to compare the risk of each CKD stages II–V between patients with T2DM from different ethnic groups. Through the tapered matching,37 38 we were able to transparently examine how the difference in specific sets of confounders contributed to the risk of each CKD stages II–V. By sequentially controlling for differences in demographic factors, SES, lifestyle risk factors, body measurements, key routinely recorded clinical measurements to patients with T2DM, antidiabetes treatments, antihypertensive treatments, anticoagulant treatments, duration of having diabetes, and period effects of enrollment, we observed how the risks of each stages II–V of CKD compared after each matching step between patients with T2DM from different ethnic backgrounds.…”

“…Entropy balancing, the most popular tapered matching method,18 19 was used to incrementally match the control cohort (NZE) to the focal cohorts (Māori and Pasifika) with additional covariates. This allowed direct observation of how each matched cohort changed in terms of HR and in terms of unmatched covariates.…”

Ethnic Differences in Cancer Rates Among Adults With Type 2 Diabetes in New Zealand From 1994 to 2018

“…A tapered matching method was used to assess ethnic disparities in cancer risks between the focal and control groups because entropy balancing is the most popular approach. 15 , 16 This involved incrementally matching the control cohort (New Zealand European) to the focal cohorts (Māori and Pasifika) using additional covariates and directly observing how the matched cohort changed in terms of hazard ratios (HRs) and in terms of unmatched covariates.…”