Effectiveness and safety of apixaban versus warfarin in non-valvular atrial fibrillation patients in “real-world” clinical practice

Li, Xiaoyan Shawn; Deitelzweig, Steve; Keshishian, Allison; Hamilton, Melissa; Horblyuk, Ruslan; Gupta, Kiran; Luo, Xuemei; Mardekian, Jack; Friend, Keith; Nadkarni, Anagha; Pan, Xiangbin; Lip, Gregory Y.H.

doi:10.1160/th17-01-0068

Cited by 148 publications

(164 citation statements)

References 27 publications

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“…The third study compared the effectiveness of apixaban versus warfarin in nonvalvular atrial fibrillation (NVAF) patients . In the original study, data were pooled from MarketScan and 3 other large US claims databases (PharMetrics, Optum, and Humana) and patients were followed up for stroke/systemic embolism (SE) and major bleeding.…”

Section: Simulation Experimentsmentioning

confidence: 99%

“…The third study compared the effectiveness of apixaban versus warfarin in nonvalvular atrial fibrillation (NVAF) patients. 32 In the original study, data were pooled from MarketScan and 3 other large US claims databases (PharMetrics, Optum, and Humana) and patients were followed up for stroke/systemic embolism (SE) and major bleeding. Using MarketScan data only, we identified 163 336 NVAF patients that were newly initiated on apixaban (approved by the US Food and Drug Administration in December 2012) or warfarin from January 1, 2013, to December 31, 2015, (8% initiated on apixaban versus 92% on warfarin).…”

Section: Empirical Datamentioning

confidence: 99%

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Comparing methods for estimation of heterogeneous treatment effects using observational data from health care databases

Wendling

Jung

Callahan

et al. 2018

Statistics in Medicine

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There is growing interest in using routinely collected data from health care databases to study the safety and effectiveness of therapies in "real-world" conditions, as it can provide complementary evidence to that of randomized controlled trials. Causal inference from health care databases is challenging because the data are typically noisy, high dimensional, and most importantly, observational. It requires methods that can estimate heterogeneous treatment effects while controlling for confounding in high dimensions. Bayesian additive regression trees, causal forests, causal boosting, and causal multivariate adaptive regression splines are off-the-shelf methods that have shown good performance for estimation of heterogeneous treatment effects in observational studies of continuous outcomes. However, it is not clear how these methods would perform in health care database studies where outcomes are often binary and rare and data structures are complex. In this study, we evaluate these methods in simulation studies that recapitulate key characteristics of comparative effectiveness studies. We focus on the conditional average effect of a binary treatment on a binary outcome using the conditional risk difference as an estimand. To emulate health care database studies, we propose a simulation design where real covariate and treatment assignment data are used and only outcomes are simulated based on nonparametric models of the real outcomes. We apply this design to 4 published observational studies that used records from 2 major health care databases in the United States. Our results suggest that Bayesian additive regression trees and causal boosting consistently provide low bias in conditional risk difference estimates in the context of health care database studies.

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Section: Simulation Experimentsmentioning

confidence: 99%

Section: Empirical Datamentioning

confidence: 99%

Comparing methods for estimation of heterogeneous treatment effects using observational data from health care databases

Wendling

Jung

Callahan

et al. 2018

Statistics in Medicine

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“…Since 2014, several real‐world observational studies investigated the bleeding risk of NOAC in many countries . Annex 10 reports some characteristics of these postapproval published studies and shows heterogeneity for many aspects: most of them used retrospective data from nationwide administrative or insurance databases with limited clinical information – no access for patient's mortality .…”

Section: Discussionmentioning

confidence: 99%

“…International multicentre trials have shown noninferiority to warfarin in patients with AF with lower risk of intracranial haemorrhage but a higher risk of gastrointestinal bleeding . Several reports from registries and analysis of claims databases have recently suggested, compared with VKA, a similar safety profile of NOAC in the community and in randomized trials. However, meta‐analyses highlighted inconsistency among those observational studies using different designs: Weeda et al.…”

Section: Introductionmentioning

confidence: 99%

Major bleeding with antithrombotic agents: a 2012–2015 study using the French nationwide Health Insurance database linked to emergency department records within five areas – rationale and design of SACHA study

Bouget¹,

Balusson²,

Scailteux³

et al. 2019

Fundamemntal Clinical Pharma

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Bleeding represents the most recognized and feared complications of antithrombotic drugs including oral anticoagulants. Previous studies showed inconsistent results on the safety profile. Among explanations, bleeding definition could vary and classification bias exists related to the lack of medical evaluation. To quantify the risk of major haemorrhagic event and event‐free survival associated with antithrombotic drugs (vitamin K antagonist [VKA], non‐VKA anticoagulant [NOAC], antiplatelet agent, parenteral anticoagulant) in 2012–2015, we linked the French nationwide Health Insurance database (SNIIRAM) with a local ‘emergency database’ (clinical and biological data collected in clinical records). In the VKA‐NOAC comparison, a Cox regression analysis will be used to estimate the hazard ratio of major haemorrhagic event adjusted on gender, modified HAS‐BLED score and comorbidities. A distinction on the type of major haemorrhagic event (intracranial, gastrointestinal and other haemorrhagic events) was made. We present here the study protocol and the database linkage results. Using six linkage keys, among 3 837 557 hospital visits identified in SNIIRAM, 5264 have been matched with a major haemorrhagic event identified in the ‘emergency database’, thus clinically confirmed. The 1090 unmatched haemorrhagic events could be explained by the fact that patients were not extracted in the SNIIRAM database (patients living in accommodation establishment with internal use of pharmacy, military people with specific insurance…). We showed the value of SNIIRAM enrichment with a clinical database, a necessary step to categorize haemorrhagic events by a clinically relevant definition and medical validation; it will allow to estimate more accuracy each type of haemorrhagic event.

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“…For example, assuming two sets of event rates for major bleeding of 2.5/100 PYs (OAC A 1 ) vs 2.0/100 PYs (OAC B 1 ) or 6.0/100 PYs (OAC A 2 ) vs 4.8/100 PYs (OAC B 2 ), the resulting hazard ratios would be identical (at 1.25), but absolute differences and interpretation of the clinical relevance would vary substantially (Δ 1 = 0.5%/100 PYs, NNH = 200; and Δ 2 = 1.2%/100 PYs, NNH = 84). Most claims analyses of OAC in NVAF patients report both hazard ratios and absolute risk rates, with bleeding event estimates of the latter ranging from 2.5 to 7.5 events/100 PYs. Given the potential impact that overestimation (or underestimation) of bleeding risk may have on the interpretation of claims database study results, it is important that steps are taken whenever possible to assure the most accurate estimation of event rates to allow for optimal risk–benefit assessment and to not scare clinicians away from proper OAC use (either initiation, continued use, or appropriate dosing) due to undue concern over bleeding.…”

Section: Discussionmentioning

confidence: 99%

Agreement between coding schemas used to identify bleeding‐related hospitalizations in claims analyses of nonvalvular atrial fibrillation patients

Coleman

Vaitsiakhovich

Nguyen

et al. 2018

Clinical Cardiology

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Background Schemas to identify bleeding‐related hospitalizations in claims data differ in billing codes used and coding positions allowed. We assessed agreement across bleeding‐related hospitalization coding schemas for claims analyses of nonvalvular atrial fibrillation (NVAF) patients on oral anticoagulation (OAC). Hypothesis We hypothesized that prior coding schemas used to identify bleeding‐related hospitalizations in claim database studies would provide varying levels of agreement in incidence rates. Methods Within MarketScan data, we identified adults, newly started on OAC for NVAF from January 2012 to June 2015. Billing code schemas developed by Cunningham et al., the US Food and Drug Administration (FDA) Mini‐Sentinel program, and Yao et al. were used to identify bleeding‐related hospitalizations as a surrogate for major bleeding. Bleeds were subcategorized as intracranial hemorrhage (ICH), gastrointestinal (GI), or other. Schema agreement was assessed by comparing incidence, rates of events/100 person‐years (PYs), and Cohen's kappa statistic. Results We identified 151 738 new‐users of OAC with NVAF (CHA2DS2‐VASc score = 3, [interquartile range = 2–4] and median HAS‐BLED score = 3 [interquartile range = 2–3]). The Cunningham, FDA Mini‐Sentinel, and Yao schemas identified any bleeding‐related hospitalizations in 1.87% (95% confidence interval [CI]: 1.81‐1.94), 2.65% (95% CI: 2.57‐2.74), and 4.66% (95% CI: 4.55‐4.76) of patients (corresponding rates = 3.45, 4.90, and 8.65 events/100 PYs). Kappa agreement across schemas was weak‐to‐moderate (κ = 0.47–0.66) for any bleeding hospitalization. Near‐perfect agreement (κ = 0.99) was observed with the FDA Mini‐Sentinel and Yao schemas for ICH‐related hospitalizations, but agreement was weak when comparing Cunningham to FDA Mini‐Sentinel or Yao (κ = 0.52–0.53). FDA Mini‐Sentinel and Yao agreement was moderate (κ = 0.62) for GI bleeding, but agreement was weak when comparing Cunningham to FDA Mini‐Sentinel or Yao (κ = 0.44–0.56). For other bleeds, agreement across schemas was minimal (κ = 0.14–0.38). Conclusions We observed varying levels of agreement among 3 bleeding‐related hospitalizations schemas in NVAF patients.

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Effectiveness and safety of apixaban versus warfarin in non-valvular atrial fibrillation patients in “real-world” clinical practice

Cited by 148 publications

References 27 publications

Comparing methods for estimation of heterogeneous treatment effects using observational data from health care databases

Comparing methods for estimation of heterogeneous treatment effects using observational data from health care databases

Major bleeding with antithrombotic agents: a 2012–2015 study using the French nationwide Health Insurance database linked to emergency department records within five areas – rationale and design of SACHA study

Agreement between coding schemas used to identify bleeding‐related hospitalizations in claims analyses of nonvalvular atrial fibrillation patients

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