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Adelakun AR, Turgeon RD, De Vera MA, McGrail K, Loewen PS. Oral anticoagulant switching in patients with atrial fibrillation: a scoping review. BMJ Open 2023; 13:e071907. [PMID: 37185198 PMCID: PMC10151984 DOI: 10.1136/bmjopen-2023-071907] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/17/2023] Open
Abstract
INTRODUCTION Oral anticoagulants (OACs) prevent stroke in patients with atrial fibrillation (AF). Several factors may cause OAC switching. OBJECTIVES To examine the phenomenon of OAC switching in patients with AF, including all available evidence; frequency and patterns of switch, clinical outcomes, adherence, patient-reported outcomes, reasons for switch, factors associated with switch and evidence gaps. DESIGN Scoping review. DATA SOURCES MEDLINE, Embase and Web of Science, up to January 2022. RESULTS Of the 116 included studies, 2/3 examined vitamin K antagonist (VKA) to direct-acting OAC (DOAC) switching. Overall, OAC switching was common and the definition of an OAC switch varied across. Switching from VKA to dabigatran was the most prevalent switch type, but VKA to apixaban has increased in recent years. Patients on DOAC switched more to warfarin than to other DOACs. OAC doses involved in the switches were hardly reported and patients were often censored after the first switch. Switching back to a previously taken OAC (frequently warfarin) occurred in 5%-21% of switchers.The risk of ischaemic stroke and gastrointestinal bleeding in VKA to DOAC switchers compared with non-switchers was conflicting, while there was no difference in the risk of other types of bleeding. The risk of ischaemic stroke in switchers from DOAC versus non-switchers was conflicting. Studies evaluating adherence found no significant changes in adherence after switching from VKA to DOAC, however, an increase in satisfaction with therapy were reported. Reasons for OAC switch, and factors associated with OAC switch were mostly risk factors for stroke and bleeding. Clinical outcomes, adherence and patient-reported outcomes were sparse for switches from DOACs. CONCLUSIONS OAC switching is common in patients with AF and patients often switch back to an OAC they have previously been on. There are aspects of OAC switching that have received little study, especially in switches from DOACs.
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Affiliation(s)
- Adenike R Adelakun
- Faculty of Pharmaceutical Sciences, The University of British Columbia, Vancouver, British Columbia, Canada
- Collaboration for Outcomes Research and Evaluation, Faculty of Pharmaceutical Science, The University of British Columbia, Vancouver, British Columbia, Canada
| | - Ricky D Turgeon
- Faculty of Pharmaceutical Sciences, The University of British Columbia, Vancouver, British Columbia, Canada
- Collaboration for Outcomes Research and Evaluation, Faculty of Pharmaceutical Science, The University of British Columbia, Vancouver, British Columbia, Canada
| | - Mary A De Vera
- Faculty of Pharmaceutical Sciences, The University of British Columbia, Vancouver, British Columbia, Canada
- Collaboration for Outcomes Research and Evaluation, Faculty of Pharmaceutical Science, The University of British Columbia, Vancouver, British Columbia, Canada
| | - Kimberlyn McGrail
- Centre for Health Services and Policy Research, The University of British Columbia, Vancouver, British Columbia, Canada
- School of Population and Public Health, The University of British Columbia, Vancouver, British Columbia, Canada
| | - Peter S Loewen
- Faculty of Pharmaceutical Sciences, The University of British Columbia, Vancouver, British Columbia, Canada
- Collaboration for Outcomes Research and Evaluation, Faculty of Pharmaceutical Science, The University of British Columbia, Vancouver, British Columbia, Canada
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Dalli LL, Kilkenny MF, Arnet I, Sanfilippo FM, Cummings DM, Kapral MK, Kim J, Cameron J, Yap KY, Greenland M, Cadilhac DA. Towards better reporting of the Proportion of Days Covered method in cardiovascular medication adherence: A scoping review and new tool TEN-SPIDERS. Br J Clin Pharmacol 2022; 88:4427-4442. [PMID: 35524398 PMCID: PMC9546055 DOI: 10.1111/bcp.15391] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Revised: 04/29/2022] [Accepted: 05/03/2022] [Indexed: 11/27/2022] Open
Abstract
Although medication adherence is commonly measured in electronic datasets using the proportion of days covered (PDC), no standardized approach is used to calculate and report this measure. We conducted a scoping review to understand the approaches taken to calculate and report the PDC for cardiovascular medicines to develop improved guidance for researchers using this measure. After prespecifying methods in a registered protocol, we searched Ovid Medline, Embase, Scopus, CINAHL Plus and grey literature (1 July 2012 to 14 December 2020) for articles containing the terms “proportion of days covered” and “cardiovascular medicine”, or synonyms and subject headings. Of the 523 articles identified, 316 were reviewed in full and 76 were included (93% observational studies; 47% from the USA; 2 grey literature articles). In 45 articles (59%), the PDC was measured from the first dispensing/claim date. Good adherence was defined as 80% PDC in 61 articles, 56% of which contained a rationale for selecting this threshold. The following parameters, important for deriving the PDC, were often not reported/unclear: switching (53%), early refills (45%), in‐hospital supplies (45%), presupply (28%) and survival (7%). Of the 46 articles where dosing information was unavailable, 59% reported how doses were imputed. To improve the transparent and systematic reporting of the PDC, we propose the TEN‐SPIDERS tool, covering the following PDC parameters: Threshold, Eligibility criteria, Numerator and denominator, Survival, Presupply, In‐hospital supplies, Dosing, Early Refills, and Switching. Use of this tool will standardize reporting of the PDC to facilitate reliable comparisons of medication adherence estimates between studies.
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Affiliation(s)
- Lachlan L Dalli
- Stroke and Ageing Research, Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Victoria, Australia
| | - Monique F Kilkenny
- Stroke and Ageing Research, Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Victoria, Australia.,Stroke Division, Florey Institute of Neuroscience and Mental Health, University of Melbourne, Victoria, Australia
| | - Isabelle Arnet
- Department of Pharmaceutical Sciences, University of Basel, Basel, Switzerland
| | - Frank M Sanfilippo
- School of Population and Global Health, The University of Western Australia, Western Australia, Australia
| | - Doyle M Cummings
- Department of Family Medicine, Brody School of Medicine, East Carolina University, Greenville, North Carolina, USA.,Centre for Health Disparities, East Carolina University, Greenville, North Carolina, USA
| | - Moira K Kapral
- ICES, Toronto, Canada.,Division of General Internal Medicine, Department of Medicine, University of Toronto, Canada.,Institute of Health Policy, Management, and Evaluation, University of Toronto, Canada
| | - Joosup Kim
- Stroke and Ageing Research, Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Victoria, Australia.,Stroke Division, Florey Institute of Neuroscience and Mental Health, University of Melbourne, Victoria, Australia
| | - Jan Cameron
- Stroke and Ageing Research, Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Victoria, Australia.,School of Nursing and Midwifery, Monash University, Victoria, Australia.,Australian Centre for Heart Health, Victoria, Australia
| | - Kevin Y Yap
- Department of Pharmacy, Singapore General Hospital, Singapore.,School of Psychology and Public Health, La Trobe University, Victoria, Australia
| | - Melanie Greenland
- Oxford Vaccine Group, Department of Paediatrics, Centre for Clinical Vaccinology and Tropical Medicine, Churchill Hospital, Oxford, UK.,Nuffield Department of Population Health, Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | - Dominique A Cadilhac
- Stroke and Ageing Research, Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Victoria, Australia.,Stroke Division, Florey Institute of Neuroscience and Mental Health, University of Melbourne, Victoria, Australia
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Sinyavskaya L, Renoux C, Durand M. Defining the duration of the dispensation of oral anticoagulants in administrative healthcare databases. Pharmacoepidemiol Drug Saf 2021; 31:105-109. [PMID: 34714965 DOI: 10.1002/pds.5378] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Revised: 10/16/2021] [Accepted: 10/26/2021] [Indexed: 11/09/2022]
Abstract
PURPOSE In clinical practice, warfarin therapy requires frequent dose adjustments. In pharmacy claims, the days supplied value may not reflect the true duration of warfarin dispensation. This may affect the measures of association comparing the safety of direct oral anticoagulants (DOACs) versus warfarin. METHODS Using Quebec healthcare administrative databases, we formed a cohort of 55 230 patients newly treated with oral anticoagulants between 2010 and 2016. The duration of dispensations was defined using two approaches: the recorded days supplied value, and the longitudinal coverage approximation (data-driven) that may account for individual variation in drug usage patterns. Propensity scores adjusted Cox proportional hazards regression models were used to estimate the hazard ratio (HR) of major bleeding with dabigatran or rivaroxaban versus warfarin. RESULTS Using the days supplied, the mean (and standard deviation) dispensation durations for dabigatran, rivaroxaban, and warfarin were 19 (15), 19 (14), and 13 (12) days, respectively. Using the data-driven approach, the durations were 20 (16), 19 (15), and 15 (16) days, respectively. The choice of the approach had no impact on the HR estimates. CONCLUSIONS In our settings, the data-driven approach closely approximated the recorded days supplied value for the standard dose therapies such as dabigatran and rivaroxaban. For warfarin, the data-driven approach captured more variability in the duration of dispensations compared to the days supplied value, which may better reflect the true drug-taking behavior of warfarin. Both approaches may provide valid estimates when comparing the safety of DOACs versus warfarin.
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Affiliation(s)
- Liliya Sinyavskaya
- Research Center, Centre Hospitalier de l'Université de Montréal (CHUM), Montreal, Québec, Canada
| | - Christel Renoux
- Centre for Clinical Epidemiology, Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Québec, Canada.,Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, Québec, Canada.,Department of Neurology and Neurosurgery, McGill University, Montreal, Québec, Canada
| | - Madeleine Durand
- Research Center, Centre Hospitalier de l'Université de Montréal (CHUM), Montreal, Québec, Canada
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Reweighting Oranges to Apples: Transported RE-LY Trial Versus Nonexperimental Effect Estimates of Anticoagulation in Atrial Fibrillation. Epidemiology 2020; 31:605-613. [PMID: 32740469 DOI: 10.1097/ede.0000000000001230] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
BACKGROUND Results from trials and nonexperimental studies are often directly compared, with little attention paid to differences between study populations. When target and trial population data are available, accounting for these differences through transporting trial results to target populations of interest provides useful perspective. We aimed to compare two-year risk differences (RDs) for ischemic stroke, mortality, and gastrointestinal bleeding in older adults with atrial fibrillation initiating dabigatran and warfarin when using trial transport methods versus nonexperimental methods. METHODS We identified Medicare beneficiaries who initiated warfarin or dabigatran from a 20% nationwide sample. To transport treatment effects observed in the randomized evaluation of long-term anticoagulation trial, we applied inverse odds weights to standardize estimates to two Medicare target populations of interest, initiators of: (1) dabigatran and (2) warfarin. Separately, we conducted a nonexperimental study in the Medicare populations using standardized morbidity ratio weighting to control measured confounding. RESULTS Comparing dabigatran to warfarin, estimated two-year RDs for ischemic stroke were similar with trial transport and nonexperimental methods. However, two-year mortality RDs were closer to the null when using trial transport versus nonexperimental methods for the dabigatran target population (transported RD: -0.57%; nonexperimental RD: -1.9%). Estimated gastrointestinal bleeding RDs from trial transport (dabigatran initiator RD: 1.8%; warfarin initiator RD: 1.9%) appeared more harmful than nonexperimental results (dabigatran initiator RD: 0.14%; warfarin initiator RD: 0.57%). CONCLUSIONS Differences in study populations can and should be considered quantitatively to ensure results are relevant to populations of interest, particularly when comparing trial with nonexperimental findings. See video abstract: http://links.lww.com/EDE/B703.
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Webster-Clark M, Stürmer T, Edwards JK, Poole C, Simpson RJ, Lund JL. Real-world on-treatment and initial treatment absolute risk differences for dabigatran vs warfarin in older US adults. Pharmacoepidemiol Drug Saf 2020; 29:832-841. [PMID: 32666678 DOI: 10.1002/pds.5069] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2019] [Revised: 05/05/2020] [Accepted: 06/01/2020] [Indexed: 11/07/2022]
Abstract
PURPOSE Trials and past observational work compared dabigatran and warfarin in patients with atrial fibrillation, but few reported estimates of absolute harm and benefit under real-world adherence patterns, particularly in older adults that may have differing benefit-harm profiles. We aimed to estimate risk differences for ischemic stroke, death, and gastrointestinal bleeding after initiating dabigatran and warfarin in older adults (a) when patients adhere to treatment and (b) under real-world adherence patterns. METHODS In a 20% sample of nationwide Medicare claims from 2010 to 2015, we identified beneficiaries aged 66 years and older initiating warfarin and dabigatran. We followed individuals from initiation until death or October 2015 (initial treatment, IT) and separately censored individuals' follow-up after drug switches and gaps in supply (on-treatment, OT). We applied inverse probability of treatment and standardized morbidity ratio weights, as well as inverse probability of censoring weights, to estimate two-year risk differences (RDs) for dabigatran vs warfarin. RESULTS We identified 10,717 dabigatran and 74,891 warfarin initiators. Weighted OT RDs suggested decreased ischemic stroke risk for dabigatran vs warfarin; IT RDs indicated increased or no change in ischemic stroke risk. Regardless of follow-up approach and weighting strategy, risk of death appeared lower and risk of gastrointestinal bleeding appeared higher when comparing dabigatran vs warfarin. CONCLUSIONS Dabigatran use was associated with lower risks of mortality and ischemic stroke in routine care when older adults stayed on treatment. IT analyses suggested that these benefits may be diminished under real-world patterns of switching and discontinuation.
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Affiliation(s)
- Michael Webster-Clark
- Department of Epidemiology, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Til Stürmer
- Department of Epidemiology, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Jessie K Edwards
- Department of Epidemiology, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Charles Poole
- Department of Epidemiology, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Ross J Simpson
- Department of Medicine, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Jennifer L Lund
- Department of Epidemiology, University of North Carolina, Chapel Hill, North Carolina, USA
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