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      Risk of acute myocardial infarction with NSAIDs in real world use: bayesian meta-analysis of individual patient data

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          Abstract

          Objective To characterise the determinants, time course, and risks of acute myocardial infarction associated with use of oral non-steroidal anti-inflammatory drugs (NSAIDs).

          Design Systematic review followed by a one stage bayesian individual patient data meta-analysis.

          Data sources Studies from Canadian and European healthcare databases.

          Review methods Eligible studies were sourced from computerised drug prescription or medical databases, conducted in the general or an elderly population, documented acute myocardial infarction as specific outcome, studied selective cyclo-oxygenase-2 inhibitors (including rofecoxib) and traditional NSAIDs, compared risk of acute myocardial infarction in NSAID users with non-users, allowed for time dependent analyses, and minimised effects of confounding and misclassification bias.

          Exposure and outcomes Drug exposure was modelled as an indicator variable incorporating the specific NSAID, its recency, duration of use, and dose. The outcome measures were the summary adjusted odds ratios of first acute myocardial infarction after study entry for each category of NSAID use at index date (date of acute myocardial infarction for cases, matched date for controls) versus non-use in the preceding year and the posterior probability of acute myocardial infarction.

          Results A cohort of 446 763 individuals including 61 460 with acute myocardial infarction was acquired. Taking any dose of NSAIDs for one week, one month, or more than a month was associated with an increased risk of myocardial infarction. With use for one to seven days the probability of increased myocardial infarction risk (posterior probability of odds ratio >1.0) was 92% for celecoxib, 97% for ibuprofen, and 99% for diclofenac, naproxen, and rofecoxib. The corresponding odds ratios (95% credible intervals) were 1.24 (0.91 to 1.82) for celecoxib, 1.48 (1.00 to 2.26) for ibuprofen, 1.50 (1.06 to 2.04) for diclofenac, 1.53 (1.07 to 2.33) for naproxen, and 1.58 (1.07 to 2.17) for rofecoxib. Greater risk of myocardial infarction was documented for higher dose of NSAIDs. With use for longer than one month, risks did not appear to exceed those associated with shorter durations.

          Conclusions All NSAIDs, including naproxen, were found to be associated with an increased risk of acute myocardial infarction. Risk of myocardial infarction with celecoxib was comparable to that of traditional NSAIDS and was lower than for rofecoxib. Risk was greatest during the first month of NSAID use and with higher doses.

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          Most cited references48

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          Cardiovascular safety of non-steroidal anti-inflammatory drugs: network meta-analysis

          Objective To analyse the available evidence on cardiovascular safety of non-steroidal anti-inflammatory drugs. Design Network meta-analysis. Data sources Bibliographic databases, conference proceedings, study registers, the Food and Drug Administration website, reference lists of relevant articles, and reports citing relevant articles through the Science Citation Index (last update July 2009). Manufacturers of celecoxib and lumiracoxib provided additional data. Study selection All large scale randomised controlled trials comparing any non-steroidal anti-inflammatory drug with other non-steroidal anti-inflammatory drugs or placebo. Two investigators independently assessed eligibility. Data extraction The primary outcome was myocardial infarction. Secondary outcomes included stroke, death from cardiovascular disease, and death from any cause. Two investigators independently extracted data. Data synthesis 31 trials in 116 429 patients with more than 115 000 patient years of follow-up were included. Patients were allocated to naproxen, ibuprofen, diclofenac, celecoxib, etoricoxib, rofecoxib, lumiracoxib, or placebo. Compared with placebo, rofecoxib was associated with the highest risk of myocardial infarction (rate ratio 2.12, 95% credibility interval 1.26 to 3.56), followed by lumiracoxib (2.00, 0.71 to 6.21). Ibuprofen was associated with the highest risk of stroke (3.36, 1.00 to 11.6), followed by diclofenac (2.86, 1.09 to 8.36). Etoricoxib (4.07, 1.23 to 15.7) and diclofenac (3.98, 1.48 to 12.7) were associated with the highest risk of cardiovascular death. Conclusions Although uncertainty remains, little evidence exists to suggest that any of the investigated drugs are safe in cardiovascular terms. Naproxen seemed least harmful. Cardiovascular risk needs to be taken into account when prescribing any non-steroidal anti-inflammatory drug.
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            A structural approach to selection bias.

            The term "selection bias" encompasses various biases in epidemiology. We describe examples of selection bias in case-control studies (eg, inappropriate selection of controls) and cohort studies (eg, informative censoring). We argue that the causal structure underlying the bias in each example is essentially the same: conditioning on a common effect of 2 variables, one of which is either exposure or a cause of exposure and the other is either the outcome or a cause of the outcome. This structure is shared by other biases (eg, adjustment for variables affected by prior exposure). A structural classification of bias distinguishes between biases resulting from conditioning on common effects ("selection bias") and those resulting from the existence of common causes of exposure and outcome ("confounding"). This classification also leads to a unified approach to adjust for selection bias.
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              Blood pressure, stroke, and coronary heart disease. Part 2, Short-term reductions in blood pressure: overview of randomised drug trials in their epidemiological context.

              There are 14 unconfounded randomised trials of antihypertensive drugs (chiefly diuretics or beta-blockers): total 37,000 individuals, mean treatment duration 5 years, mean diastolic blood pressure (DBP) difference 5-6 mm Hg. In prospective observational studies, a long-term difference of 5-6 mm Hg in usual DBP is associated with about 35-40% less stroke and 20-25% less coronary heart disease (CHD). For those dying in the trials, the DBP difference had persisted only 2-3 years, yet an overview showed that vascular mortality was significantly reduced (2p less than 0.0002); non-vascular mortality appeared unchanged. Stroke was reduced by 42% SD 6 (95% confidence interval 35-50%; 289 vs 484 events, 2p less than 0.0001), suggesting that virtually all the epidemiologically expected stroke reduction appears rapidly. CHD was reduced by 14% SD 5 (95% CI 4-22%; 671 vs 771 events, 2p less than 0.01), suggesting that just over half the epidemiologically expected CHD reduction appears rapidly. Although this significant CHD reduction could well be worthwhile, its size remains indefinite for most circumstances (though beta-blockers after myocardial infarction are of substantial benefit). At present, therefore, a sufficiently high risk of stroke (perhaps because of age, blood pressure, or, in particular, history of cerebrovascular disease) may be the clearest indication for antihypertensive treatment.
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                Author and article information

                Contributors
                Role: epidemiologist
                Role: director and associate professor
                Role: biostatistician
                Role: programmer analyst
                Role: senior medical officer in charge of training
                Role: professor
                Role: professor
                Journal
                BMJ
                BMJ
                bmj
                The BMJ
                BMJ Publishing Group Ltd.
                0959-8138
                1756-1833
                2017
                09 May 2017
                : 357
                : j1909
                Affiliations
                [1 ]Department of Pharmacy and Research Centre, Centre hospitalier de l’Université de Montréal, Montreal, H2X 1N4, Canada
                [2 ]Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Canada
                [3 ]Technology Assessment Unit of the McGill University Health Centre, Montreal, Canada
                [4 ]Division of Clinical Epidemiology, McGill University Health Centre–Research Institute, Montreal, Canada
                [5 ]Unit of Primary Care, Hospital District of Helsinki and Uusimaa, Helsinki, Finland
                [6 ]Department of Clinical Epidemiology, Leibniz Institute for Prevention Research and Epidemiology—BIPS, Bremen, Germany
                [7 ]Department of Medicine, McGill University, Montreal, Canada
                Author notes
                Article
                balm036777
                10.1136/bmj.j1909
                5423546
                28487435
                0f96889a-5fe8-4c32-94c9-f1194fdeb50c
                Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions

                This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

                History
                : 10 April 2017
                Categories
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                Medicine
                Medicine

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