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

RESEARCH Cardiovascular safety of non-steroidal anti-inflammatory drugs: network meta-analysis Abstract 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). To be included, trials required at least two arms with at least 100 patient years of follow-up. In the case of trials with several arms, we included only arms with at least 100 patient years of follow-up. We excluded trials in patients with cancer. For an intervention to be included in our analyses, at least 10 patients allocated to the intervention had to have had a myocardial infarction in all eligible trials combined. Trial identification and data collection We searched bibliographic databases, relevant conference proceedings, study registers, and the FDA website, manually searched reference lists of relevant articles, and retrieved reports citing relevant articles through the Science Citation Index (see web extra appendix 1). The search was last updated in July 2009. Two investigators independently assessed trials for eligibility and extracted data. If a trial was covered in more than one report we used a hierarchy of data sources: reports to the FDA, peer reviewed articles, reports from the web based repository for results of clinical studies, published abstracts, and other sources, such as trial websites. Finally, we contacted all authors of primary trial reports and manufacturers of relevant non-steroidal anti-inflammatory drugs (Pfizer, Merck, Novartis) for missing outcome data. One independent investigator and two manufacturers (Pfizer and Novartis) provided additional information. Outcome measures The prespecified primary outcome was fatal or non-fatal myocardial infarction. Secondary outcomes were haemorrhagic or ischaemic fatal or non-fatal stroke; cardiovascular death, defined as any death due to cardiovascular causes (for example, myocardial infarction, low output failure, fatal arrhythmia, pulmonary embolism, stroke), and death of unknown cause; death from any cause; and the Antiplatelet Trialists’ Collaboration composite outcome of non-fatal myocardial infarction, non-fatal stroke, or cardiovascular death. Statistical analysis Whenever possible we used results from intention to treat analysis of the longest follow-up available. We excluded comparisons with zero events in both groups from the relevant analysis since such comparisons provide no information on the magnitude of the treatment effect. We used a Bayesian random effects model, which fully preserves randomised treatment comparisons within trials. Analyses were done using Markov chain Monte Carlo methods with minimally informative prior distributions. As measures of treatment effects, we calculated rate ratios based on patient years. We estimated rate ratios from the median of the posterior distribution as well as corresponding 95% credibility intervals. In the presence of minimally informative priors, credibility intervals can be interpreted like conventional confidence intervals. Rate ratios below 1 indicate a detrimental effect of the control intervention throughout. Finally, we calculated confidence levels, defined as the posterior probability that an increase in risk is smaller than a specified threshold. Confidence levels take into account both the magnitude of the pooled rate ratio and the corresponding uncertainty. Precise estimates are more informative and result in sharp increases in the confidence that the rate ratio of a drug does not exceed a specified threshold. When the specified threshold of the rate ratio increases, imprecise estimates that are based on low numbers of events are uninformative and lead to slow increases in confidence and relevant uncertainty even for large rate ratios. We prespecified a rate ratio