Last data update: Sep 16, 2024. (Total: 47680 publications since 2009)
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Query Trace: Bittl JA [original query] |
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Bayesian analysis: A practical approach to interpret clinical trials and create clinical practice guidelines
Bittl JA , He Y . Circ Cardiovasc Qual Outcomes 2017 10 (8) Bayesian analysis is firmly grounded in the science of probability and has been increasingly supplementing or replacing traditional approaches based on P values. In this review, we present gradually more complex examples, along with programming code and data sets, to show how Bayesian analysis takes evidence from randomized clinical trials to update what is already known about specific treatments in cardiovascular medicine. In the example of revascularization choices for diabetic patients who have multivessel coronary artery disease, we combine the results of the FREEDOM trial (Future Revascularization Evaluation in Patients with Diabetes Mellitus: Optimal Management of Multivessel Disease) with prior probability distributions to show how strongly we should believe in the new Class I recommendation ("should be done") for a preference of bypass surgery over percutaneous coronary intervention. In the debate about the duration of dual antiplatelet therapy after drug-eluting stent implantation, we avoid a common pitfall in traditional meta-analysis and create a network of randomized clinical trials to compare outcomes after specific treatment durations. Although we find no credible increase in mortality, we affirm the tradeoff between increased bleeding and reduced myocardial infarctions with prolonged dual antiplatelet therapy, findings that support the new Class IIb recommendation ("may be considered") to extend dual antiplatelet therapy after drug-eluting stent implantation. In the decision between culprit artery-only and multivessel percutaneous coronary intervention in patients with ST-segment elevation myocardial infarction, we use hierarchical meta-analysis to analyze evidence from observational studies and randomized clinical trials and find that the probability of all-cause mortality at longest follow-up is similar after both strategies, a finding that challenges the older ban against noninfarct-artery intervention during primary percutaneous coronary intervention. These examples illustrate how Bayesian analysis integrates new trial information with existing knowledge to reduce uncertainty and change attitudes about treatments in cardiovascular medicine. |
Factors affecting bleeding and stent thrombosis in clinical trials comparing bivalirudin with heparin during percutaneous coronary intervention
Bittl JA , He Y , Lang CD , Dangas GD . Circ Cardiovasc Interv 2015 8 (12) e002789 BACKGROUND: Patients treated with bivalirudin in randomized clinical trials of percutaneous coronary intervention generally have less bleeding but more acute stent thrombosis (ST) than do patients treated with heparin, but differences have varied among trials. METHODS AND RESULTS: We modeled the risk of major hemorrhage and ischemic outcomes 30 days after percutaneous coronary intervention by treatment assignment and the use of adjunctive therapies in 18 randomized clinical trials enrolling 41 871 patients. Overall bivalirudin caused less major bleeding (odds ratio [OR], 0.64; 95% confidence interval [CI], 0.53-0.76), more ST (OR, 1.58; 95% CI, 1.19-2.09), and no difference in mortality (OR, 0.93; 95% CI, 0.77-1.14) than heparin. A risk-benefit analysis identified 19 fewer bleeds and 5 more STs for every 1000 patients treated with bivalirudin in place of heparin. No significant bleeding advantage of bivalirudin over heparin could be identified in randomized clinical trials when transradial access (OR, 0.89; 95% CI, 0.57-1.41) and planned glycoprotein IIb/IIIa inhibitors were used with bivalirudin in the majority of patients (OR, 1.07; 95% CI, 0.87-1.31). The use of prasugrel or ticagrelor eliminated bleeding differences (OR, 0.80; 95% CI, 0.63-1.03) but did not reduce the risk of ST after bivalirudin (OR, 2.20; 95% CI, 1.48-3.27). CONCLUSIONS: Substituting bivalirudin for heparin conferred a tradeoff between bleeding and ST. Transradial access, adjunctive glycoprotein IIb/IIIa inhibitors, and potent P2Y12 inhibitors attenuated the bleeding advantage of bivalirudin over heparin but had no apparent effect on early ST. New approaches to reduce bleeding and ischemic complications during percutaneous coronary intervention warrant further investigation. |
Outcomes after multivessel or culprit-vessel intervention for ST-elevation myocardial infarction in patients with multivessel coronary disease: a Bayesian cross-design meta-analysis
Bittl JA , Tamis-Holland JE , Lang CD , He Y . Catheter Cardiovasc Interv 2015 86 Suppl 1 S15-22 INTRODUCTION: During primary percutaneous coronary intervention (PCI), patients with ST-elevation myocardial infarction (STEMI) and multivessel coronary disease can undergo either multivessel intervention (MVI) or culprit-vessel intervention (CVI) only. BACKGROUND: Randomized controlled trials (RCTs) support the use of MVI, but cohort studies support the use of CVI. METHODS: We developed Bayesian models that incorporated parameters for study type and study outcome after MVI or CVI. RESULTS: A total of 18 studies (4 RCTs, 3 matched cohort studies, and 11 unmatched observational studies) enrolled 48,398 patients with STEMI and multivessel CAD and reported outcomes after MVI or CVI-only at the time of primary PCI. Using a Bayesian hierarchical model, we found that the point estimates replicated previously reported trends, but the wide Bayesian credible intervals (BCI) excluded any plausible mortality difference between MVI versus CVI in all three study types: RCTs (odds ratio [OR] 0.60, 95% BCI 0.31-1.20), matched cohort studies (OR 1.37, 95% BCI 0.86-2.24), or unmatched cohort studies (OR 1.16, 95% BCI 0.70-1.89). Both the global summary (OR 1.10, 95% BCI 0.74-1.51) and a sensitivity analysis that weighted the RCTs 1-5 times as much as observational studies revealed no credible advantage of one PCI strategy over the other (OR 1.05, 95% BCI 0.64-1.48). CONCLUSIONS: Bayesian approaches contextualize the comparison of different strategies by study type and suggest that neither MVI nor CVI emerges as a preferred strategy in an analysis that accounts mortality differences. |
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