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Extracorporeal Membrane Oxygenation for Severe Acute Respiratory Distress Syndrome and Posterior Probability of Mortality Benefit in a Post Hoc Bayesian Analysis of a Randomized Clinical Trial.
JAMA. 2018 12 04; 320(21):2251-2259.JAMA

Abstract

Importance

Bayesian analysis of clinical trial data may provide useful information to aid in study interpretation, especially when trial evidence suggests that the benefits of an intervention are uncertain, such as in a trial that evaluated early extracorporeal membrane oxygenation (ECMO) for severe acute respiratory distress syndrome (ARDS).

Objective

To demonstrate the potential utility of Bayesian analyses by estimating the posterior probability, under various assumptions, that early ECMO was associated with reduced mortality in patients with very severe ARDS in a randomized clinical trial (RCT).

Design and Evidence

A post hoc Bayesian analysis of data from an RCT (ECMO to Rescue Lung Injury in Severe ARDS [EOLIA]) that included 249 patients with very severe ARDS who had been randomized to receive early ECMO (n = 124; mortality at 60 days, 35%) vs initial conventional lung-protective ventilation with the option for rescue ECMO (n = 125, mortality at 60 days, 46%). The trial was designed to detect an absolute risk reduction (ARR) of 20%, relative risk (RR) of 0.67. Statistical prior distributions were specified to represent varying levels of preexisting enthusiasm or skepticism for ECMO and by Bayesian meta-analysis of previously published studies (with downweighting to account for differences and quality between studies). The RR, credible interval (CrI), ARR, and probability of clinically important mortality benefit (varying from RR less than 1 to RR less than 0.67 and ARR from 2% or more to 20% or more) were estimated with Bayesian modeling.

Findings

Combining a minimally informative prior distribution with the findings of the EOLIA trial, the posterior probability of RR less than 1 for mortality at 60 days after randomization was 96% (RR, 0.78 [95% CrI, 0.56-1.04]); the posterior probability of RR less than 0.67 was 18%, the probability of ARR of 2% or more was 92%, and the probability of ARR of 20% or more was 2%. With a moderately enthusiastic prior, equivalent to information from a trial of 264 patients with an RR of 0.78, the estimated RR was 0.78 (95% CrI, 0.63-0.96), the probability of RR less than 1 was 99%, the probability of RR less than 0.67 was 8%, the probability of ARR of 2% or more was 97%, and the probability of ARR of 20% or more was 0%. With a strongly skeptical prior, equivalent to information from a trial of 264 patients with an RR of 1.0, the estimated RR was 0.88 (95% CrI, 0.71-1.09), the probability of RR less than 1 was 88%, the probability of RR less than 0.67 was 0%, the probability of ARR of 2% or more was 78%, and the probability of ARR of 20% or more was 0%. If the prior was informed by previous studies, the estimated RR was 0.71 (95% CrI, 0.55-0.94), the probability of RR less than 1 was 99%, the probability of RR less than 0.67 was 48%, the probability of ARR of 2% or more was 98%, and the probability of ARR of 20% or more was 4%.

Conclusions and Relevance

Post hoc Bayesian analysis of data from a randomized clinical trial of early extracorporeal membrane oxygenation compared with conventional lung-protective ventilation with the option for rescue extracorporeal membrane oxygenation among patients with very severe acute respiratory distress syndrome provides information about the posterior probability of mortality benefit under a broad set of assumptions that may help inform interpretation of the study findings.

Authors+Show Affiliations

Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, Ontario, Canada. Department of Medicine, University Health Network, Toronto, Ontario, Canada. Toronto General Hospital Research Institute, Toronto, Ontario, Canada.Department of Medicine, University Health Network, Toronto, Ontario, Canada. Toronto General Hospital Research Institute, Toronto, Ontario, Canada. Institute for Health Policy, Management, and Evaluation, University of Toronto, Toronto, Ontario, Canada.Département Biostatistique Santé Publique et Information Médicale, Unité de Recherche Clinique, Centre de Pharmacoépidémiologie, Assistance Publique-Hôpitaux de Paris, Hôpitaux Universitaires Pitié Salpêtrière-Charles Foix, Sorbonne Université, Paris, France.Institute for Health Policy, Management, and Evaluation, University of Toronto, Toronto, Ontario, Canada. Department of Anesthesia, University of Toronto, Toronto, Ontario, Canada. Department of Anesthesia and Pain Management, Toronto General Hospital, Toronto, Ontario, Canada. Applied Health Research Centre of the Li Ka Shing Knowledge Institute, Department of Medicine, St Michael's Hospital, University of Toronto, Toronto, Ontario, Canada.Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, Ontario, Canada. Department of Medicine, University Health Network, Toronto, Ontario, Canada. Institute for Health Policy, Management, and Evaluation, University of Toronto, Toronto, Ontario, Canada.Institute for Health Policy, Management, and Evaluation, University of Toronto, Toronto, Ontario, Canada. Applied Health Research Centre of the Li Ka Shing Knowledge Institute, Department of Medicine, St Michael's Hospital, University of Toronto, Toronto, Ontario, Canada.Division of Pulmonary, Allergy, and Critical Care Medicine, Columbia University Medical Center, New York, New York. New York-Presbyterian Hospital, New York.Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, Ontario, Canada. Keenan Centre for Biomedical Research, Li Ka Shing Knowledge Institute, St Michael's Hospital, Toronto, Ontario, Canada.Sorbonne Université INSERM Unité Mixte de Recherche, Institute of Cardiometabolism and Nutrition, Paris, France. Service de Médecine Intensive-Réanimation, Institute de Cardiologie, Assistance Publique-Hôpitaux de Paris Hôpital Pitié-Salpêtrière, Paris, France.

Pub Type(s)

Comparative Study
Journal Article
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

30347031

Citation

Goligher, Ewan C., et al. "Extracorporeal Membrane Oxygenation for Severe Acute Respiratory Distress Syndrome and Posterior Probability of Mortality Benefit in a Post Hoc Bayesian Analysis of a Randomized Clinical Trial." JAMA, vol. 320, no. 21, 2018, pp. 2251-2259.
Goligher EC, Tomlinson G, Hajage D, et al. Extracorporeal Membrane Oxygenation for Severe Acute Respiratory Distress Syndrome and Posterior Probability of Mortality Benefit in a Post Hoc Bayesian Analysis of a Randomized Clinical Trial. JAMA. 2018;320(21):2251-2259.
Goligher, E. C., Tomlinson, G., Hajage, D., Wijeysundera, D. N., Fan, E., Jüni, P., Brodie, D., Slutsky, A. S., & Combes, A. (2018). Extracorporeal Membrane Oxygenation for Severe Acute Respiratory Distress Syndrome and Posterior Probability of Mortality Benefit in a Post Hoc Bayesian Analysis of a Randomized Clinical Trial. JAMA, 320(21), 2251-2259. https://doi.org/10.1001/jama.2018.14276
Goligher EC, et al. Extracorporeal Membrane Oxygenation for Severe Acute Respiratory Distress Syndrome and Posterior Probability of Mortality Benefit in a Post Hoc Bayesian Analysis of a Randomized Clinical Trial. JAMA. 2018 12 4;320(21):2251-2259. PubMed PMID: 30347031.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Extracorporeal Membrane Oxygenation for Severe Acute Respiratory Distress Syndrome and Posterior Probability of Mortality Benefit in a Post Hoc Bayesian Analysis of a Randomized Clinical Trial. AU - Goligher,Ewan C, AU - Tomlinson,George, AU - Hajage,David, AU - Wijeysundera,Duminda N, AU - Fan,Eddy, AU - Jüni,Peter, AU - Brodie,Daniel, AU - Slutsky,Arthur S, AU - Combes,Alain, PY - 2018/10/23/pubmed PY - 2018/12/24/medline PY - 2018/10/23/entrez SP - 2251 EP - 2259 JF - JAMA JO - JAMA VL - 320 IS - 21 N2 - Importance: Bayesian analysis of clinical trial data may provide useful information to aid in study interpretation, especially when trial evidence suggests that the benefits of an intervention are uncertain, such as in a trial that evaluated early extracorporeal membrane oxygenation (ECMO) for severe acute respiratory distress syndrome (ARDS). Objective: To demonstrate the potential utility of Bayesian analyses by estimating the posterior probability, under various assumptions, that early ECMO was associated with reduced mortality in patients with very severe ARDS in a randomized clinical trial (RCT). Design and Evidence: A post hoc Bayesian analysis of data from an RCT (ECMO to Rescue Lung Injury in Severe ARDS [EOLIA]) that included 249 patients with very severe ARDS who had been randomized to receive early ECMO (n = 124; mortality at 60 days, 35%) vs initial conventional lung-protective ventilation with the option for rescue ECMO (n = 125, mortality at 60 days, 46%). The trial was designed to detect an absolute risk reduction (ARR) of 20%, relative risk (RR) of 0.67. Statistical prior distributions were specified to represent varying levels of preexisting enthusiasm or skepticism for ECMO and by Bayesian meta-analysis of previously published studies (with downweighting to account for differences and quality between studies). The RR, credible interval (CrI), ARR, and probability of clinically important mortality benefit (varying from RR less than 1 to RR less than 0.67 and ARR from 2% or more to 20% or more) were estimated with Bayesian modeling. Findings: Combining a minimally informative prior distribution with the findings of the EOLIA trial, the posterior probability of RR less than 1 for mortality at 60 days after randomization was 96% (RR, 0.78 [95% CrI, 0.56-1.04]); the posterior probability of RR less than 0.67 was 18%, the probability of ARR of 2% or more was 92%, and the probability of ARR of 20% or more was 2%. With a moderately enthusiastic prior, equivalent to information from a trial of 264 patients with an RR of 0.78, the estimated RR was 0.78 (95% CrI, 0.63-0.96), the probability of RR less than 1 was 99%, the probability of RR less than 0.67 was 8%, the probability of ARR of 2% or more was 97%, and the probability of ARR of 20% or more was 0%. With a strongly skeptical prior, equivalent to information from a trial of 264 patients with an RR of 1.0, the estimated RR was 0.88 (95% CrI, 0.71-1.09), the probability of RR less than 1 was 88%, the probability of RR less than 0.67 was 0%, the probability of ARR of 2% or more was 78%, and the probability of ARR of 20% or more was 0%. If the prior was informed by previous studies, the estimated RR was 0.71 (95% CrI, 0.55-0.94), the probability of RR less than 1 was 99%, the probability of RR less than 0.67 was 48%, the probability of ARR of 2% or more was 98%, and the probability of ARR of 20% or more was 4%. Conclusions and Relevance: Post hoc Bayesian analysis of data from a randomized clinical trial of early extracorporeal membrane oxygenation compared with conventional lung-protective ventilation with the option for rescue extracorporeal membrane oxygenation among patients with very severe acute respiratory distress syndrome provides information about the posterior probability of mortality benefit under a broad set of assumptions that may help inform interpretation of the study findings. SN - 1538-3598 UR - https://www.unboundmedicine.com/medline/citation/30347031/full_citation L2 - https://jamanetwork.com/journals/jama/fullarticle/10.1001/jama.2018.14276 DB - PRIME DP - Unbound Medicine ER -