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Remote, real-time expert elicitation to determine the prior probability distribution for Bayesian sample size determination in international randomised controlled trials: Bronchiolitis in Infants Placebo Versus Epinephrine and Dexamethasone (BIPED) study
Bayesian methods are increasing in popularity in clinical research. The design of Bayesian clinical trials requires a prior distribution, which can be elicited from experts. In diseases with international differences in management, the elicitation exercise should recruit internationally, making a fa...
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Published in: | Current controlled trials in cardiovascular medicine 2022-04, Vol.23 (1), p.279-279, Article 279 |
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description | Bayesian methods are increasing in popularity in clinical research. The design of Bayesian clinical trials requires a prior distribution, which can be elicited from experts. In diseases with international differences in management, the elicitation exercise should recruit internationally, making a face-to-face elicitation session expensive and more logistically challenging. Thus, we used a remote, real-time elicitation exercise to construct prior distributions. These elicited distributions were then used to determine the sample size of the Bronchiolitis in Infants with Placebo Versus Epinephrine and Dexamethasone (BIPED) study, an international randomised controlled trial in the Pediatric Emergency Research Network (PERN). The BIPED study aims to determine whether the combination of epinephrine and dexamethasone, compared to placebo, is effective in reducing hospital admission for infants presenting with bronchiolitis to the emergency department.
We developed a Web-based tool to support the elicitation of the probability of hospitalisation for infants with bronchiolitis. Experts participated in online workshops to specify their individual prior distributions, which were aggregated using the equal-weighted linear pooling method. Experts were then invited to provide their comments on the aggregated distribution. The average length criterion determined the BIPED sample size.
Fifteen paediatric emergency medicine clinicians from Canada, the USA, Australia and New Zealand participated in three workshops to provide their elicited prior distributions. The mean elicited probability of admission for infants with bronchiolitis was slightly lower for those receiving epinephrine and dexamethasone compared to supportive care in the aggregate distribution. There were substantial differences in the individual beliefs but limited differences between North America and Australasia. From this aggregate distribution, a sample size of 410 patients per arm results in an average 95% credible interval length of less than 9% and a relative predictive power of 90%.
Remote, real-time expert elicitation is a feasible, useful and practical tool to determine a prior distribution for international randomised controlled trials. Bayesian methods can then determine the trial sample size using these elicited prior distributions. The ease and low cost of remote expert elicitation mean that this approach is suitable for future international randomised controlled trials.
ClinicalTrials.gov NCT0 |
doi_str_mv | 10.1186/s13063-022-06240-w |
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We developed a Web-based tool to support the elicitation of the probability of hospitalisation for infants with bronchiolitis. Experts participated in online workshops to specify their individual prior distributions, which were aggregated using the equal-weighted linear pooling method. Experts were then invited to provide their comments on the aggregated distribution. The average length criterion determined the BIPED sample size.
Fifteen paediatric emergency medicine clinicians from Canada, the USA, Australia and New Zealand participated in three workshops to provide their elicited prior distributions. The mean elicited probability of admission for infants with bronchiolitis was slightly lower for those receiving epinephrine and dexamethasone compared to supportive care in the aggregate distribution. There were substantial differences in the individual beliefs but limited differences between North America and Australasia. From this aggregate distribution, a sample size of 410 patients per arm results in an average 95% credible interval length of less than 9% and a relative predictive power of 90%.
Remote, real-time expert elicitation is a feasible, useful and practical tool to determine a prior distribution for international randomised controlled trials. Bayesian methods can then determine the trial sample size using these elicited prior distributions. The ease and low cost of remote expert elicitation mean that this approach is suitable for future international randomised controlled trials.
ClinicalTrials.gov NCT03567473.</description><identifier>ISSN: 1745-6215</identifier><identifier>EISSN: 1745-6215</identifier><identifier>DOI: 10.1186/s13063-022-06240-w</identifier><identifier>PMID: 35410375</identifier><language>eng</language><publisher>England: BioMed Central Ltd</publisher><subject>Bayes Theorem ; Bayesian statistical decision theory ; Bayesian statistics ; Bronchiolitis ; Bronchiolitis - diagnosis ; Bronchiolitis - drug therapy ; Care and treatment ; Child ; Clinical medicine ; Comparative analysis ; Demographic aspects ; Design ; Dexamethasone ; Dexamethasone - therapeutic use ; Drug therapy ; Emergency medical care ; Epinephrine ; Epinephrine - therapeutic use ; Expert elicitation ; Health aspects ; Humans ; Infant ; Infants ; Methodology ; Palliative care ; Patient outcomes ; Pediatrics ; Prior probability distribution ; Probability ; Randomised controlled trials ; Randomized Controlled Trials as Topic ; Rare diseases ; Research ethics ; Sample Size ; Sample size determination ; Steroids ; Trial design</subject><ispartof>Current controlled trials in cardiovascular medicine, 2022-04, Vol.23 (1), p.279-279, Article 279</ispartof><rights>2022. The Author(s).</rights><rights>COPYRIGHT 2022 BioMed Central Ltd.</rights><rights>The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>The Author(s) 2022</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c563t-c7cacf0359b931d7414a8ecbb0c621aac4dcbe4b2ca1162392a75ec9056ccad63</citedby><cites>FETCH-LOGICAL-c563t-c7cacf0359b931d7414a8ecbb0c621aac4dcbe4b2ca1162392a75ec9056ccad63</cites><orcidid>0000-0002-7263-4251</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2730330991?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2730330991?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,27924,27925,37013,38516,43895,53791,53793,74412</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35410375$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Lan, Jingxian</creatorcontrib><creatorcontrib>Plint, Amy C</creatorcontrib><creatorcontrib>Dalziel, Stuart R</creatorcontrib><creatorcontrib>Klassen, Terry P</creatorcontrib><creatorcontrib>Offringa, Martin</creatorcontrib><creatorcontrib>Heath, Anna</creatorcontrib><creatorcontrib>Pediatric Emergency Research Canada (PERC) KIDSCAN/PREDICT BIPED Study Group</creatorcontrib><creatorcontrib>on behalf of the Pediatric Emergency Research Canada (PERC) KIDSCAN/PREDICT BIPED Study Group</creatorcontrib><title>Remote, real-time expert elicitation to determine the prior probability distribution for Bayesian sample size determination in international randomised controlled trials: Bronchiolitis in Infants Placebo Versus Epinephrine and Dexamethasone (BIPED) study</title><title>Current controlled trials in cardiovascular medicine</title><addtitle>Trials</addtitle><description>Bayesian methods are increasing in popularity in clinical research. The design of Bayesian clinical trials requires a prior distribution, which can be elicited from experts. In diseases with international differences in management, the elicitation exercise should recruit internationally, making a face-to-face elicitation session expensive and more logistically challenging. Thus, we used a remote, real-time elicitation exercise to construct prior distributions. These elicited distributions were then used to determine the sample size of the Bronchiolitis in Infants with Placebo Versus Epinephrine and Dexamethasone (BIPED) study, an international randomised controlled trial in the Pediatric Emergency Research Network (PERN). The BIPED study aims to determine whether the combination of epinephrine and dexamethasone, compared to placebo, is effective in reducing hospital admission for infants presenting with bronchiolitis to the emergency department.
We developed a Web-based tool to support the elicitation of the probability of hospitalisation for infants with bronchiolitis. Experts participated in online workshops to specify their individual prior distributions, which were aggregated using the equal-weighted linear pooling method. Experts were then invited to provide their comments on the aggregated distribution. The average length criterion determined the BIPED sample size.
Fifteen paediatric emergency medicine clinicians from Canada, the USA, Australia and New Zealand participated in three workshops to provide their elicited prior distributions. The mean elicited probability of admission for infants with bronchiolitis was slightly lower for those receiving epinephrine and dexamethasone compared to supportive care in the aggregate distribution. There were substantial differences in the individual beliefs but limited differences between North America and Australasia. From this aggregate distribution, a sample size of 410 patients per arm results in an average 95% credible interval length of less than 9% and a relative predictive power of 90%.
Remote, real-time expert elicitation is a feasible, useful and practical tool to determine a prior distribution for international randomised controlled trials. Bayesian methods can then determine the trial sample size using these elicited prior distributions. The ease and low cost of remote expert elicitation mean that this approach is suitable for future international randomised controlled trials.
ClinicalTrials.gov NCT03567473.</description><subject>Bayes Theorem</subject><subject>Bayesian statistical decision theory</subject><subject>Bayesian statistics</subject><subject>Bronchiolitis</subject><subject>Bronchiolitis - diagnosis</subject><subject>Bronchiolitis - drug therapy</subject><subject>Care and treatment</subject><subject>Child</subject><subject>Clinical medicine</subject><subject>Comparative analysis</subject><subject>Demographic aspects</subject><subject>Design</subject><subject>Dexamethasone</subject><subject>Dexamethasone - therapeutic use</subject><subject>Drug therapy</subject><subject>Emergency medical care</subject><subject>Epinephrine</subject><subject>Epinephrine - therapeutic use</subject><subject>Expert elicitation</subject><subject>Health aspects</subject><subject>Humans</subject><subject>Infant</subject><subject>Infants</subject><subject>Methodology</subject><subject>Palliative care</subject><subject>Patient outcomes</subject><subject>Pediatrics</subject><subject>Prior probability distribution</subject><subject>Probability</subject><subject>Randomised controlled trials</subject><subject>Randomized Controlled Trials as Topic</subject><subject>Rare diseases</subject><subject>Research ethics</subject><subject>Sample Size</subject><subject>Sample size determination</subject><subject>Steroids</subject><subject>Trial design</subject><issn>1745-6215</issn><issn>1745-6215</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>COVID</sourceid><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNptk9tu1DAQhiMEoqXwAlwgS9wUiRQ7dk5cIPUErFSJCgG31tiedF058WJ7aZeHR3h3S2kRSpQ44___7BlniuI5oweMdc2byDhteEmrqqRNJWh59aDYZa2oy6Zi9cM7453iSYyXlArec_G42OG1YJS39W7x6zOOPuFrEhBcmeyIBK8XGBJBZ7VNkKyfSPLEYMIw2glJmiNZBOtDfnoFyjqbVsTYmIJVy41-yJNHsMJoYSIRxoVDEu1PvKVssXZ958D2ExwJMBk_2oiGaD-l4J3Lw8wFF9-So-AnPbc-r2fj2jybBphSJOcONCpPvmGIy0hOF3mbi3lYbzYDyQlew4hpDtHnyP7R7Pz05BWJaWlWT4tHQ2bjs5v3XvH1_emX44_l2acPs-PDs1LXDU-lbjXogfK6Vz1nphVMQIdaKapzeQG0MFqhUJUGxpqK9xW0Neqe1o3WYBq-V8y2XOPhUubqjRBW0oOVm4APFxJCstqhBNXShma76DoB9aC4VsYgo5VgDSqTWe-2rMVSjWg05kKBuwe9PzPZubzwP2TX9w3ruwzYvwEE_32JMclcco3OwYR-GWXViL7uGkbX0pf_SC_9Mp-Xy6qWU85p37O_qgvICdhp8HldvYbKw5yM4G3bVVl18B9VvgyONh83DjbH7xmqrUEHH2PA4TZHRuW6A-S2A2TuALnpAHmVTS_uVufW8ueX578Bq_cJoQ</recordid><startdate>20220411</startdate><enddate>20220411</enddate><creator>Lan, Jingxian</creator><creator>Plint, Amy C</creator><creator>Dalziel, Stuart R</creator><creator>Klassen, Terry P</creator><creator>Offringa, Martin</creator><creator>Heath, Anna</creator><general>BioMed Central Ltd</general><general>BioMed Central</general><general>BMC</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7RV</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>COVID</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>K9.</scope><scope>KB0</scope><scope>M0S</scope><scope>M1P</scope><scope>NAPCQ</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0002-7263-4251</orcidid></search><sort><creationdate>20220411</creationdate><title>Remote, real-time expert elicitation to determine the prior probability distribution for Bayesian sample size determination in international randomised controlled trials: Bronchiolitis in Infants Placebo Versus Epinephrine and Dexamethasone (BIPED) study</title><author>Lan, Jingxian ; Plint, Amy C ; Dalziel, Stuart R ; Klassen, Terry P ; Offringa, Martin ; Heath, Anna</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c563t-c7cacf0359b931d7414a8ecbb0c621aac4dcbe4b2ca1162392a75ec9056ccad63</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Bayes Theorem</topic><topic>Bayesian statistical decision theory</topic><topic>Bayesian statistics</topic><topic>Bronchiolitis</topic><topic>Bronchiolitis - diagnosis</topic><topic>Bronchiolitis - drug therapy</topic><topic>Care and treatment</topic><topic>Child</topic><topic>Clinical medicine</topic><topic>Comparative analysis</topic><topic>Demographic aspects</topic><topic>Design</topic><topic>Dexamethasone</topic><topic>Dexamethasone - therapeutic use</topic><topic>Drug therapy</topic><topic>Emergency medical care</topic><topic>Epinephrine</topic><topic>Epinephrine - therapeutic use</topic><topic>Expert elicitation</topic><topic>Health aspects</topic><topic>Humans</topic><topic>Infant</topic><topic>Infants</topic><topic>Methodology</topic><topic>Palliative care</topic><topic>Patient outcomes</topic><topic>Pediatrics</topic><topic>Prior probability distribution</topic><topic>Probability</topic><topic>Randomised controlled trials</topic><topic>Randomized Controlled Trials as Topic</topic><topic>Rare diseases</topic><topic>Research ethics</topic><topic>Sample Size</topic><topic>Sample size determination</topic><topic>Steroids</topic><topic>Trial design</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lan, Jingxian</creatorcontrib><creatorcontrib>Plint, Amy C</creatorcontrib><creatorcontrib>Dalziel, Stuart R</creatorcontrib><creatorcontrib>Klassen, Terry P</creatorcontrib><creatorcontrib>Offringa, Martin</creatorcontrib><creatorcontrib>Heath, Anna</creatorcontrib><creatorcontrib>Pediatric Emergency Research Canada (PERC) KIDSCAN/PREDICT BIPED Study Group</creatorcontrib><creatorcontrib>on behalf of the Pediatric Emergency Research Canada (PERC) KIDSCAN/PREDICT BIPED Study Group</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>ProQuest Nursing & Allied Health Database</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>Coronavirus Research Database</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>PML(ProQuest Medical Library)</collection><collection>Nursing & Allied Health Premium</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Current controlled trials in cardiovascular medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lan, Jingxian</au><au>Plint, Amy C</au><au>Dalziel, Stuart R</au><au>Klassen, Terry P</au><au>Offringa, Martin</au><au>Heath, Anna</au><aucorp>Pediatric Emergency Research Canada (PERC) KIDSCAN/PREDICT BIPED Study Group</aucorp><aucorp>on behalf of the Pediatric Emergency Research Canada (PERC) KIDSCAN/PREDICT BIPED Study Group</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Remote, real-time expert elicitation to determine the prior probability distribution for Bayesian sample size determination in international randomised controlled trials: Bronchiolitis in Infants Placebo Versus Epinephrine and Dexamethasone (BIPED) study</atitle><jtitle>Current controlled trials in cardiovascular medicine</jtitle><addtitle>Trials</addtitle><date>2022-04-11</date><risdate>2022</risdate><volume>23</volume><issue>1</issue><spage>279</spage><epage>279</epage><pages>279-279</pages><artnum>279</artnum><issn>1745-6215</issn><eissn>1745-6215</eissn><abstract>Bayesian methods are increasing in popularity in clinical research. The design of Bayesian clinical trials requires a prior distribution, which can be elicited from experts. In diseases with international differences in management, the elicitation exercise should recruit internationally, making a face-to-face elicitation session expensive and more logistically challenging. Thus, we used a remote, real-time elicitation exercise to construct prior distributions. These elicited distributions were then used to determine the sample size of the Bronchiolitis in Infants with Placebo Versus Epinephrine and Dexamethasone (BIPED) study, an international randomised controlled trial in the Pediatric Emergency Research Network (PERN). The BIPED study aims to determine whether the combination of epinephrine and dexamethasone, compared to placebo, is effective in reducing hospital admission for infants presenting with bronchiolitis to the emergency department.
We developed a Web-based tool to support the elicitation of the probability of hospitalisation for infants with bronchiolitis. Experts participated in online workshops to specify their individual prior distributions, which were aggregated using the equal-weighted linear pooling method. Experts were then invited to provide their comments on the aggregated distribution. The average length criterion determined the BIPED sample size.
Fifteen paediatric emergency medicine clinicians from Canada, the USA, Australia and New Zealand participated in three workshops to provide their elicited prior distributions. The mean elicited probability of admission for infants with bronchiolitis was slightly lower for those receiving epinephrine and dexamethasone compared to supportive care in the aggregate distribution. There were substantial differences in the individual beliefs but limited differences between North America and Australasia. From this aggregate distribution, a sample size of 410 patients per arm results in an average 95% credible interval length of less than 9% and a relative predictive power of 90%.
Remote, real-time expert elicitation is a feasible, useful and practical tool to determine a prior distribution for international randomised controlled trials. Bayesian methods can then determine the trial sample size using these elicited prior distributions. The ease and low cost of remote expert elicitation mean that this approach is suitable for future international randomised controlled trials.
ClinicalTrials.gov NCT03567473.</abstract><cop>England</cop><pub>BioMed Central Ltd</pub><pmid>35410375</pmid><doi>10.1186/s13063-022-06240-w</doi><tpages>1</tpages><orcidid>https://orcid.org/0000-0002-7263-4251</orcidid><oa>free_for_read</oa></addata></record> |
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ispartof | Current controlled trials in cardiovascular medicine, 2022-04, Vol.23 (1), p.279-279, Article 279 |
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subjects | Bayes Theorem Bayesian statistical decision theory Bayesian statistics Bronchiolitis Bronchiolitis - diagnosis Bronchiolitis - drug therapy Care and treatment Child Clinical medicine Comparative analysis Demographic aspects Design Dexamethasone Dexamethasone - therapeutic use Drug therapy Emergency medical care Epinephrine Epinephrine - therapeutic use Expert elicitation Health aspects Humans Infant Infants Methodology Palliative care Patient outcomes Pediatrics Prior probability distribution Probability Randomised controlled trials Randomized Controlled Trials as Topic Rare diseases Research ethics Sample Size Sample size determination Steroids Trial design |
title | Remote, real-time expert elicitation to determine the prior probability distribution for Bayesian sample size determination in international randomised controlled trials: Bronchiolitis in Infants Placebo Versus Epinephrine and Dexamethasone (BIPED) study |
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