Early stopping by using stochastic curtailment in a three-arm sequential trial
Interim analysis is important in a large clinical trial for ethical and cost considerations. Sometimes, an interim analysis needs to be performed at an earlier than planned time point. In that case, methods using stochastic curtailment are useful in examining the data for early stopping while contro...
Gespeichert in:
Veröffentlicht in: | Applied statistics 2003-01, Vol.52 (2), p.139-152 |
---|---|
Hauptverfasser: | , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 152 |
---|---|
container_issue | 2 |
container_start_page | 139 |
container_title | Applied statistics |
container_volume | 52 |
creator | Leung, Denis Heng-Yan Wang, You-Gan Amar, David |
description | Interim analysis is important in a large clinical trial for ethical and cost considerations. Sometimes, an interim analysis needs to be performed at an earlier than planned time point. In that case, methods using stochastic curtailment are useful in examining the data for early stopping while controlling the inflation of type I and type II errors. We consider a three-arm randomized study of treatments to reduce perioperative blood loss following major surgery. Owing to slow accrual, an unplanned interim analysis was required by the study team to determine whether the study should be continued. We distinguish two different cases: when all treatments are under direct comparison and when one of the treatments is a control. We used simulations to study the operating characteristics of five different stochastic curtailment methods. We also considered the influence of timing of the interim analyses on the type I error and power of the test. We found that the type I error and power between the different methods can be quite different. The analysis for the perioperative blood loss trial was carried out at approximately a quarter of the planned sample size. We found that there is little evidence that the active treatments are better than a placebo and recommended closure of the trial. |
doi_str_mv | 10.1111/1467-9876.00394 |
format | Article |
fullrecord | <record><control><sourceid>jstor_proqu</sourceid><recordid>TN_cdi_proquest_miscellaneous_38455267</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><jstor_id>3592700</jstor_id><sourcerecordid>3592700</sourcerecordid><originalsourceid>FETCH-LOGICAL-c5124-fc4159497c66c47d41cb71f375722f4b34b473b5634553b65a4b3ae060428a653</originalsourceid><addsrcrecordid>eNqFUctuFDEQtBBILAtnLhx8gdskfnvnCKsQSKIgEV43y2M8rBfPI7YXmL9PDxMtR1rqdqtc5S61EXpOyQmFOKVC6areaHVCCK_FA7Q6Ig_RCjBZ1UyKx-hJznsCQYlYoeszm-KEcxnGMfQ_cDPhQ54bQNzO5hIcdodUbIid7wsOPba47JL3lU0dzv72AHCwEZcE9Sl61NqY_bP7c40-vz37tH1XXX04f799fVU5SZmoWieorEWtnVJO6O-CukbTlmupGWtFw0UjNG-k4kJK3ihpAbOeKCLYxirJ1-jV8u6YBnCQi-lCdj5G2_vhkA3fgJApDcTThejSkHPyrRlT6GyaDCVm3puZt2TmLZm_ewPFxaJIfvTuSG-i3Q8pZ2d-GW4lgzJBMhDBEeYWcoSkvDYUCLvSwWMv733a7Gxsk-1dyP88wGzOyWxTLLzfIfrpfx7Nx5ub7eL1xSLbw3elo4zLmmlgrlG1XIdc_J_jtU0_DczV0ny9Pjff1CV58-WSGcXvAA6urMk</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>38455267</pqid></control><display><type>article</type><title>Early stopping by using stochastic curtailment in a three-arm sequential trial</title><source>RePEc</source><source>Business Source Complete</source><source>JSTOR Mathematics & Statistics</source><source>Access via Wiley Online Library</source><source>JSTOR Archive Collection A-Z Listing</source><source>Oxford University Press Journals All Titles (1996-Current)</source><creator>Leung, Denis Heng-Yan ; Wang, You-Gan ; Amar, David</creator><creatorcontrib>Leung, Denis Heng-Yan ; Wang, You-Gan ; Amar, David</creatorcontrib><description>Interim analysis is important in a large clinical trial for ethical and cost considerations. Sometimes, an interim analysis needs to be performed at an earlier than planned time point. In that case, methods using stochastic curtailment are useful in examining the data for early stopping while controlling the inflation of type I and type II errors. We consider a three-arm randomized study of treatments to reduce perioperative blood loss following major surgery. Owing to slow accrual, an unplanned interim analysis was required by the study team to determine whether the study should be continued. We distinguish two different cases: when all treatments are under direct comparison and when one of the treatments is a control. We used simulations to study the operating characteristics of five different stochastic curtailment methods. We also considered the influence of timing of the interim analyses on the type I error and power of the test. We found that the type I error and power between the different methods can be quite different. The analysis for the perioperative blood loss trial was carried out at approximately a quarter of the planned sample size. We found that there is little evidence that the active treatments are better than a placebo and recommended closure of the trial.</description><identifier>ISSN: 0035-9254</identifier><identifier>EISSN: 1467-9876</identifier><identifier>DOI: 10.1111/1467-9876.00394</identifier><identifier>CODEN: APSTAG</identifier><language>eng</language><publisher>Oxford, UK: Blackwell Publishers</publisher><subject>Antifibrinolytics ; Applications ; Biometrics ; Blood ; Bonferroni adjustment ; Clinical trials ; Conditional power ; Conditional probabilities ; Error rates ; Exact sciences and technology ; Experimentation ; Hypothesis ; Inference from stochastic processes; time series analysis ; Inflation ; Interim analysis ; Mathematics ; Medical sciences ; Null hypothesis ; Placebos ; Predictive power ; Probability and statistics ; Probability theory and stochastic processes ; Sample size ; Sciences and techniques of general use ; Sequential methods ; Simulation ; Special processes (renewal theory, markov renewal processes, semi-markov processes, statistical mechanics type models, applications) ; Statistical analysis ; Statistical methods ; Statistics ; Stochastic curtailment ; Stochastic processes ; Stopping time</subject><ispartof>Applied statistics, 2003-01, Vol.52 (2), p.139-152</ispartof><rights>Copyright 2003 The Royal Statistical Society</rights><rights>2003 INIST-CNRS</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c5124-fc4159497c66c47d41cb71f375722f4b34b473b5634553b65a4b3ae060428a653</citedby><cites>FETCH-LOGICAL-c5124-fc4159497c66c47d41cb71f375722f4b34b473b5634553b65a4b3ae060428a653</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.jstor.org/stable/pdf/3592700$$EPDF$$P50$$Gjstor$$H</linktopdf><linktohtml>$$Uhttps://www.jstor.org/stable/3592700$$EHTML$$P50$$Gjstor$$H</linktohtml><link.rule.ids>315,781,785,804,833,1418,4009,27929,27930,45579,45580,58022,58026,58255,58259</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=14673307$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttp://econpapers.repec.org/article/blajorssc/v_3a52_3ay_3a2003_3ai_3a2_3ap_3a139-152.htm$$DView record in RePEc$$Hfree_for_read</backlink></links><search><creatorcontrib>Leung, Denis Heng-Yan</creatorcontrib><creatorcontrib>Wang, You-Gan</creatorcontrib><creatorcontrib>Amar, David</creatorcontrib><title>Early stopping by using stochastic curtailment in a three-arm sequential trial</title><title>Applied statistics</title><description>Interim analysis is important in a large clinical trial for ethical and cost considerations. Sometimes, an interim analysis needs to be performed at an earlier than planned time point. In that case, methods using stochastic curtailment are useful in examining the data for early stopping while controlling the inflation of type I and type II errors. We consider a three-arm randomized study of treatments to reduce perioperative blood loss following major surgery. Owing to slow accrual, an unplanned interim analysis was required by the study team to determine whether the study should be continued. We distinguish two different cases: when all treatments are under direct comparison and when one of the treatments is a control. We used simulations to study the operating characteristics of five different stochastic curtailment methods. We also considered the influence of timing of the interim analyses on the type I error and power of the test. We found that the type I error and power between the different methods can be quite different. The analysis for the perioperative blood loss trial was carried out at approximately a quarter of the planned sample size. We found that there is little evidence that the active treatments are better than a placebo and recommended closure of the trial.</description><subject>Antifibrinolytics</subject><subject>Applications</subject><subject>Biometrics</subject><subject>Blood</subject><subject>Bonferroni adjustment</subject><subject>Clinical trials</subject><subject>Conditional power</subject><subject>Conditional probabilities</subject><subject>Error rates</subject><subject>Exact sciences and technology</subject><subject>Experimentation</subject><subject>Hypothesis</subject><subject>Inference from stochastic processes; time series analysis</subject><subject>Inflation</subject><subject>Interim analysis</subject><subject>Mathematics</subject><subject>Medical sciences</subject><subject>Null hypothesis</subject><subject>Placebos</subject><subject>Predictive power</subject><subject>Probability and statistics</subject><subject>Probability theory and stochastic processes</subject><subject>Sample size</subject><subject>Sciences and techniques of general use</subject><subject>Sequential methods</subject><subject>Simulation</subject><subject>Special processes (renewal theory, markov renewal processes, semi-markov processes, statistical mechanics type models, applications)</subject><subject>Statistical analysis</subject><subject>Statistical methods</subject><subject>Statistics</subject><subject>Stochastic curtailment</subject><subject>Stochastic processes</subject><subject>Stopping time</subject><issn>0035-9254</issn><issn>1467-9876</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2003</creationdate><recordtype>article</recordtype><sourceid>X2L</sourceid><recordid>eNqFUctuFDEQtBBILAtnLhx8gdskfnvnCKsQSKIgEV43y2M8rBfPI7YXmL9PDxMtR1rqdqtc5S61EXpOyQmFOKVC6areaHVCCK_FA7Q6Ig_RCjBZ1UyKx-hJznsCQYlYoeszm-KEcxnGMfQ_cDPhQ54bQNzO5hIcdodUbIid7wsOPba47JL3lU0dzv72AHCwEZcE9Sl61NqY_bP7c40-vz37tH1XXX04f799fVU5SZmoWieorEWtnVJO6O-CukbTlmupGWtFw0UjNG-k4kJK3ihpAbOeKCLYxirJ1-jV8u6YBnCQi-lCdj5G2_vhkA3fgJApDcTThejSkHPyrRlT6GyaDCVm3puZt2TmLZm_ewPFxaJIfvTuSG-i3Q8pZ2d-GW4lgzJBMhDBEeYWcoSkvDYUCLvSwWMv733a7Gxsk-1dyP88wGzOyWxTLLzfIfrpfx7Nx5ub7eL1xSLbw3elo4zLmmlgrlG1XIdc_J_jtU0_DczV0ny9Pjff1CV58-WSGcXvAA6urMk</recordid><startdate>20030101</startdate><enddate>20030101</enddate><creator>Leung, Denis Heng-Yan</creator><creator>Wang, You-Gan</creator><creator>Amar, David</creator><general>Blackwell Publishers</general><general>Blackwell</general><general>Royal Statistical Society</general><scope>BSCLL</scope><scope>IQODW</scope><scope>DKI</scope><scope>X2L</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>8BJ</scope><scope>FQK</scope><scope>JBE</scope></search><sort><creationdate>20030101</creationdate><title>Early stopping by using stochastic curtailment in a three-arm sequential trial</title><author>Leung, Denis Heng-Yan ; Wang, You-Gan ; Amar, David</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c5124-fc4159497c66c47d41cb71f375722f4b34b473b5634553b65a4b3ae060428a653</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2003</creationdate><topic>Antifibrinolytics</topic><topic>Applications</topic><topic>Biometrics</topic><topic>Blood</topic><topic>Bonferroni adjustment</topic><topic>Clinical trials</topic><topic>Conditional power</topic><topic>Conditional probabilities</topic><topic>Error rates</topic><topic>Exact sciences and technology</topic><topic>Experimentation</topic><topic>Hypothesis</topic><topic>Inference from stochastic processes; time series analysis</topic><topic>Inflation</topic><topic>Interim analysis</topic><topic>Mathematics</topic><topic>Medical sciences</topic><topic>Null hypothesis</topic><topic>Placebos</topic><topic>Predictive power</topic><topic>Probability and statistics</topic><topic>Probability theory and stochastic processes</topic><topic>Sample size</topic><topic>Sciences and techniques of general use</topic><topic>Sequential methods</topic><topic>Simulation</topic><topic>Special processes (renewal theory, markov renewal processes, semi-markov processes, statistical mechanics type models, applications)</topic><topic>Statistical analysis</topic><topic>Statistical methods</topic><topic>Statistics</topic><topic>Stochastic curtailment</topic><topic>Stochastic processes</topic><topic>Stopping time</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Leung, Denis Heng-Yan</creatorcontrib><creatorcontrib>Wang, You-Gan</creatorcontrib><creatorcontrib>Amar, David</creatorcontrib><collection>Istex</collection><collection>Pascal-Francis</collection><collection>RePEc IDEAS</collection><collection>RePEc</collection><collection>CrossRef</collection><collection>International Bibliography of the Social Sciences (IBSS)</collection><collection>International Bibliography of the Social Sciences</collection><collection>International Bibliography of the Social Sciences</collection><jtitle>Applied statistics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Leung, Denis Heng-Yan</au><au>Wang, You-Gan</au><au>Amar, David</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Early stopping by using stochastic curtailment in a three-arm sequential trial</atitle><jtitle>Applied statistics</jtitle><date>2003-01-01</date><risdate>2003</risdate><volume>52</volume><issue>2</issue><spage>139</spage><epage>152</epage><pages>139-152</pages><issn>0035-9254</issn><eissn>1467-9876</eissn><coden>APSTAG</coden><abstract>Interim analysis is important in a large clinical trial for ethical and cost considerations. Sometimes, an interim analysis needs to be performed at an earlier than planned time point. In that case, methods using stochastic curtailment are useful in examining the data for early stopping while controlling the inflation of type I and type II errors. We consider a three-arm randomized study of treatments to reduce perioperative blood loss following major surgery. Owing to slow accrual, an unplanned interim analysis was required by the study team to determine whether the study should be continued. We distinguish two different cases: when all treatments are under direct comparison and when one of the treatments is a control. We used simulations to study the operating characteristics of five different stochastic curtailment methods. We also considered the influence of timing of the interim analyses on the type I error and power of the test. We found that the type I error and power between the different methods can be quite different. The analysis for the perioperative blood loss trial was carried out at approximately a quarter of the planned sample size. We found that there is little evidence that the active treatments are better than a placebo and recommended closure of the trial.</abstract><cop>Oxford, UK</cop><pub>Blackwell Publishers</pub><doi>10.1111/1467-9876.00394</doi><tpages>14</tpages><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 0035-9254 |
ispartof | Applied statistics, 2003-01, Vol.52 (2), p.139-152 |
issn | 0035-9254 1467-9876 |
language | eng |
recordid | cdi_proquest_miscellaneous_38455267 |
source | RePEc; Business Source Complete; JSTOR Mathematics & Statistics; Access via Wiley Online Library; JSTOR Archive Collection A-Z Listing; Oxford University Press Journals All Titles (1996-Current) |
subjects | Antifibrinolytics Applications Biometrics Blood Bonferroni adjustment Clinical trials Conditional power Conditional probabilities Error rates Exact sciences and technology Experimentation Hypothesis Inference from stochastic processes time series analysis Inflation Interim analysis Mathematics Medical sciences Null hypothesis Placebos Predictive power Probability and statistics Probability theory and stochastic processes Sample size Sciences and techniques of general use Sequential methods Simulation Special processes (renewal theory, markov renewal processes, semi-markov processes, statistical mechanics type models, applications) Statistical analysis Statistical methods Statistics Stochastic curtailment Stochastic processes Stopping time |
title | Early stopping by using stochastic curtailment in a three-arm sequential trial |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-12T22%3A37%3A07IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-jstor_proqu&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Early%20stopping%20by%20using%20stochastic%20curtailment%20in%20a%20three-arm%20sequential%20trial&rft.jtitle=Applied%20statistics&rft.au=Leung,%20Denis%20Heng-Yan&rft.date=2003-01-01&rft.volume=52&rft.issue=2&rft.spage=139&rft.epage=152&rft.pages=139-152&rft.issn=0035-9254&rft.eissn=1467-9876&rft.coden=APSTAG&rft_id=info:doi/10.1111/1467-9876.00394&rft_dat=%3Cjstor_proqu%3E3592700%3C/jstor_proqu%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=38455267&rft_id=info:pmid/&rft_jstor_id=3592700&rfr_iscdi=true |