{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,31]],"date-time":"2026-10-31T13:25:41Z","timestamp":1793453141116,"version":"4.5.0"},"reference-count":26,"publisher":"SAGE Publications","issue":"10","license":[{"start":{"date-parts":[[2017,2,21]],"date-time":"2017-02-21T00:00:00Z","timestamp":1487635200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Stat Methods Med Res"],"published-print":{"date-parts":[[2018,10]]},"abstract":"<jats:p>Data of previous trials with a similar setting are often available in the analysis of clinical trials. Several Bayesian methods have been proposed for including historical data as prior information in the analysis of the current trial, such as the (modified) power prior, the (robust) meta-analytic-predictive prior, the commensurate prior and methods proposed by Pocock and Murray et\u00a0al. We compared these methods and illustrated their use in a practical setting, including an assessment of the comparability of the current and the historical data. The motivating data set consists of randomised controlled trials for acute myeloid leukaemia. A simulation study was used to compare the methods in terms of bias, precision, power and type I error rate. Methods that estimate parameters for the between-trial heterogeneity generally offer the best trade-off of power, precision and type I error, with the meta-analytic-predictive prior being the most promising method. The results show that it can be feasible to include historical data in the analysis of clinical trials, if an appropriate method is used to estimate the heterogeneity between trials, and the historical data satisfy criteria for comparability.<\/jats:p>","DOI":"10.1177\/0962280217694506","type":"journal-article","created":{"date-parts":[[2017,2,22]],"date-time":"2017-02-22T01:52:01Z","timestamp":1487728321000},"page":"3167-3182","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":140,"title":["Including historical data in the analysis of clinical trials: Is it worth the effort?"],"prefix":"10.1177","volume":"27","author":[{"given":"Joost","family":"van Rosmalen","sequence":"first","affiliation":[{"name":"Department of Biostatistics, Erasmus University Medical Center, Rotterdam, the Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David","family":"Dejardin","sequence":"additional","affiliation":[{"name":"F. Hoffmann-La Roche, Basel, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yvette","family":"van Norden","sequence":"additional","affiliation":[{"name":"HOVON Data Center, Department of Hematology, Erasmus MC Cancer Institute, Rotterdam, the Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bob","family":"L\u00f6wenberg","sequence":"additional","affiliation":[{"name":"Department of Hematology, Erasmus University Medical Center, Rotterdam, the Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Emmanuel","family":"Lesaffre","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, Erasmus University Medical Center, Rotterdam, the Netherlands"},{"name":"Interuniversity Institute for Biostatistics and Statistical Bioinformatics, KU Leuven, Leuven, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2017,2,21]]},"reference":[{"key":"bibr1-0962280217694506","doi-asserted-by":"publisher","DOI":"10.1016\/0021-9681(76)90044-8"},{"key":"bibr2-0962280217694506","doi-asserted-by":"publisher","DOI":"10.1214\/ss\/1009212673"},{"key":"bibr3-0962280217694506","doi-asserted-by":"publisher","DOI":"10.1002\/env.752"},{"key":"bibr4-0962280217694506","doi-asserted-by":"publisher","DOI":"10.1002\/sim.3722"},{"key":"bibr5-0962280217694506","doi-asserted-by":"publisher","DOI":"10.1177\/1740774509356002"},{"key":"bibr6-0962280217694506","doi-asserted-by":"publisher","DOI":"10.1111\/biom.12242"},{"key":"bibr7-0962280217694506","doi-asserted-by":"publisher","DOI":"10.1214\/12-BA722"},{"key":"bibr8-0962280217694506","doi-asserted-by":"publisher","DOI":"10.1111\/biom.12115"},{"key":"bibr9-0962280217694506","doi-asserted-by":"publisher","DOI":"10.1002\/sim.4212"},{"key":"bibr10-0962280217694506","doi-asserted-by":"publisher","DOI":"10.1002\/pst.1589"},{"key":"bibr11-0962280217694506","doi-asserted-by":"publisher","DOI":"10.1200\/JCO.1997.15.12.3496"},{"key":"bibr12-0962280217694506","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMoa025406"},{"key":"bibr13-0962280217694506","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMoa1010222"},{"key":"bibr14-0962280217694506","doi-asserted-by":"publisher","DOI":"10.1182\/blood-2011-11-389841"},{"key":"bibr15-0962280217694506","doi-asserted-by":"publisher","DOI":"10.1200\/JCO.2005.06.027"},{"key":"bibr16-0962280217694506","first-page":"111","volume":"4","author":"Bernardo JM","year":"1996","journal-title":"Far East J Math Sci"},{"key":"bibr17-0962280217694506","doi-asserted-by":"publisher","DOI":"10.1002\/sim.6728"},{"key":"bibr18-0962280217694506","doi-asserted-by":"publisher","DOI":"10.1016\/S0378-3758(99)00140-8"},{"key":"bibr19-0962280217694506","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2288-12-183"},{"key":"bibr20-0962280217694506","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.1962.10480660"},{"key":"bibr21-0962280217694506","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467-9868.2007.00650.x"},{"key":"bibr22-0962280217694506","unstructured":"Duan Y.\n                      A modified Bayesian power prior approach with applications in water quality evaluation\n                      . 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