Summing up evidence: one answer is not always enough

dc.contributor.authorLau, J.en
dc.contributor.authorIoannidis, J. P.en
dc.contributor.authorSchmid, C. H.en
dc.date.accessioned2015-11-24T18:49:41Z
dc.date.available2015-11-24T18:49:41Z
dc.identifier.issn0140-6736-
dc.identifier.urihttps://olympias.lib.uoi.gr/jspui/handle/123456789/17995
dc.rightsDefault Licence-
dc.subjectEvidence-Based Medicineen
dc.subjectHumansen
dc.subject*Meta-Analysis as Topicen
dc.subjectModels, Statisticalen
dc.subjectRandomized Controlled Trials as Topicen
dc.subjectRegression Analysisen
dc.subjectResearch Designen
dc.subjectSelection Biasen
dc.titleSumming up evidence: one answer is not always enoughen
heal.abstractAre meta-analyses the brave new world, or are the critics of such combined analyses right to say that the biases inherent in clinical trials make them uncombinable? Negative trials are often unreported, and hence can be missed by meta-analysts. And how much heterogeneity between trials is acceptable? A recent major criticism is that large randomised trials do not always agree with a prior meta-analysis. Neither individual trials nor meta-analyses, reporting as they do on population effects, tell how to treat the individual patient. Here we take a more rounded approach to meta-analyses, arguing that their strengths outweigh their weaknesses, although the latter must not be brushed aside.en
heal.accesscampus-
heal.fullTextAvailabilityTRUE-
heal.identifier.primary10.1016/S0140-6736(97)08468-7-
heal.identifier.secondaryhttp://www.ncbi.nlm.nih.gov/pubmed/9439507-
heal.identifier.secondaryhttp://ac.els-cdn.com/S0140673697084687/1-s2.0-S0140673697084687-main.pdf?_tid=ce749e4ee8328723a1e119eff5b54fc3&acdnat=1333364762_a0fd900d57fac99a39ed5330f703ec68-
heal.journalNameLanceten
heal.journalTypepeer-reviewed-
heal.languageen-
heal.publicationDate1998-
heal.recordProviderΠανεπιστήμιο Ιωαννίνων. Σχολή Επιστημών Υγείας. Τμήμα Ιατρικήςel
heal.typejournalArticle-
heal.type.elΆρθρο Περιοδικούel
heal.type.enJournal articleen

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