Large trials vs meta-analysis of smaller trials: how do their results compare?
Φόρτωση...
Ημερομηνία
Συγγραφείς
Cappelleri, J. C.
Ioannidis, J. P.
Schmid, C. H.
de Ferranti, S. D.
Aubert, M.
Chalmers, T. C.
Lau, J.
Τίτλος Εφημερίδας
Περιοδικό ISSN
Τίτλος τόμου
Εκδότης
Περίληψη
Τύπος
Είδος δημοσίευσης σε συνέδριο
Είδος περιοδικού
peer-reviewed
Είδος εκπαιδευτικού υλικού
Όνομα συνεδρίου
Όνομα περιοδικού
JAMA
Όνομα βιβλίου
Σειρά βιβλίου
Έκδοση βιβλίου
Συμπληρωματικός/δευτερεύων τίτλος
Περιγραφή
OBJECTIVE: To evaluate the results of large clinical trials vs the pooled results of smaller trials. DATA IDENTIFICATION: Meta-analyses with at least 1 "large" study were identified from the Cochrane Pregnancy and Childbirth Database and from MEDLINE (1966-1995). STUDY SELECTION: We used a sample size approach to select 79 meta-analyses with at least 1 large study of 1000 or more patients. We used a statistical power approach to select 61 meta-analyses with at least 1 large study based on statistical power considerations. DATA EXTRACTION: The outcome of interest for each meta-analysis was the primary one stated in the original publication or, when not clearly specified, was decided on clinically. DATA SYNTHESIS: By random effects calculations, we found agreement between large and smaller trials in 90% of the meta-analyses selected by the sample size approach and in 82% of the meta-analyses selected by the statistical power approach. Twice as many disagreements appeared when the variability among large studies and among smaller studies was not considered (ie, fixed effects calculations). Of the 15 disagreements between results of large and smaller trials using the random effects model, plausible explanations were identified in 10 meta-analyses: 5 with differences in the control rate of events between large and smaller trials, 4 with specific protocol or study differences, and 1 with potential publication bias. Two other disagreements were not clinically important, and tentative reasons could be identified for 2 of the remaining 3 disagreements. CONCLUSIONS: Results of smaller studies are usually compatible with the results of large studies, but discrepancies do occur even when the diversity among both large studies and smaller studies is considered. Clinically important differences without a potential explanation are extremely uncommon. Future research should further examine sources of heterogeneity between the results of large and smaller trials.
Περιγραφή
Λέξεις-κλειδιά
Bias (Epidemiology), *Clinical Trials as Topic, Data Interpretation, Statistical, *Meta-Analysis as Topic, Models, Statistical, Regression Analysis
Θεματική κατηγορία
Παραπομπή
Σύνδεσμος
http://www.ncbi.nlm.nih.gov/pubmed/8861993
Γλώσσα
en
Εκδίδον τμήμα/τομέας
Όνομα επιβλέποντος
Εξεταστική επιτροπή
Γενική Περιγραφή / Σχόλια
Ίδρυμα και Σχολή/Τμήμα του υποβάλλοντος
Πανεπιστήμιο Ιωαννίνων. Σχολή Επιστημών Υγείας. Τμήμα Ιατρικής