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The Article Alert for the week of December 01, 2014 (sample articles)
Glas HE, Glass LM, DiFrancesco JJ. ClinicalTrials.gov: An Underutilized Source of Research Data About the Design and Conduct of Commercial Clinical Trials. Ther Innov Regul Sci. Epub 2014 Oct 13.
Since 2007, the US federal government has required that organizations sponsoring clinical trials with a least one site in the United States submit information on these clinical trials to an existing database: ClinicalTrials.gov. Over time, the number of mandatory variables has grown and will probably continue to grow. The database now represents an important source of descriptive information about the landscape for clinical trials. In addition, it constitutes a rich pool of data to test hypotheses—for instance, what variables are associated with an organization’s ability to correctly estimate study completion times or complete those studies in as short a time frame as possible. This paper concludes that for mandated variables that the authors have labeled study identification, protocol and study design, and study execution, the data set constitutes a potentially very valuable research resource. With the exception of some site-related information, incomplete data did not exceed 3%. The incomplete site data are concentrated in several companies, so it is not unreasonable to assume that those data will also become more complete.
Moons KG, de Groot JA, Bouwmeester W, Vergouwe Y, Mallett S, Altman DG, Reitsma JB, Collins GS. Critical Appraisal and data extraction for systematic reviews of prediction modelling studies: the CHARMS checklist. PLoS Med. 2014 Oct 14;11(10):e1001744. PMID: 25314315.
Carl Moons and colleagues provide a checklist and background explanation for critically appraising and extracting data from systematic reviews of prognostic and diagnostic prediction modelling studies. Please see later in the article for the Editors' Summary.
- FREE FULL TEXT: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4196729/pdf/pmed.1001744.pdf
- DOI: http://dx.doi.org/10.1371/journal.pmed.1001744
- PubMed: http://www.ncbi.nlm.nih.gov/pubmed/25314315
- PubMed Central: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4196729/
van Enst WA, Scholten RJ, Whiting P, Zwinderman AH, Hooft L. Meta-epidemiologic analysis indicates that MEDLINE searches are sufficient for diagnostic test accuracy systematic reviews. J.Clin.Epidemiol. 2014 Jul 1;67(11):1192-9. PMID: 24996667.
Objectives: To investigate how the summary estimates in diagnostic test accuracy (DTA) systematic reviews are affected when searches are limited to MEDLINE.
Study Design and Setting: A systematic search was performed to identify DTA reviews that had conducted exhaustive searches and included a meta-analysis. Primary studies included in selected reviews were assessed to determine whether they were indexed on MEDLINE. The effect of omitting non-MEDLINE studies from meta-analyses was investigated by calculating the summary relative diagnostic odds ratio (RDORs) = DORMEDLINE only/DORall studies. We also calculated the summary difference in sensitivity and specificity between all studies and only MEDLINE-indexed studies.
Results: Ten reviews contributing 15 meta-analyses met inclusion criteria for quantitative analysis. The RDOR comparing MEDLINE-only studies with all studies was 1.04 (95% confidence interval [CI], 0.95, 1.15). Summary estimates of sensitivity and specificity remained almost unchanged (difference in sensitivity: -0.08%; 95% CI -1% to 1%; difference in specificity: -0.1%; 95% CI -0.8% to 1%).
Conclusion: Restricting to studies indexed on MEDLINE did not influence the summary estimates of the meta-analyses in our sample. In certain circumstances, for instance, when resources are limited, it may be appropriate to restrict searches to MEDLINE. However, the impact on individual reviews cannot be predicted.