Publication and Reporting of Test Accuracy Studies Registered in ClinicalTrials.gov

Korevaar, Daniël A.; Ochodo, Eleanor; Bossuyt, Patrick M.; Hooft, Lotty

doi:10.1373/clinchem.2013.218149

Cited by 47 publications

(44 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…gov or one of the WHO Primary Registries, ensures that existence of the studies can be identified. [108][109][110][111][112] This has many advantages, including avoiding overlapping or redundant studies, and allowing colleagues and potential participants to contact the study coordinators.…”

Section: Item 27 Implications For Practice Including the Intended Umentioning

confidence: 99%

STARD 2015 guidelines for reporting diagnostic accuracy studies: explanation and elaboration

et al. 2016

Self Cite

View full text Add to dashboard Cite

Diagnostic accuracy studies are, like other clinical studies, at risk of bias due to shortcomings in design and conduct, and the results of a diagnostic accuracy study may not apply to other patient groups and settings. Readers of study reports need to be informed about study design and conduct, in sufficient detail to judge the trustworthiness and applicability of the study findings. The STARD statement (Standards for Reporting of Diagnostic Accuracy Studies) was developed to improve the completeness and transparency of reports of diagnostic accuracy studies. STARD contains a list of essential items that can be used as a checklist, by authors, reviewers and other readers, to ensure that a report of a diagnostic accuracy study contains the necessary information. STARD was recently updated. All updated STARD materials, including the checklist, are available at http://www.equator-network.org/reporting-guidelines/stard. Here, we present the STARD 2015 explanation and elaboration document. Through commented examples of appropriate reporting, we clarify the rationale for each of the 30 items on the STARD 2015 checklist, and describe what is expected from authors in developing sufficiently informative study reports.

show abstract

Section: Item 27 Implications For Practice Including the Intended Umentioning

confidence: 99%

STARD 2015 guidelines for reporting diagnostic accuracy studies: explanation and elaboration

et al. 2016

Self Cite

View full text Add to dashboard Cite

show abstract

“…Korevaar et al compared prospective registered diagnostic studies to the publications. They concluded that failure to publish and selective publication were prevalent in diagnostic accuracy studies but the dataset was too small to draw firm conclusions [16]. Brazelli and colleagues, however, tracked a cohort of conference abstracts and did not find evidence of publication bias in the process that occurs after abstract acceptance [17].…”

Section: Introductionmentioning

confidence: 99%

Investigation of publication bias in meta-analyses of diagnostic test accuracy: a meta-epidemiological study

Enst

Ochodo

Scholten

et al. 2014

BMC Med Res Methodol

Self Cite

328

196

View full text Add to dashboard Cite

BackgroundThe validity of a meta-analysis can be understood better in light of the possible impact of publication bias. The majority of the methods to investigate publication bias in terms of small study-effects are developed for meta-analyses of intervention studies, leaving authors of diagnostic test accuracy (DTA) systematic reviews with limited guidance. The aim of this study was to evaluate if and how publication bias was assessed in meta-analyses of DTA, and to compare the results of various statistical methods used to assess publication bias.MethodsA systematic search was initiated to identify DTA reviews with a meta-analysis published between September 2011 and January 2012. We extracted all information about publication bias from the reviews and the two-by-two tables. Existing statistical methods for the detection of publication bias were applied on data from the included studies.ResultsOut of 1,335 references, 114 reviews could be included. Publication bias was explicitly mentioned in 75 reviews (65.8%) and 47 of these had performed statistical methods to investigate publication bias in terms of small study-effects: 6 by drawing funnel plots, 16 by statistical testing and 25 by applying both methods. The applied tests were Egger’s test (n = 18), Deeks’ test (n = 12), Begg’s test (n = 5), both the Egger and Begg tests (n = 4), and other tests (n = 2). Our own comparison of the results of Begg’s, Egger’s and Deeks’ test for 92 meta-analyses indicated that up to 34% of the results did not correspond with one another.ConclusionsThe majority of DTA review authors mention or investigate publication bias. They mainly use suboptimal methods like the Begg and Egger tests that are not developed for DTA meta-analyses. Our comparison of the Begg, Egger and Deeks tests indicated that these tests do give different results and thus are not interchangeable. Deeks’ test is recommended for DTA meta-analyses and should be preferred.

show abstract

“…This requirement does not extend, however, to registration of the diagnostic test analytics used in the trials. A recent analysis of ClinicalTrials.gov revealed discrepancies between the registered diagnostic test protocols versus what was reported in the final publications in 32% of the 418 trials reviewed [32].…”

Section: Biospecimens and Biobanksmentioning

confidence: 99%

The national biomarker development alliance: confronting the poor productivity of biomarker research and development

Poste¹,

Compton

Barker

2014

Expert Review of Molecular Diagnostics

View full text Add to dashboard Cite

Making precision (personalized) medicine a routine clinical reality will require a comprehensive inventory of validated biomarkers and molecular diagnostic tests to stratify disease subtypes and improve accuracy in diagnosis and treatment selection. Realization of this promise has been hindered by the poor productivity of biomarker identification and validation. This situation reflects deficiencies that are pervasive across the entire spectrum of biomarker R&D, from discovery to clinical validation and in the failure of regulatory and reimbursement policies to accommodate new classes of biomarkers. The launch of the National Biomarker Development Alliance is the culmination of a 2-year review and consultation process involving diverse stakeholders to advance standards, best practices and guidelines to enhance biomarker discovery and validation by adoption of systems-based approaches and trans-sector collaboration between academia, clinical medicine and relevant private and public sector stakeholders.

show abstract

Publication and Reporting of Test Accuracy Studies Registered in ClinicalTrials.gov

Cited by 47 publications

References 24 publications

STARD 2015 guidelines for reporting diagnostic accuracy studies: explanation and elaboration

STARD 2015 guidelines for reporting diagnostic accuracy studies: explanation and elaboration

Investigation of publication bias in meta-analyses of diagnostic test accuracy: a meta-epidemiological study

The national biomarker development alliance: confronting the poor productivity of biomarker research and development

Contact Info

Product

Resources

About