Reporting of test comparisons in diagnostic accuracy studies: A literature review.
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ABSTRACT:
SUBMITTER: Vali Y
PROVIDER: S-EPMC8246725 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:ObjectiveTo provide guidance on standards for reporting studies of diagnostic test accuracy for dementia disorders.MethodsAn international consensus process on reporting standards in dementia and cognitive impairment (STARDdem) was established, focusing on studies presenting data from which sensitivity and specificity were reported or could be derived. A working group led the initiative through 4 rounds of consensus work, using a modified Delphi process and culminating in a face-to-face consensus meeting in October 2012. The aim of this process was to agree on how best to supplement the generic standards of the STARD statement to enhance their utility and encourage their use in dementia research.ResultsMore than 200 comments were received during the wider consultation rounds. The areas at most risk of inadequate reporting were identified and a set of dementia-specific recommendations to supplement the STARD guidance were developed, including better reporting of patient selection, the reference standard used, avoidance of circularity, and reporting of test-retest reliability.ConclusionSTARDdem is an implementation of the STARD statement in which the original checklist is elaborated and supplemented with guidance pertinent to studies of cognitive disorders. Its adoption is expected to increase transparency, enable more effective evaluation of diagnostic tests in Alzheimer disease and dementia, contribute to greater adherence to methodologic standards, and advance the development of Alzheimer biomarkers.
| S-EPMC4115600 | biostudies-literature
Project description:BackgroundPoor reporting quality in diagnostic accuracy studies hampers an adequate judgment of the validity of the study. The Standards for Reporting of Diagnostic Accuracy Studies (STARD) statement was published to improve the reporting quality of diagnostic accuracy studies. This study aimed to evaluate the adherence of diagnostic accuracy studies published in Annals of Laboratory Medicine (ALM) to STARD 2015 and to identify directions for improvement in the reporting quality of these studies.MethodsTwo independent authors assessed articles published in ALM between 2012-2018 for compliance with 30 STARD 2015 checklist items to identify all eligible diagnostic accuracy studies published during this period. We included 66 diagnostic accuracy studies. A total of the fulfilled STARD items were calculated, and adherence was analyzed on an individual-item basis.ResultsThe overall mean±SD number of STARD items reported for the included studies was 11.2±2.7. Only five (7.6%) studies adhered to more than 50% of the 30 items. No study satisfied more than 80% of the items. Large variability in adherence to reporting standards was detected across items, ranging from 0% to 100%.ConclusionsAdherence to STARD 2015 is suboptimal among diagnostic accuracy studies published in ALM. Our study emphasizes the necessity of adherence to STARD to improve the reporting quality of future diagnostic accuracy studies to be published in ALM.
| S-EPMC6933069 | biostudies-literature
Project description:IntroductionStandards for Reporting of Diagnostic Accuracy Study (STARD) was developed to improve the completeness and transparency of reporting in studies investigating diagnostic test accuracy. However, its current form, STARD 2015 does not address the issues and challenges raised by artificial intelligence (AI)-centred interventions. As such, we propose an AI-specific version of the STARD checklist (STARD-AI), which focuses on the reporting of AI diagnostic test accuracy studies. This paper describes the methods that will be used to develop STARD-AI.Methods and analysisThe development of the STARD-AI checklist can be distilled into six stages. (1) A project organisation phase has been undertaken, during which a Project Team and a Steering Committee were established; (2) An item generation process has been completed following a literature review, a patient and public involvement and engagement exercise and an online scoping survey of international experts; (3) A three-round modified Delphi consensus methodology is underway, which will culminate in a teleconference consensus meeting of experts; (4) Thereafter, the Project Team will draft the initial STARD-AI checklist and the accompanying documents; (5) A piloting phase among expert users will be undertaken to identify items which are either unclear or missing. This process, consisting of surveys and semistructured interviews, will contribute towards the explanation and elaboration document and (6) On finalisation of the manuscripts, the group's efforts turn towards an organised dissemination and implementation strategy to maximise end-user adoption.Ethics and disseminationEthical approval has been granted by the Joint Research Compliance Office at Imperial College London (reference number: 19IC5679). A dissemination strategy will be aimed towards five groups of stakeholders: (1) academia, (2) policy, (3) guidelines and regulation, (4) industry and (5) public and non-specific stakeholders. We anticipate that dissemination will take place in Q3 of 2021.
| S-EPMC8240576 | biostudies-literature
Project description:BackgroundThere are a variety of ways in which accuracy of clinical tests can be summarised in systematic reviews. Variation in reporting of summary measures has only been assessed in a small survey restricted to meta-analyses of screening studies found in a single database. Therefore, we performed this study to assess the measures of accuracy used for reporting results of primary studies as well as their meta-analysis in systematic reviews of test accuracy studies.MethodsRelevant reviews on test accuracy were selected from the Database of Abstracts of Reviews of Effectiveness (1994-2000), which electronically searches seven bibliographic databases and manually searches key resources. The structured abstracts of these reviews were screened and information on accuracy measures was extracted from the full texts of 90 relevant reviews, 60 of which used meta-analysis.ResultsSensitivity or specificity was used for reporting the results of primary studies in 65/90 (72%) reviews, predictive values in 26/90 (28%), and likelihood ratios in 20/90 (22%). For meta-analysis, pooled sensitivity or specificity was used in 35/60 (58%) reviews, pooled predictive values in 11/60 (18%), pooled likelihood ratios in 13/60 (22%), and pooled diagnostic odds ratio in 5/60 (8%). Summary ROC was used in 44/60 (73%) of the meta-analyses. There were no significant differences in measures of test accuracy among reviews published earlier (1994-97) and those published later (1998-2000).ConclusionsThere is considerable variation in ways of reporting and summarising results of test accuracy studies in systematic reviews. There is a need for consensus about the best ways of reporting results of test accuracy studies in reviews.
| S-EPMC100326 | biostudies-literature
Project description:ImportanceSystematic reviews of medical imaging diagnostic test accuracy (DTA) studies are affected by between-study heterogeneity due to a range of factors. Failure to appropriately assess the extent and causes of heterogeneity compromises the interpretability of systematic review findings.ObjectiveTo assess how heterogeneity has been examined in medical imaging DTA studies.Evidence reviewThe PubMed database was searched for systematic reviews of medical imaging DTA studies that performed a meta-analysis. The search was limited to the 40 journals with highest impact factor in the radiology, nuclear medicine, and medical imaging category in the InCites Journal Citation Reports of 2021 to reach a sample size of 200 to 300 included studies. Descriptive analysis was performed to characterize the imaging modality, target condition, type of meta-analysis model used, strategies for evaluating heterogeneity, and sources of heterogeneity identified. Multivariable logistic regression was performed to assess whether any factors were associated with at least 1 source of heterogeneity being identified in the included meta-analyses. Methodological quality evaluation was not performed. Data analysis occurred from October to December 2022.FindingsA total of 242 meta-analyses involving a median (range) of 987 (119-441 510) patients across a diverse range of disease categories and imaging modalities were included. The extent of heterogeneity was adequately described (ie, whether it was absent, low, moderate, or high) in 220 studies (91%) and was most commonly assessed using the I2 statistic (185 studies [76%]) and forest plots (181 studies [75%]). Heterogeneity was rated as moderate to high in 191 studies (79%). Of all included meta-analyses, 122 (50%) performed subgroup analysis and 87 (36%) performed meta-regression. Of the 242 studies assessed, 189 (78%) included 10 or more primary studies. Of these 189 studies, 60 (32%) did not perform meta-regression or subgroup analysis. Reasons for being unable to investigate sources of heterogeneity included inadequate reporting of primary study characteristics and a low number of included primary studies. Use of meta-regression was associated with identification of at least 1 source of variability (odds ratio, 1.90; 95% CI, 1.11-3.23; P = .02).Conclusions and relevanceIn this systematic review of assessment of heterogeneity in medical imaging DTA meta-analyses, most meta-analyses were impacted by a moderate to high level of heterogeneity, presenting interpretive challenges. These findings suggest that, despite the development and availability of more rigorous statistical models, heterogeneity appeared to be incomplete, inconsistently evaluated, or methodologically questionable in many cases, which lessened the interpretability of the analyses performed; comprehensive heterogeneity assessment should be addressed at the author level by improving personal familiarity with appropriate statistical methodology for assessing heterogeneity and involving biostatisticians and epidemiologists in study design, as well as at the editorial level, by mandating adherence to methodologic standards in primary DTA studies and DTA meta-analyses.
| S-EPMC10905313 | biostudies-literature
Project description: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.
| S-EPMC5128957 | biostudies-literature
Project description:ImportanceConference abstracts present information that helps clinicians and researchers to decide whether to attend a presentation. They also provide a source of unpublished research that could potentially be included in systematic reviews. We systematically assessed whether conference abstracts of studies that evaluated the accuracy of a diagnostic test were sufficiently informative.ObservationsWe identified all abstracts describing work presented at the 2010 Annual Meeting of the Association for Research in Vision and Ophthalmology. Abstracts were eligible if they included a measure of diagnostic accuracy, such as sensitivity, specificity, or likelihood ratios. Two independent reviewers evaluated each abstract using a list of 21 items, selected from published guidance for adequate reporting. A total of 126 of 6310 abstracts presented were eligible. Only a minority reported inclusion criteria (5%), clinical setting (24%), patient sampling (10%), reference standard (48%), whether test readers were masked (7%), 2 × 2 tables (16%), and confidence intervals around accuracy estimates (16%). The mean number of items reported was 8.9 of 21 (SD, 2.1; range, 4-17).Conclusions and relevanceCrucial information about study methods and results is often missing in abstracts of diagnostic studies presented at the Association for Research in Vision and Ophthalmology Annual Meeting, making it difficult to assess risk for bias and applicability to specific clinical settings.
| S-EPMC5031079 | biostudies-literature
Project description:BackgroundTo investigate the accuracy of screening tests for gestational diabetes mellitus (GDM) in Southeast Asian pregnant women.MethodsWe searched PubMed (MEDLINE), Web of Science, Cochrane Library, ClinicalTrials.gov, Google Scholar, and Google for relevant articles published in English up to November 2018 using search terms related to GDM, screening tests for GDM and diagnostic performance. The studies were independently screened and selected by both authors. The methodological quality of the included studies was independently assessed by quality assessment of diagnostic accuracy studies 2. A hierarchical summary receiver operating characteristic (HSROC) model was created to estimate the HSROC curve. The summary sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were calculated in a meta-analysis using bivariate random-effects model.ResultsA total of 19 studies were included in which the 100 g oral glucose tolerance test (OGTT) and 75 g OGTT were the two common reference standards for diagnosis of GDM. Most points of diagnostic performance in the HSROC 50 g GCT curve compared with the 100 g OGTT reference standard were clustered in the upper left-hand quadrant. The pooled sensitivity and specificity of the 50 g GCT were 79% (95% confidence interval [CI] 64%-89%) and 74% (95% CI 59%-85%), respectively. For the 75 g OGTT reference standard, the non-fasting 2-hour plasma glucose showed quite similar sensitivity the 50 g GCT compared with the 100 g OGTT reference standard. The pooled sensitivities and specificities of the fasting plasma glucose and hemoglobin A1c were 81% (95% CI 76%-86%) and 70% (95% CI 67%-72%), and 80% (95% CI 66%-90%) and 69% (95% CI 58%-78%), respectively.ConclusionOur findings indicate that the 50 g GCT using the threshold of 140 mg/dL is a good screening test for identifying GDM at 24 to 28 weeks' gestational age for both high-risk and universal screening strategies in Southeast Asian countries. The non-fasting 2-hour PG, fasting plasma glucose or hemoglobin A1c are alternative choices for screening.
| S-EPMC7668444 | biostudies-literature
Project description:Melanoma has the highest mortality rate among skin cancers, and early-diagnosis is essential to maximize survival rate. The current procedure for melanoma diagnosis is based on dermoscopy, i.e., a qualitative visual inspection of lesions with intrinsic limited diagnostic reliability and reproducibility. Other non-invasive diagnostic techniques may represent valuable solutions to retrieve additional objective information of a lesion. This review aims to compare the diagnostic performance of non-invasive techniques, alternative to dermoscopy, for melanoma detection in clinical settings. A systematic review of the available literature was performed using PubMed, Scopus and Google scholar databases (2010-September 2020). All human, in-vivo, non-invasive studies using techniques, alternative to dermoscopy, for melanoma diagnosis were included with no restriction on the recruited population. The reference standard was histology but dermoscopy was accepted only in case of benign lesions. Attributes of the analyzed studies were compared, and the quality was evaluated using CASP Checklist. For studies in which the investigated technique was implemented as a diagnostic tool (DTA studies), the QUADAS-2 tool was applied. For DTA studies that implemented a melanoma vs. other skin lesions classification task, a meta-analysis was performed reporting the SROC curves. Sixty-two references were included in the review, of which thirty-eight were analyzed using QUADAS-2. Study designs were: clinical trials (13), retrospective studies (10), prospective studies (8), pilot studies (10), multitiered study (1); the remain studies were proof of concept or had undefined study type. Studies were divided in categories based on the physical principle employed by each diagnostic technique. Twenty-nine out of thirty-eight DTA studies were included in the meta-analysis. Heterogeneity of studies' types, testing strategy, and diagnostic task limited the systematic comparison of the techniques. Based on the SROC curves, spectroscopy achieved the best performance in terms of sensitivity (93%, 95% CI 92.8-93.2%) and specificity (85.2%, 95%CI 84.9-85.5%), even though there was high concern regarding robustness of metrics. Reflectance-confocal-microscopy, instead, demonstrated higher robustness and a good diagnostic performance (sensitivity 88.2%, 80.3-93.1%; specificity 65.2%, 55-74.2%). Best practice recommendations were proposed to reduce bias in future DTA studies. Particular attention should be dedicated to widen the use of alternative techniques to conventional dermoscopy.
| S-EPMC8103840 | biostudies-literature
Project description:BackgroundSystematic review is an indispensable tool for optimal evidence collection and evaluation in evidence-based medicine. However, the explosive increase of the original literatures makes it difficult to accomplish critical appraisal and regular update. Artificial intelligence (AI) algorithms have been applied to automate the literature screening procedure in medical systematic reviews. In these studies, different algorithms were used and results with great variance were reported. It is therefore imperative to systematically review and analyse the developed automatic methods for literature screening and their effectiveness reported in current studies.MethodsAn electronic search will be conducted using PubMed, Embase, ACM Digital Library, and IEEE Xplore Digital Library databases, as well as literatures found through supplementary search in Google scholar, on automatic methods for literature screening in systematic reviews. Two reviewers will independently conduct the primary screening of the articles and data extraction, in which nonconformities will be solved by discussion with a methodologist. Data will be extracted from eligible studies, including the basic characteristics of study, the information of training set and validation set, and the function and performance of AI algorithms, and summarised in a table. The risk of bias and applicability of the eligible studies will be assessed by the two reviewers independently based on Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2). Quantitative analyses, if appropriate, will also be performed.DiscussionAutomating systematic review process is of great help in reducing workload in evidence-based practice. Results from this systematic review will provide essential summary of the current development of AI algorithms for automatic literature screening in medical evidence synthesis and help to inspire further studies in this field.Systematic review registrationPROSPERO CRD42020170815 (28 April 2020).
| S-EPMC8760775 | biostudies-literature