Blog
About

88
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Commercial Serological Tests for the Diagnosis of Active Pulmonary and Extrapulmonary Tuberculosis: An Updated Systematic Review and Meta-Analysis

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          An up-to-date systematic review and meta-analysis by Karen Steingart and colleagues confirms that commercially available serological tests do not provide an accurate diagnosis of tuberculosis.

          Abstract

          Background

          Serological (antibody detection) tests for tuberculosis (TB) are widely used in developing countries. As part of a World Health Organization policy process, we performed an updated systematic review to assess the diagnostic accuracy of commercial serological tests for pulmonary and extrapulmonary TB with a focus on the relevance of these tests in low- and middle-income countries.

          Methods and Findings

          We used methods recommended by the Cochrane Collaboration and GRADE approach for rating quality of evidence. In a previous review, we searched multiple databases for papers published from 1 January 1990 to 30 May 2006, and in this update, we add additional papers published from that period until 29 June 2010. We prespecified subgroups to address heterogeneity and summarized test performance using bivariate random effects meta-analysis. For pulmonary TB, we included 67 studies (48% from low- and middle-income countries) with 5,147 participants. For all tests, estimates were variable for sensitivity (0% to 100%) and specificity (31% to 100%). For anda-TB IgG, the only test with enough studies for meta-analysis, pooled sensitivity was 76% (95% CI 63%–87%) in smear-positive (seven studies) and 59% (95% CI 10%–96%) in smear-negative (four studies) patients; pooled specificities were 92% (95% CI 74%–98%) and 91% (95% CI 79%–96%), respectively. Compared with ELISA (pooled sensitivity 60% [95% CI 6%–65%]; pooled specificity 98% [95% CI 96%–99%]), immunochromatographic tests yielded lower pooled sensitivity (53%, 95% CI 42%–64%) and comparable pooled specificity (98%, 95% CI 94%–99%). For extrapulmonary TB, we included 25 studies (40% from low- and middle-income countries) with 1,809 participants. For all tests, estimates were variable for sensitivity (0% to 100%) and specificity (59% to 100%). Overall, quality of evidence was graded very low for studies of pulmonary and extrapulmonary TB.

          Conclusions

          Despite expansion of the literature since 2006, commercial serological tests continue to produce inconsistent and imprecise estimates of sensitivity and specificity. Quality of evidence remains very low. These data informed a recently published World Health Organization policy statement against serological tests.

          Please see later in the article for the Editors' Summary

          Editors' Summary

          Background

          Every year nearly 10 million people develop tuberculosis—a contagious bacterial infection—and about two million people die from the disease. Mycobacterium tuberculosis, the bacterium that causes tuberculosis, is spread in airborne droplets when people with the disease cough or sneeze. It usually infects the lungs (pulmonary tuberculosis) but can also infect the lymph nodes, bones, and other tissues (extrapulmonary tuberculosis). The characteristic symptoms of tuberculosis are a persistent cough, weight loss, and night sweats. Diagnostic tests for the disease include microscopic examination of sputum (mucus brought up from the lungs by coughing) for M. tuberculosis bacilli, chest radiography, mycobacterial culture (in which bacteriologists try to grow M. tuberculosis from sputum or tissue samples), and nucleic acid amplification tests (which detect the bacterium's genome in patient samples). Tuberculosis can usually be cured by taking several powerful drugs daily or several times a week for at least six months.

          Why Was This Study Done?

          Although efforts to control tuberculosis have advanced over the past decade, missed tuberculosis diagnoses and mismanaged tuberculosis continue to fuel the global epidemic. A missed diagnosis may lead to more severe illness and death, especially for people infected with both tuberculosis and HIV. Also, a missed diagnosis means that an untreated individual with pulmonary tuberculosis may remain infectious for longer, continuing to spread tuberculosis within the community Missed diagnoses are a particular problem in resource-limited countries where sputum microscopy and chest radiography often perform poorly and other diagnostic tests are too expensive and complex for routine use. Serological tests, which detect antibodies against M. tuberculosis in the blood (antibodies are proteins made by the immune system in response to infections), might provide a way to diagnose tuberculosis in resource-limited countries. Indeed, many serological tests for tuberculosis diagnosis are on sale in developing countries. However, because of doubts about the accuracy of these commercial tests, they are not recommended for use in routine practice. In this systematic review and meta-analysis, the researchers assess the diagnostic accuracy of commercial serological tests for pulmonary and extrapulmonary tuberculosis. A systematic review uses predefined criteria to identify all the research on a given topic; meta-analysis is a statistical method that combines the results of several studies.

          What Did the Researchers Do and Find?

          The researchers searched the literature for studies that evaluated serological tests for active tuberculosis published between 1990 and 2010. They used data from these studies to calculate each test's sensitivity (the proportion of patients with a positive serological test among patients with tuberculosis confirmed by a reference method; a high sensitivity indicates that the test detects most patients with tuberculosis) and specificity (the proportion of patients with a negative serological result among people without tuberculosis; a high specificity means the test gives few false-positive diagnoses). They also assessed the methodological quality of each study and rated the overall quality of the evidence. The researchers found 67 studies (half from low/middle-income countries) that evaluated serological tests for the diagnosis of pulmonary tuberculosis. The sensitivity of these tests varied between studies, ranging from 0% to 100%; their specificities ranged from 31% to 100%. For the anda-TB IgG test—the only test with sufficient studies for a meta-analysis—the pooled sensitivity from the relevant studies was 76% in smear-positive patients and 59% in smear-negative patients. The pooled specificities were 92% and 91%, respectively. The researchers found 25 studies (40% from low/middle-income countries) that evaluated serological tests for the diagnosis of extrapulmonary tuberculosis. Again, sensitivities and specificities for each test varied greatly between studies, ranging from 0% to 100% and 59% to 100%, respectively. Overall, for both pulmonary and extrapulmonary tuberculosis, the quality of evidence from the studies of the serological tests was graded very low.

          What Do These Findings Mean?

          This systematic review, which updates an analysis published in 2007, indicates that commercial serological tests do not provide an accurate diagnosis of tuberculosis. This finding confirms previous systematic reviews of the evidence, despite a recent expansion in the relevant literature. Moreover, the researchers' analysis indicates that the overall quality of the body of evidence on these tests remains poor. Many of the identified studies used unsatisfactory patient selection methods, for example. Clearly, there is a need for continued and improved research on existing serological tests and for research into new approaches to the serological diagnosis of tuberculosis. For now, though, based on these findings, cost-effectiveness data, and expert opinion, the World Health Organization has issued a recommendation against the use of currently available serological tests for the diagnosis of tuberculosis, while stressing the importance of continued research on these and other tests that could provide quick and accurate diagnosis of TB.

          Additional Information

          Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001062.

          Related collections

          Most cited references 78

          • Record: found
          • Abstract: found
          • Article: not found
          Is Open Access

          Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement

          Introduction Systematic reviews and meta-analyses have become increasingly important in health care. Clinicians read them to keep up to date with their field [1],[2], and they are often used as a starting point for developing clinical practice guidelines. Granting agencies may require a systematic review to ensure there is justification for further research [3], and some health care journals are moving in this direction [4]. As with all research, the value of a systematic review depends on what was done, what was found, and the clarity of reporting. As with other publications, the reporting quality of systematic reviews varies, limiting readers' ability to assess the strengths and weaknesses of those reviews. Several early studies evaluated the quality of review reports. In 1987, Mulrow examined 50 review articles published in four leading medical journals in 1985 and 1986 and found that none met all eight explicit scientific criteria, such as a quality assessment of included studies [5]. In 1987, Sacks and colleagues [6] evaluated the adequacy of reporting of 83 meta-analyses on 23 characteristics in six domains. Reporting was generally poor; between one and 14 characteristics were adequately reported (mean = 7.7; standard deviation = 2.7). A 1996 update of this study found little improvement [7]. In 1996, to address the suboptimal reporting of meta-analyses, an international group developed a guidance called the QUOROM Statement (QUality Of Reporting Of Meta-analyses), which focused on the reporting of meta-analyses of randomized controlled trials [8]. In this article, we summarize a revision of these guidelines, renamed PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses), which have been updated to address several conceptual and practical advances in the science of systematic reviews (Box 1). Box 1: Conceptual Issues in the Evolution from QUOROM to PRISMA Completing a Systematic Review Is an Iterative Process The conduct of a systematic review depends heavily on the scope and quality of included studies: thus systematic reviewers may need to modify their original review protocol during its conduct. Any systematic review reporting guideline should recommend that such changes can be reported and explained without suggesting that they are inappropriate. The PRISMA Statement (Items 5, 11, 16, and 23) acknowledges this iterative process. Aside from Cochrane reviews, all of which should have a protocol, only about 10% of systematic reviewers report working from a protocol [22]. Without a protocol that is publicly accessible, it is difficult to judge between appropriate and inappropriate modifications. Conduct and Reporting Research Are Distinct Concepts This distinction is, however, less straightforward for systematic reviews than for assessments of the reporting of an individual study, because the reporting and conduct of systematic reviews are, by nature, closely intertwined. For example, the failure of a systematic review to report the assessment of the risk of bias in included studies may be seen as a marker of poor conduct, given the importance of this activity in the systematic review process [37]. Study-Level Versus Outcome-Level Assessment of Risk of Bias For studies included in a systematic review, a thorough assessment of the risk of bias requires both a “study-level” assessment (e.g., adequacy of allocation concealment) and, for some features, a newer approach called “outcome-level” assessment. An outcome-level assessment involves evaluating the reliability and validity of the data for each important outcome by determining the methods used to assess them in each individual study [38]. The quality of evidence may differ across outcomes, even within a study, such as between a primary efficacy outcome, which is likely to be very carefully and systematically measured, and the assessment of serious harms [39], which may rely on spontaneous reports by investigators. This information should be reported to allow an explicit assessment of the extent to which an estimate of effect is correct [38]. Importance of Reporting Biases Different types of reporting biases may hamper the conduct and interpretation of systematic reviews. Selective reporting of complete studies (e.g., publication bias) [28] as well as the more recently empirically demonstrated “outcome reporting bias” within individual studies [40],[41] should be considered by authors when conducting a systematic review and reporting its results. Though the implications of these biases on the conduct and reporting of systematic reviews themselves are unclear, some previous research has identified that selective outcome reporting may occur also in the context of systematic reviews [42]. Terminology The terminology used to describe a systematic review and meta-analysis has evolved over time. One reason for changing the name from QUOROM to PRISMA was the desire to encompass both systematic reviews and meta-analyses. We have adopted the definitions used by the Cochrane Collaboration [9]. A systematic review is a review of a clearly formulated question that uses systematic and explicit methods to identify, select, and critically appraise relevant research, and to collect and analyze data from the studies that are included in the review. Statistical methods (meta-analysis) may or may not be used to analyze and summarize the results of the included studies. Meta-analysis refers to the use of statistical techniques in a systematic review to integrate the results of included studies. Developing the PRISMA Statement A three-day meeting was held in Ottawa, Canada, in June 2005 with 29 participants, including review authors, methodologists, clinicians, medical editors, and a consumer. The objective of the Ottawa meeting was to revise and expand the QUOROM checklist and flow diagram, as needed. The executive committee completed the following tasks, prior to the meeting: a systematic review of studies examining the quality of reporting of systematic reviews, and a comprehensive literature search to identify methodological and other articles that might inform the meeting, especially in relation to modifying checklist items. An international survey of review authors, consumers, and groups commissioning or using systematic reviews and meta-analyses was completed, including the International Network of Agencies for Health Technology Assessment (INAHTA) and the Guidelines International Network (GIN). The survey aimed to ascertain views of QUOROM, including the merits of the existing checklist items. The results of these activities were presented during the meeting and are summarized on the PRISMA Web site (http://www.prisma-statement.org/). Only items deemed essential were retained or added to the checklist. Some additional items are nevertheless desirable, and review authors should include these, if relevant [10]. For example, it is useful to indicate whether the systematic review is an update [11] of a previous review, and to describe any changes in procedures from those described in the original protocol. Shortly after the meeting a draft of the PRISMA checklist was circulated to the group, including those invited to the meeting but unable to attend. A disposition file was created containing comments and revisions from each respondent, and the checklist was subsequently revised 11 times. The group approved the checklist, flow diagram, and this summary paper. Although no direct evidence was found to support retaining or adding some items, evidence from other domains was believed to be relevant. For example, Item 5 asks authors to provide registration information about the systematic review, including a registration number, if available. Although systematic review registration is not yet widely available [12],[13], the participating journals of the International Committee of Medical Journal Editors (ICMJE) [14] now require all clinical trials to be registered in an effort to increase transparency and accountability [15]. Those aspects are also likely to benefit systematic reviewers, possibly reducing the risk of an excessive number of reviews addressing the same question [16],[17] and providing greater transparency when updating systematic reviews. The PRISMA Statement The PRISMA Statement consists of a 27-item checklist (Table 1; see also Text S1 for a downloadable Word template for researchers to re-use) and a four-phase flow diagram (Figure 1; see also Figure S1 for a downloadable Word template for researchers to re-use). The aim of the PRISMA Statement is to help authors improve the reporting of systematic reviews and meta-analyses. We have focused on randomized trials, but PRISMA can also be used as a basis for reporting systematic reviews of other types of research, particularly evaluations of interventions. PRISMA may also be useful for critical appraisal of published systematic reviews. However, the PRISMA checklist is not a quality assessment instrument to gauge the quality of a systematic review. 10.1371/journal.pmed.1000097.g001 Figure 1 Flow of information through the different phases of a systematic review. 10.1371/journal.pmed.1000097.t001 Table 1 Checklist of items to include when reporting a systematic review or meta-analysis. Section/Topic # Checklist Item Reported on Page # TITLE Title 1 Identify the report as a systematic review, meta-analysis, or both. ABSTRACT Structured summary 2 Provide a structured summary including, as applicable: background; objectives; data sources; study eligibility criteria, participants, and interventions; study appraisal and synthesis methods; results; limitations; conclusions and implications of key findings; systematic review registration number. INTRODUCTION Rationale 3 Describe the rationale for the review in the context of what is already known. Objectives 4 Provide an explicit statement of questions being addressed with reference to participants, interventions, comparisons, outcomes, and study design (PICOS). METHODS Protocol and registration 5 Indicate if a review protocol exists, if and where it can be accessed (e.g., Web address), and, if available, provide registration information including registration number. Eligibility criteria 6 Specify study characteristics (e.g., PICOS, length of follow-up) and report characteristics (e.g., years considered, language, publication status) used as criteria for eligibility, giving rationale. Information sources 7 Describe all information sources (e.g., databases with dates of coverage, contact with study authors to identify additional studies) in the search and date last searched. Search 8 Present full electronic search strategy for at least one database, including any limits used, such that it could be repeated. Study selection 9 State the process for selecting studies (i.e., screening, eligibility, included in systematic review, and, if applicable, included in the meta-analysis). Data collection process 10 Describe method of data extraction from reports (e.g., piloted forms, independently, in duplicate) and any processes for obtaining and confirming data from investigators. Data items 11 List and define all variables for which data were sought (e.g., PICOS, funding sources) and any assumptions and simplifications made. Risk of bias in individual studies 12 Describe methods used for assessing risk of bias of individual studies (including specification of whether this was done at the study or outcome level), and how this information is to be used in any data synthesis. Summary measures 13 State the principal summary measures (e.g., risk ratio, difference in means). Synthesis of results 14 Describe the methods of handling data and combining results of studies, if done, including measures of consistency (e.g., I2) for each meta-analysis. Risk of bias across studies 15 Specify any assessment of risk of bias that may affect the cumulative evidence (e.g., publication bias, selective reporting within studies). Additional analyses 16 Describe methods of additional analyses (e.g., sensitivity or subgroup analyses, meta-regression), if done, indicating which were pre-specified. RESULTS Study selection 17 Give numbers of studies screened, assessed for eligibility, and included in the review, with reasons for exclusions at each stage, ideally with a flow diagram. Study characteristics 18 For each study, present characteristics for which data were extracted (e.g., study size, PICOS, follow-up period) and provide the citations. Risk of bias within studies 19 Present data on risk of bias of each study and, if available, any outcome-level assessment (see Item 12). Results of individual studies 20 For all outcomes considered (benefits or harms), present, for each study: (a) simple summary data for each intervention group and (b) effect estimates and confidence intervals, ideally with a forest plot. Synthesis of results 21 Present results of each meta-analysis done, including confidence intervals and measures of consistency. Risk of bias across studies 22 Present results of any assessment of risk of bias across studies (see Item 15). Additional analysis 23 Give results of additional analyses, if done (e.g., sensitivity or subgroup analyses, meta-regression [see Item 16]). DISCUSSION Summary of evidence 24 Summarize the main findings including the strength of evidence for each main outcome; consider their relevance to key groups (e.g., health care providers, users, and policy makers). Limitations 25 Discuss limitations at study and outcome level (e.g., risk of bias), and at review level (e.g., incomplete retrieval of identified research, reporting bias). Conclusions 26 Provide a general interpretation of the results in the context of other evidence, and implications for future research. FUNDING Funding 27 Describe sources of funding for the systematic review and other support (e.g., supply of data); role of funders for the systematic review. From QUOROM to PRISMA The new PRISMA checklist differs in several respects from the QUOROM checklist, and the substantive specific changes are highlighted in Table 2. Generally, the PRISMA checklist “decouples” several items present in the QUOROM checklist and, where applicable, several checklist items are linked to improve consistency across the systematic review report. 10.1371/journal.pmed.1000097.t002 Table 2 Substantive specific changes between the QUOROM checklist and the PRISMA checklist (a tick indicates the presence of the topic in QUOROM or PRISMA). Section/Topic Item QUOROM PRISMA Comment Abstract √ √ QUOROM and PRISMA ask authors to report an abstract. However, PRISMA is not specific about format. Introduction Objective √ This new item (4) addresses the explicit question the review addresses using the PICO reporting system (which describes the participants, interventions, comparisons, and outcome(s) of the systematic review), together with the specification of the type of study design (PICOS); the item is linked to Items 6, 11, and 18 of the checklist. Methods Protocol √ This new item (5) asks authors to report whether the review has a protocol and if so how it can be accessed. Methods Search √ √ Although reporting the search is present in both QUOROM and PRISMA checklists, PRISMA asks authors to provide a full description of at least one electronic search strategy (Item 8). Without such information it is impossible to repeat the authors' search. Methods Assessment of risk of bias in included studies √ √ Renamed from “quality assessment” in QUOROM. This item (12) is linked with reporting this information in the results (Item 19). The new concept of “outcome-level” assessment has been introduced. Methods Assessment of risk of bias across studies √ This new item (15) asks authors to describe any assessments of risk of bias in the review, such as selective reporting within the included studies. This item is linked with reporting this information in the results (Item 22). Discussion √ √ Although both QUOROM and PRISMA checklists address the discussion section, PRISMA devotes three items (24–26) to the discussion. In PRISMA the main types of limitations are explicitly stated and their discussion required. Funding √ This new item (27) asks authors to provide information on any sources of funding for the systematic review. The flow diagram has also been modified. Before including studies and providing reasons for excluding others, the review team must first search the literature. This search results in records. Once these records have been screened and eligibility criteria applied, a smaller number of articles will remain. The number of included articles might be smaller (or larger) than the number of studies, because articles may report on multiple studies and results from a particular study may be published in several articles. To capture this information, the PRISMA flow diagram now requests information on these phases of the review process. Endorsement The PRISMA Statement should replace the QUOROM Statement for those journals that have endorsed QUOROM. We hope that other journals will support PRISMA; they can do so by registering on the PRISMA Web site. To underscore to authors, and others, the importance of transparent reporting of systematic reviews, we encourage supporting journals to reference the PRISMA Statement and include the PRISMA Web address in their Instructions to Authors. We also invite editorial organizations to consider endorsing PRISMA and encourage authors to adhere to its principles. The PRISMA Explanation and Elaboration Paper In addition to the PRISMA Statement, a supporting Explanation and Elaboration document has been produced [18] following the style used for other reporting guidelines [19]–[21]. The process of completing this document included developing a large database of exemplars to highlight how best to report each checklist item, and identifying a comprehensive evidence base to support the inclusion of each checklist item. The Explanation and Elaboration document was completed after several face to face meetings and numerous iterations among several meeting participants, after which it was shared with the whole group for additional revisions and final approval. Finally, the group formed a dissemination subcommittee to help disseminate and implement PRISMA. Discussion The quality of reporting of systematic reviews is still not optimal [22]–[27]. In a recent review of 300 systematic reviews, few authors reported assessing possible publication bias [22], even though there is overwhelming evidence both for its existence [28] and its impact on the results of systematic reviews [29]. Even when the possibility of publication bias is assessed, there is no guarantee that systematic reviewers have assessed or interpreted it appropriately [30]. Although the absence of reporting such an assessment does not necessarily indicate that it was not done, reporting an assessment of possible publication bias is likely to be a marker of the thoroughness of the conduct of the systematic review. Several approaches have been developed to conduct systematic reviews on a broader array of questions. For example, systematic reviews are now conducted to investigate cost-effectiveness [31], diagnostic [32] or prognostic questions [33], genetic associations [34], and policy making [35]. The general concepts and topics covered by PRISMA are all relevant to any systematic review, not just those whose objective is to summarize the benefits and harms of a health care intervention. However, some modifications of the checklist items or flow diagram will be necessary in particular circumstances. For example, assessing the risk of bias is a key concept, but the items used to assess this in a diagnostic review are likely to focus on issues such as the spectrum of patients and the verification of disease status, which differ from reviews of interventions. The flow diagram will also need adjustments when reporting individual patient data meta-analysis [36]. We have developed an explanatory document [18] to increase the usefulness of PRISMA. For each checklist item, this document contains an example of good reporting, a rationale for its inclusion, and supporting evidence, including references, whenever possible. We believe this document will also serve as a useful resource for those teaching systematic review methodology. We encourage journals to include reference to the explanatory document in their Instructions to Authors. Like any evidence-based endeavor, PRISMA is a living document. To this end we invite readers to comment on the revised version, particularly the new checklist and flow diagram, through the PRISMA Web site. We will use such information to inform PRISMA's continued development. Supporting Information Figure S1 Flow of information through the different phases of a systematic review (downloadable template document for researchers to re-use). (0.08 MB DOC) Click here for additional data file. Text S1 Checklist of items to include when reporting a systematic review or meta-analysis (downloadable template document for researchers to re-use). (0.04 MB DOC) Click here for additional data file.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            GRADE guidelines: 3. Rating the quality of evidence.

            This article introduces the approach of GRADE to rating quality of evidence. GRADE specifies four categories-high, moderate, low, and very low-that are applied to a body of evidence, not to individual studies. In the context of a systematic review, quality reflects our confidence that the estimates of the effect are correct. In the context of recommendations, quality reflects our confidence that the effect estimates are adequate to support a particular recommendation. Randomized trials begin as high-quality evidence, observational studies as low quality. "Quality" as used in GRADE means more than risk of bias and so may also be compromised by imprecision, inconsistency, indirectness of study results, and publication bias. In addition, several factors can increase our confidence in an estimate of effect. GRADE provides a systematic approach for considering and reporting each of these factors. GRADE separates the process of assessing quality of evidence from the process of making recommendations. Judgments about the strength of a recommendation depend on more than just the quality of evidence. Copyright © 2011 Elsevier Inc. All rights reserved.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              The development of QUADAS: a tool for the quality assessment of studies of diagnostic accuracy included in systematic reviews

              Background In the era of evidence based medicine, with systematic reviews as its cornerstone, adequate quality assessment tools should be available. There is currently a lack of a systematically developed and evaluated tool for the assessment of diagnostic accuracy studies. The aim of this project was to combine empirical evidence and expert opinion in a formal consensus method to develop a tool to be used in systematic reviews to assess the quality of primary studies of diagnostic accuracy. Methods We conducted a Delphi procedure to develop the quality assessment tool by refining an initial list of items. Members of the Delphi panel were experts in the area of diagnostic research. The results of three previously conducted reviews of the diagnostic literature were used to generate a list of potential items for inclusion in the tool and to provide an evidence base upon which to develop the tool. Results A total of nine experts in the field of diagnostics took part in the Delphi procedure. The Delphi procedure consisted of four rounds, after which agreement was reached on the items to be included in the tool which we have called QUADAS. The initial list of 28 items was reduced to fourteen items in the final tool. Items included covered patient spectrum, reference standard, disease progression bias, verification bias, review bias, clinical review bias, incorporation bias, test execution, study withdrawals, and indeterminate results. The QUADAS tool is presented together with guidelines for scoring each of the items included in the tool. Conclusions This project has produced an evidence based quality assessment tool to be used in systematic reviews of diagnostic accuracy studies. Further work to determine the usability and validity of the tool continues.
                Bookmark

                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                PLoS Med
                PLoS
                plosmed
                PLoS Medicine
                Public Library of Science (San Francisco, USA )
                1549-1277
                1549-1676
                August 2011
                August 2011
                9 August 2011
                : 8
                : 8
                Affiliations
                [1 ]Department of Health Services, University of Washington School of Public Health, Seattle, Washington, United States of America
                [2 ]Division of Pulmonary and Critical Care Medicine, San Francisco General Hospital, University of California, San Francisco, California, United States of America
                [3 ]Curry International Tuberculosis Center, University of California, San Francisco, California, United States of America
                [4 ]Department of Epidemiology, Biostatistics, and Occupational Health, McGill University & Montreal, Chest Institute, Montreal, Quebec, Canada
                [5 ]Department of Pathology, New York University Langone Medical Center, New York, New York, United States of America
                [6 ]Department of Microbiology, New York University Langone Medical Center, New York, New York, United States of America
                [7 ]Veterans Affairs Medical Center, New York, New York, United States of America
                [8 ]UNICEF/UNDP/World Bank/WHO Special Programme for Research and Training in Tropical Diseases, World Health Organization, Geneva, Switzerland
                Universidad Peruana Cayetano Heredia, Peru
                Author notes

                Conceived and designed the experiments: KRS AR MP. Performed the experiments: KRS LFF. Analyzed the data: KRS ND IS. Contributed reagents/materials/analysis tools: ND IS. Wrote the paper: KRS MP. ICMJE criteria for authorship read and met: KRS LFF ND IS SL AR PCH MP. Agree with the manuscript's results and conclusions: KRS LFF ND IS SL AR PCH MP. Wrote the first draft of the paper: KRS. Obtained funding: AR.

                Article
                PMEDICINE-D-10-00633
                10.1371/journal.pmed.1001062
                3153457
                21857806
                World Health Organization; licensee Public Library of Science (PLoS). This is an Open Access article in the spirit of the Public Library of Science (PLoS) principles for Open Access http://www.plos.org/oa/, without any waiver of WHO's privileges and immunities under international law, convention, or agreement. This article should not be reproduced for use in association with the promotion of commercial products, services, or any legal entity. There should be no suggestion that WHO endorses any specific organization or products. The use of the WHO logo is not permitted. This notice should be preserved along with the article's original URL.
                Counts
                Pages: 19
                Categories
                Research Article
                Medicine
                Global Health
                Infectious Diseases
                Public Health

                Medicine

                Comments

                Comment on this article