Is the Comparator in Your Diagnostic Cost-Effectiveness Model "Standard of Care"? Recommendations from Literature Reviews and Expert Interviews on How to Identify and Operationalize It.

OBJECTIVES: This research aimed to develop best-practice recommendations for identifying the "standard of care" (SoC) and integrate it when it is the comparator in diagnostic economic models (SoC comparator). METHODS: A multi-methods approach comprising 2 pragmatic literature reviews and 9 expert interviews was used. Experts rated their agreement with draft recommendations based on the authors' analysis of the reviews. These were refined iteratively to produce final recommendations. RESULTS: Fourteen best-practice recommendations are provided. Care pathway mapping (using quantitative, qualitative, or mixed-methods approaches) should be used for identifying the SoC comparator. Guidelines analysis can be integrated with expert opinion to identify pathway variability and discrepancies from clinical practice. For integrating the SoC comparator into the model, recommendations around structure, input sourcing, data aggregation and reporting, input uncertainty, and model variability are presented. For example, modelers should consider that the reference standard is not synonymous with the SoC, and the SoC may not be the only comparator. The comparator limitations should be discussed with clinical experts, but elicitation of its diagnostic accuracy is not recommended. Probabilistic sensitivity analysis is recommended when evaluating the overall input uncertainty, and deterministic sensitivity analysis is useful when there is high model uncertainty or SoC variability. Consensus could not be reached for some topics (eg, the role of real-world data, model averaging, and alternative model structures), but the reported discussions provide points for consideration. CONCLUSIONS: To our knowledge, this is the first guidance to support modelers when identifying and operationalizing the SoC comparator in diagnostic cost-effectiveness models.

Concordance of randomised controlled trials for artificial intelligence interventions with the CONSORT-AI reporting guidelines.

The Consolidated Standards of Reporting Trials extension for Artificial Intelligence interventions (CONSORT-AI) was published in September 2020. Since its publication, several randomised controlled trials (RCTs) of AI interventions have been published but their completeness and transparency of reporting is unknown. This systematic review assesses the completeness of reporting of AI RCTs following publication of CONSORT-AI and provides a comprehensive summary of RCTs published in recent years. 65 RCTs were identified, mostly conducted in China (37%) and USA (18%). Median concordance with CONSORT-AI reporting was 90% (IQR 77-94%), although only 10 RCTs explicitly reported its use. Several items were consistently under-reported, including algorithm version, accessibility of the AI intervention or code, and references to a study protocol. Only 3 of 52 included journals explicitly endorsed or mandated CONSORT-AI. Despite a generally high concordance amongst recent AI RCTs, some AI-specific considerations remain systematically poorly reported. Further encouragement of CONSORT-AI adoption by journals and funders may enable more complete adoption of the full CONSORT-AI guidelines.

Directrices para presentación de informes de ensayos clínicos sobre intervenciones con inteligencia artificial: extensión CONSORT-AI / Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension / Diretrizes para relatórios de ensaios clínicos com intervenções que utilizam inteligência artificial: a extensão CONSORT-AI

resumen está disponible en el texto completo

ABSTRACT The CONSORT 2010 statement provides minimum guidelines for reporting randomized trials. Its widespread use has been instrumental in ensuring transparency in the evaluation of new interventions. More recently, there has been a growing recognition that interventions involving artificial intelligence (AI) need to undergo rigorous, prospective evaluation to demonstrate impact on health outcomes. The CONSORT-AI (Consolidated Standards of Reporting Trials-Artificial Intelligence) extension is a new reporting guideline for clinical trials evaluating interventions with an AI component. It was developed in parallel with its companion statement for clinical trial protocols: SPIRIT-AI (Standard Protocol Items: Recommendations for Interventional Trials-Artificial Intelligence). Both guidelines were developed through a staged consensus process involving literature review and expert consultation to generate 29 candidate items, which were assessed by an international multi-stakeholder group in a two-stage Delphi survey (103 stakeholders), agreed upon in a two-day consensus meeting (31 stakeholders) and refined through a checklist pilot (34 participants). The CONSORT-AI extension includes 14 new items that were considered sufficiently important for AI interventions that they should be routinely reported in addition to the core CONSORT 2010 items. CONSORT-AI recommends that investigators provide clear descriptions of the AI intervention, including instructions and skills required for use, the setting in which the AI intervention is integrated, the handling of inputs and outputs of the AI intervention, the human-AI interaction and provision of an analysis of error cases. CONSORT-AI will help promote transparency and completeness in reporting clinical trials for AI interventions. It will assist editors and peer reviewers, as well as the general readership, to understand, interpret and critically appraise the quality of clinical trial design and risk of bias in the reported outcomes.

RESUMO A declaração CONSORT 2010 apresenta diretrizes mínimas para relatórios de ensaios clínicos randomizados. Seu uso generalizado tem sido fundamental para garantir a transparência na avaliação de novas intervenções. Recentemente, tem-se reconhecido cada vez mais que intervenções que incluem inteligência artificial (IA) precisam ser submetidas a uma avaliação rigorosa e prospectiva para demonstrar seus impactos sobre os resultados de saúde. A extensão CONSORT-AI (Consolidated Standards of Reporting Trials - Artificial Intelligence) é uma nova diretriz para relatórios de ensaios clínicos que avaliam intervenções com um componente de IA. Ela foi desenvolvida em paralelo à sua declaração complementar para protocolos de ensaios clínicos, a SPIRIT-AI (Standard Protocol Items: Recommendations for Interventional Trials - Artificial Intelligence). Ambas as diretrizes foram desenvolvidas por meio de um processo de consenso em etapas que incluiu revisão da literatura e consultas a especialistas para gerar 29 itens candidatos. Foram feitas consultas sobre esses itens a um grupo internacional composto por 103 interessados diretos, que participaram de uma pesquisa Delphi em duas etapas. Chegou-se a um acordo sobre os itens em uma reunião de consenso que incluiu 31 interessados diretos, e os itens foram refinados por meio de uma lista de verificação piloto que envolveu 34 participantes. A extensão CONSORT-AI inclui 14 itens novos que, devido à sua importância para as intervenções de IA, devem ser informados rotineiramente juntamente com os itens básicos da CONSORT 2010. A CONSORT-AI preconiza que os pesquisadores descrevam claramente a intervenção de IA, incluindo instruções e as habilidades necessárias para seu uso, o contexto no qual a intervenção de IA está inserida, considerações sobre o manuseio dos dados de entrada e saída da intervenção de IA, a interação humano-IA e uma análise dos casos de erro. A CONSORT-AI ajudará a promover a transparência e a integralidade nos relatórios de ensaios clínicos com intervenções que utilizam IA. Seu uso ajudará editores e revisores, bem como leitores em geral, a entender, interpretar e avaliar criticamente a qualidade do desenho do ensaio clínico e o risco de viés nos resultados relatados.

Directrices para los protocolos de ensayos clínicos de intervenciones con inteligencia artificial: la extensión SPIRIT-AI / Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension / Diretrizes para protocolos de ensaios clínicos com intervenções que utilizam inteligência artificial: a extensão SPIRIT-AI

resumen está disponible en el texto completo

ABSTRACT The SPIRIT 2013 statement aims to improve the completeness of clinical trial protocol reporting by providing evidence-based recommendations for the minimum set of items to be addressed. This guidance has been instrumental in promoting transparent evaluation of new interventions. More recently, there has been a growing recognition that interventions involving artificial intelligence (AI) need to undergo rigorous, prospective evaluation to demonstrate their impact on health outcomes. The SPIRIT-AI (Standard Protocol Items: Recommendations for Interventional Trials-Artificial Intelligence) extension is a new reporting guideline for clinical trial protocols evaluating interventions with an AI component. It was developed in parallel with its companion statement for trial reports: CONSORT-AI (Consolidated Standards of Reporting Trials-Artificial Intelligence). Both guidelines were developed through a staged consensus process involving literature review and expert consultation to generate 26 candidate items, which were consulted upon by an international multi-stakeholder group in a two-stage Delphi survey (103 stakeholders), agreed upon in a consensus meeting (31 stakeholders) and refined through a checklist pilot (34 participants). The SPIRIT-AI extension includes 15 new items that were considered sufficiently important for clinical trial protocols of AI interventions. These new items should be routinely reported in addition to the core SPIRIT 2013 items. SPIRIT-AI recommends that investigators provide clear descriptions of the AI intervention, including instructions and skills required for use, the setting in which the AI intervention will be integrated, considerations for the handling of input and output data, the human-AI interaction and analysis of error cases. SPIRIT-AI will help promote transparency and completeness for clinical trial protocols for AI interventions. Its use will assist editors and peer reviewers, as well as the general readership, to understand, interpret and critically appraise the design and risk of bias for a planned clinical trial.

RESUMO A declaração SPIRIT 2013 tem como objetivo melhorar a integralidade dos relatórios dos protocolos de ensaios clínicos, fornecendo recomendações baseadas em evidências para o conjunto mínimo de itens que devem ser abordados. Essas orientações têm sido fundamentais para promover uma avaliação transparente de novas intervenções. Recentemente, tem-se reconhecido cada vez mais que intervenções que incluem inteligência artificial (IA) precisam ser submetidas a uma avaliação rigorosa e prospectiva para demonstrar seus impactos sobre os resultados de saúde. A extensão SPIRIT-AI (Standard Protocol Items: Recommendations for Interventional Trials - Artificial Intelligence) é uma nova diretriz de relatório para protocolos de ensaios clínicos que avaliam intervenções com um componente de IA. Essa diretriz foi desenvolvida em paralelo à sua declaração complementar para relatórios de ensaios clínicos, CONSORT-AI (Consolidated Standards of Reporting Trials - Artificial Intelligence). Ambas as diretrizes foram desenvolvidas por meio de um processo de consenso em etapas que incluiu revisão da literatura e consultas a especialistas para gerar 26 itens candidatos. Foram feitas consultas sobre esses itens a um grupo internacional composto por 103 interessados diretos, que participaram de uma pesquisa Delphi em duas etapas. Chegou-se a um acordo sobre os itens em uma reunião de consenso que incluiu 31 interessados diretos, e os itens foram refinados por meio de uma lista de verificação piloto que envolveu 34 participantes. A extensão SPIRIT-AI inclui 15 itens novos que foram considerados suficientemente importantes para os protocolos de ensaios clínicos com intervenções que utilizam IA. Esses itens novos devem constar dos relatórios de rotina, juntamente com os itens básicos da SPIRIT 2013. A SPIRIT-AI preconiza que os pesquisadores descrevam claramente a intervenção de IA, incluindo instruções e as habilidades necessárias para seu uso, o contexto no qual a intervenção de IA será integrada, considerações sobre o manuseio dos dados de entrada e saída, a interação humano-IA e a análise de casos de erro. A SPIRIT-AI ajudará a promover a transparência e a integralidade nos protocolos de ensaios clínicos com intervenções que utilizam IA. Seu uso ajudará editores e revisores, bem como leitores em geral, a entender, interpretar e avaliar criticamente o delineamento e o risco de viés de um futuro estudo clínico.

Health technology assessment of diagnostic tests: a state of the art review of methods guidance from international organizations.

OBJECTIVES: To identify which international health technology assessment (HTA) agencies are undertaking evaluations of medical tests, summarize commonalities and differences in methodological approach, and highlight examples of good practice. METHODS: A methodological review incorporating: systematic identification of HTA guidance documents mentioning evaluation of tests; identification of key contributing organizations and abstraction of approaches to all essential HTA steps; summary of similarities and differences between organizations; and identification of important emergent themes which define the current state of the art and frontiers where further development is needed. RESULTS: Seven key organizations were identified from 216 screened. The main themes were: elucidation of claims of test benefits; attitude to direct and indirect evidence of clinical effectiveness (including evidence linkage); searching; quality assessment; and health economic evaluation. With the exception of dealing with test accuracy data, approaches were largely based on general approaches to HTA with few test-specific modifications. Elucidation of test claims and attitude to direct and indirect evidence are where we identified the biggest dissimilarities in approach. CONCLUSIONS: There is consensus on some aspects of HTA of tests, such as dealing with test accuracy, and examples of good practice which HTA organizations new to test evaluation can emulate. The focus on test accuracy contrasts with universal acknowledgment that it is not a sufficient evidence base for test evaluation. There are frontiers where methodological development is urgently required, notably integrating direct and indirect evidence and standardizing approaches to evidence linkage.

Directrices para los protocolos de ensayos clínicos de intervenciones con inteligencia artificial: la extensión SPIRIT-AI / Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension / Diretrizes para protocolos de ensaios clínicos com intervenções que utilizam inteligência artificial: a extensão SPIRIT-AI

resumen está disponible en el texto completo

ABSTRACT The SPIRIT 2013 statement aims to improve the completeness of clinical trial protocol reporting by providing evidence-based recommendations for the minimum set of items to be addressed. This guidance has been instrumental in promoting transparent evaluation of new interventions. More recently, there has been a growing recognition that interventions involving artificial intelligence (AI) need to undergo rigorous, prospective evaluation to demonstrate their impact on health outcomes. The SPIRIT-AI (Standard Protocol Items: Recommendations for Interventional Trials-Artificial Intelligence) extension is a new reporting guideline for clinical trial protocols evaluating interventions with an AI component. It was developed in parallel with its companion statement for trial reports: CONSORT-AI (Consolidated Standards of Reporting Trials-Artificial Intelligence). Both guidelines were developed through a staged consensus process involving literature review and expert consultation to generate 26 candidate items, which were consulted upon by an international multi-stakeholder group in a two-stage Delphi survey (103 stakeholders), agreed upon in a consensus meeting (31 stakeholders) and refined through a checklist pilot (34 participants). The SPIRIT-AI extension includes 15 new items that were considered sufficiently important for clinical trial protocols of AI interventions. These new items should be routinely reported in addition to the core SPIRIT 2013 items. SPIRIT-AI recommends that investigators provide clear descriptions of the AI intervention, including instructions and skills required for use, the setting in which the AI intervention will be integrated, considerations for the handling of input and output data, the human-AI interaction and analysis of error cases. SPIRIT-AI will help promote transparency and completeness for clinical trial protocols for AI interventions. Its use will assist editors and peer reviewers, as well as the general readership, to understand, interpret and critically appraise the design and risk of bias for a planned clinical trial.

RESUMO A declaração SPIRIT 2013 tem como objetivo melhorar a integralidade dos relatórios dos protocolos de ensaios clínicos, fornecendo recomendações baseadas em evidências para o conjunto mínimo de itens que devem ser abordados. Essas orientações têm sido fundamentais para promover uma avaliação transparente de novas intervenções. Recentemente, tem-se reconhecido cada vez mais que intervenções que incluem inteligência artificial (IA) precisam ser submetidas a uma avaliação rigorosa e prospectiva para demonstrar seus impactos sobre os resultados de saúde. A extensão SPIRIT-AI (Standard Protocol Items: Recommendations for Interventional Trials - Artificial Intelligence) é uma nova diretriz de relatório para protocolos de ensaios clínicos que avaliam intervenções com um componente de IA. Essa diretriz foi desenvolvida em paralelo à sua declaração complementar para relatórios de ensaios clínicos, CONSORT-AI (Consolidated Standards of Reporting Trials - Artificial Intelligence). Ambas as diretrizes foram desenvolvidas por meio de um processo de consenso em etapas que incluiu revisão da literatura e consultas a especialistas para gerar 26 itens candidatos. Foram feitas consultas sobre esses itens a um grupo internacional composto por 103 interessados diretos, que participaram de uma pesquisa Delphi em duas etapas. Chegou-se a um acordo sobre os itens em uma reunião de consenso que incluiu 31 interessados diretos, e os itens foram refinados por meio de uma lista de verificação piloto que envolveu 34 participantes. A extensão SPIRIT-AI inclui 15 itens novos que foram considerados suficientemente importantes para os protocolos de ensaios clínicos com intervenções que utilizam IA. Esses itens novos devem constar dos relatórios de rotina, juntamente com os itens básicos da SPIRIT 2013. A SPIRIT-AI preconiza que os pesquisadores descrevam claramente a intervenção de IA, incluindo instruções e as habilidades necessárias para seu uso, o contexto no qual a intervenção de IA será integrada, considerações sobre o manuseio dos dados de entrada e saída, a interação humano-IA e a análise de casos de erro. A SPIRIT-AI ajudará a promover a transparência e a integralidade nos protocolos de ensaios clínicos com intervenções que utilizam IA. Seu uso ajudará editores e revisores, bem como leitores em geral, a entender, interpretar e avaliar criticamente o delineamento e o risco de viés de um futuro estudo clínico.

Rapid, point-of-care antigen and molecular-based tests for diagnosis of SARS-CoV-2 infection.

BACKGROUND: Accurate rapid diagnostic tests for SARS-CoV-2 infection could contribute to clinical and public health strategies to manage the COVID-19 pandemic. Point-of-care antigen and molecular tests to detect current infection could increase access to testing and early confirmation of cases, and expediate clinical and public health management decisions that may reduce transmission. OBJECTIVES: To assess the diagnostic accuracy of point-of-care antigen and molecular-based tests for diagnosis of SARS-CoV-2 infection. We consider accuracy separately in symptomatic and asymptomatic population groups. SEARCH METHODS: Electronic searches of the Cochrane COVID-19 Study Register and the COVID-19 Living Evidence Database from the University of Bern (which includes daily updates from PubMed and Embase and preprints from medRxiv and bioRxiv) were undertaken on 30 Sept 2020. We checked repositories of COVID-19 publications and included independent evaluations from national reference laboratories, the Foundation for Innovative New Diagnostics and the Diagnostics Global Health website to 16 Nov 2020. We did not apply language restrictions. SELECTION CRITERIA: We included studies of people with either suspected SARS-CoV-2 infection, known SARS-CoV-2 infection or known absence of infection, or those who were being screened for infection. We included test accuracy studies of any design that evaluated commercially produced, rapid antigen or molecular tests suitable for a point-of-care setting (minimal equipment, sample preparation, and biosafety requirements, with results within two hours of sample collection). We included all reference standards that define the presence or absence of SARS-CoV-2 (including reverse transcription polymerase chain reaction (RT-PCR) tests and established diagnostic criteria). DATA COLLECTION AND ANALYSIS: Studies were screened independently in duplicate with disagreements resolved by discussion with a third author. Study characteristics were extracted by one author and checked by a second; extraction of study results and assessments of risk of bias and applicability (made using the QUADAS-2 tool) were undertaken independently in duplicate. We present sensitivity and specificity with 95% confidence intervals (CIs) for each test and pooled data using the bivariate model separately for antigen and molecular-based tests. We tabulated results by test manufacturer and compliance with manufacturer instructions for use and according to symptom status. MAIN RESULTS: Seventy-eight study cohorts were included (described in 64 study reports, including 20 pre-prints), reporting results for 24,087 samples (7,415 with confirmed SARS-CoV-2). Studies were mainly from Europe (n = 39) or North America (n = 20), and evaluated 16 antigen and five molecular assays. We considered risk of bias to be high in 29 (50%) studies because of participant selection; in 66 (85%) because of weaknesses in the reference standard for absence of infection; and in 29 (45%) for participant flow and timing. Studies of antigen tests were of a higher methodological quality compared to studies of molecular tests, particularly regarding the risk of bias for participant selection and the index test. Characteristics of participants in 35 (45%) studies differed from those in whom the test was intended to be used and the delivery of the index test in 39 (50%) studies differed from the way in which the test was intended to be used. Nearly all studies (97%) defined the presence or absence of SARS-CoV-2 based on a single RT-PCR result, and none included participants meeting case definitions for probable COVID-19. Antigen tests Forty-eight studies reported 58 evaluations of antigen tests. Estimates of sensitivity varied considerably between studies. There were differences between symptomatic (72.0%, 95% CI 63.7% to 79.0%; 37 evaluations; 15530 samples, 4410 cases) and asymptomatic participants (58.1%, 95% CI 40.2% to 74.1%; 12 evaluations; 1581 samples, 295 cases). Average sensitivity was higher in the first week after symptom onset (78.3%, 95% CI 71.1% to 84.1%; 26 evaluations; 5769 samples, 2320 cases) than in the second week of symptoms (51.0%, 95% CI 40.8% to 61.0%; 22 evaluations; 935 samples, 692 cases). Sensitivity was high in those with cycle threshold (Ct) values on PCR ≤25 (94.5%, 95% CI 91.0% to 96.7%; 36 evaluations; 2613 cases) compared to those with Ct values >25 (40.7%, 95% CI 31.8% to 50.3%; 36 evaluations; 2632 cases). Sensitivity varied between brands. Using data from instructions for use (IFU) compliant evaluations in symptomatic participants, summary sensitivities ranged from 34.1% (95% CI 29.7% to 38.8%; Coris Bioconcept) to 88.1% (95% CI 84.2% to 91.1%; SD Biosensor STANDARD Q). Average specificities were high in symptomatic and asymptomatic participants, and for most brands (overall summary specificity 99.6%, 95% CI 99.0% to 99.8%). At 5% prevalence using data for the most sensitive assays in symptomatic people (SD Biosensor STANDARD Q and Abbott Panbio), positive predictive values (PPVs) of 84% to 90% mean that between 1 in 10 and 1 in 6 positive results will be a false positive, and between 1 in 4 and 1 in 8 cases will be missed. At 0.5% prevalence applying the same tests in asymptomatic people would result in PPVs of 11% to 28% meaning that between 7 in 10 and 9 in 10 positive results will be false positives, and between 1 in 2 and 1 in 3 cases will be missed. No studies assessed the accuracy of repeated lateral flow testing or self-testing. Rapid molecular assays Thirty studies reported 33 evaluations of five different rapid molecular tests. Sensitivities varied according to test brand. Most of the data relate to the ID NOW and Xpert Xpress assays. Using data from evaluations following the manufacturer's instructions for use, the average sensitivity of ID NOW was 73.0% (95% CI 66.8% to 78.4%) and average specificity 99.7% (95% CI 98.7% to 99.9%; 4 evaluations; 812 samples, 222 cases). For Xpert Xpress, the average sensitivity was 100% (95% CI 88.1% to 100%) and average specificity 97.2% (95% CI 89.4% to 99.3%; 2 evaluations; 100 samples, 29 cases). Insufficient data were available to investigate the effect of symptom status or time after symptom onset. AUTHORS' CONCLUSIONS: Antigen tests vary in sensitivity. In people with signs and symptoms of COVID-19, sensitivities are highest in the first week of illness when viral loads are higher. The assays shown to meet appropriate criteria, such as WHO's priority target product profiles for COVID-19 diagnostics ('acceptable' sensitivity ≥ 80% and specificity ≥ 97%), can be considered as a replacement for laboratory-based RT-PCR when immediate decisions about patient care must be made, or where RT-PCR cannot be delivered in a timely manner. Positive predictive values suggest that confirmatory testing of those with positive results may be considered in low prevalence settings. Due to the variable sensitivity of antigen tests, people who test negative may still be infected. Evidence for testing in asymptomatic cohorts was limited. Test accuracy studies cannot adequately assess the ability of antigen tests to differentiate those who are infectious and require isolation from those who pose no risk, as there is no reference standard for infectiousness. A small number of molecular tests showed high accuracy and may be suitable alternatives to RT-PCR. However, further evaluations of the tests in settings as they are intended to be used are required to fully establish performance in practice. Several important studies in asymptomatic individuals have been reported since the close of our search and will be incorporated at the next update of this review. Comparative studies of antigen tests in their intended use settings and according to test operator (including self-testing) are required.

Rapid, point-of-care antigen and molecular-based tests for diagnosis of SARS-CoV-2 infection.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the resulting COVID-19 pandemic present important diagnostic challenges. Several diagnostic strategies are available to identify or rule out current infection, identify people in need of care escalation, or to test for past infection and immune response. Point-of-care antigen and molecular tests to detect current SARS-CoV-2 infection have the potential to allow earlier detection and isolation of confirmed cases compared to laboratory-based diagnostic methods, with the aim of reducing household and community transmission. OBJECTIVES: To assess the diagnostic accuracy of point-of-care antigen and molecular-based tests to determine if a person presenting in the community or in primary or secondary care has current SARS-CoV-2 infection. SEARCH METHODS: On 25 May 2020 we undertook electronic searches in the Cochrane COVID-19 Study Register and the COVID-19 Living Evidence Database from the University of Bern, which is updated daily with published articles from PubMed and Embase and with preprints from medRxiv and bioRxiv. In addition, we checked repositories of COVID-19 publications. We did not apply any language restrictions. SELECTION CRITERIA: We included studies of people with suspected current SARS-CoV-2 infection, known to have, or not to have SARS-CoV-2 infection, or where tests were used to screen for infection. We included test accuracy studies of any design that evaluated antigen or molecular tests suitable for a point-of-care setting (minimal equipment, sample preparation, and biosafety requirements, with results available within two hours of sample collection). We included all reference standards to define the presence or absence of SARS-CoV-2 (including reverse transcription polymerase chain reaction (RT-PCR) tests and established clinical diagnostic criteria). DATA COLLECTION AND ANALYSIS: Two review authors independently screened studies and resolved any disagreements by discussion with a third review author. One review author independently extracted study characteristics, which were checked by a second review author. Two review authors independently extracted 2x2 contingency table data and assessed risk of bias and applicability of the studies using the QUADAS-2 tool. We present sensitivity and specificity, with 95% confidence intervals (CIs), for each test using paired forest plots. We pooled data using the bivariate hierarchical model separately for antigen and molecular-based tests, with simplifications when few studies were available. We tabulated available data by test manufacturer. MAIN RESULTS: We included 22 publications reporting on a total of 18 study cohorts with 3198 unique samples, of which 1775 had confirmed SARS-CoV-2 infection. Ten studies took place in North America, two in South America, four in Europe, one in China and one was conducted internationally. We identified data for eight commercial tests (four antigen and four molecular) and one in-house antigen test. Five of the studies included were only available as preprints. We did not find any studies at low risk of bias for all quality domains and had concerns about applicability of results across all studies. We judged patient selection to be at high risk of bias in 50% of the studies because of deliberate over-sampling of samples with confirmed COVID-19 infection and unclear in seven out of 18 studies because of poor reporting. Sixteen (89%) studies used only a single, negative RT-PCR to confirm the absence of COVID-19 infection, risking missing infection. There was a lack of information on blinding of index test (n = 11), and around participant exclusions from analyses (n = 10). We did not observe differences in methodological quality between antigen and molecular test evaluations. Antigen tests Sensitivity varied considerably across studies (from 0% to 94%): the average sensitivity was 56.2% (95% CI 29.5 to 79.8%) and average specificity was 99.5% (95% CI 98.1% to 99.9%; based on 8 evaluations in 5 studies on 943 samples). Data for individual antigen tests were limited with no more than two studies for any test. Rapid molecular assays Sensitivity showed less variation compared to antigen tests (from 68% to 100%), average sensitivity was 95.2% (95% CI 86.7% to 98.3%) and specificity 98.9% (95% CI 97.3% to 99.5%) based on 13 evaluations in 11 studies of on 2255 samples. Predicted values based on a hypothetical cohort of 1000 people with suspected COVID-19 infection (with a prevalence of 10%) result in 105 positive test results including 10 false positives (positive predictive value 90%), and 895 negative results including 5 false negatives (negative predictive value 99%). Individual tests We calculated pooled results of individual tests for ID NOW (Abbott Laboratories) (5 evaluations) and Xpert Xpress (Cepheid Inc) (6 evaluations). Summary sensitivity for the Xpert Xpress assay (99.4%, 95% CI 98.0% to 99.8%) was 22.6 (95% CI 18.8 to 26.3) percentage points higher than that of ID NOW (76.8%, (95% CI 72.9% to 80.3%), whilst the specificity of Xpert Xpress (96.8%, 95% CI 90.6% to 99.0%) was marginally lower than ID NOW (99.6%, 95% CI 98.4% to 99.9%; a difference of -2.8% (95% CI -6.4 to 0.8)) AUTHORS' CONCLUSIONS: This review identifies early-stage evaluations of point-of-care tests for detecting SARS-CoV-2 infection, largely based on remnant laboratory samples. The findings currently have limited applicability, as we are uncertain whether tests will perform in the same way in clinical practice, and according to symptoms of COVID-19, duration of symptoms, or in asymptomatic people. Rapid tests have the potential to be used to inform triage of RT-PCR use, allowing earlier detection of those testing positive, but the evidence currently is not strong enough to determine how useful they are in clinical practice. Prospective and comparative evaluations of rapid tests for COVID-19 infection in clinically relevant settings are urgently needed. Studies should recruit consecutive series of eligible participants, including both those presenting for testing due to symptoms and asymptomatic people who may have come into contact with confirmed cases. Studies should clearly describe symptomatic status and document time from symptom onset or time since exposure. Point-of-care tests must be conducted on samples according to manufacturer instructions for use and be conducted at the point of care. Any future research study report should conform to the Standards for Reporting of Diagnostic Accuracy (STARD) guideline.

Antibody tests for identification of current and past infection with SARS-CoV-2.

BACKGROUND: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus and resulting COVID-19 pandemic present important diagnostic challenges. Several diagnostic strategies are available to identify current infection, rule out infection, identify people in need of care escalation, or to test for past infection and immune response. Serology tests to detect the presence of antibodies to SARS-CoV-2 aim to identify previous SARS-CoV-2 infection, and may help to confirm the presence of current infection. OBJECTIVES: To assess the diagnostic accuracy of antibody tests to determine if a person presenting in the community or in primary or secondary care has SARS-CoV-2 infection, or has previously had SARS-CoV-2 infection, and the accuracy of antibody tests for use in seroprevalence surveys. SEARCH METHODS: We undertook electronic searches in the Cochrane COVID-19 Study Register and the COVID-19 Living Evidence Database from the University of Bern, which is updated daily with published articles from PubMed and Embase and with preprints from medRxiv and bioRxiv. In addition, we checked repositories of COVID-19 publications. We did not apply any language restrictions. We conducted searches for this review iteration up to 27 April 2020. SELECTION CRITERIA: We included test accuracy studies of any design that evaluated antibody tests (including enzyme-linked immunosorbent assays, chemiluminescence immunoassays, and lateral flow assays) in people suspected of current or previous SARS-CoV-2 infection, or where tests were used to screen for infection. We also included studies of people either known to have, or not to have SARS-CoV-2 infection. We included all reference standards to define the presence or absence of SARS-CoV-2 (including reverse transcription polymerase chain reaction tests (RT-PCR) and clinical diagnostic criteria). DATA COLLECTION AND ANALYSIS: We assessed possible bias and applicability of the studies using the QUADAS-2 tool. We extracted 2x2 contingency table data and present sensitivity and specificity for each antibody (or combination of antibodies) using paired forest plots. We pooled data using random-effects logistic regression where appropriate, stratifying by time since post-symptom onset. We tabulated available data by test manufacturer. We have presented uncertainty in estimates of sensitivity and specificity using 95% confidence intervals (CIs). MAIN RESULTS: We included 57 publications reporting on a total of 54 study cohorts with 15,976 samples, of which 8526 were from cases of SARS-CoV-2 infection. Studies were conducted in Asia (n = 38), Europe (n = 15), and the USA and China (n = 1). We identified data from 25 commercial tests and numerous in-house assays, a small fraction of the 279 antibody assays listed by the Foundation for Innovative Diagnostics. More than half (n = 28) of the studies included were only available as preprints. We had concerns about risk of bias and applicability. Common issues were use of multi-group designs (n = 29), inclusion of only COVID-19 cases (n = 19), lack of blinding of the index test (n = 49) and reference standard (n = 29), differential verification (n = 22), and the lack of clarity about participant numbers, characteristics and study exclusions (n = 47). Most studies (n = 44) only included people hospitalised due to suspected or confirmed COVID-19 infection. There were no studies exclusively in asymptomatic participants. Two-thirds of the studies (n = 33) defined COVID-19 cases based on RT-PCR results alone, ignoring the potential for false-negative RT-PCR results. We observed evidence of selective publication of study findings through omission of the identity of tests (n = 5). We observed substantial heterogeneity in sensitivities of IgA, IgM and IgG antibodies, or combinations thereof, for results aggregated across different time periods post-symptom onset (range 0% to 100% for all target antibodies). We thus based the main results of the review on the 38 studies that stratified results by time since symptom onset. The numbers of individuals contributing data within each study each week are small and are usually not based on tracking the same groups of patients over time. Pooled results for IgG, IgM, IgA, total antibodies and IgG/IgM all showed low sensitivity during the first week since onset of symptoms (all less than 30.1%), rising in the second week and reaching their highest values in the third week. The combination of IgG/IgM had a sensitivity of 30.1% (95% CI 21.4 to 40.7) for 1 to 7 days, 72.2% (95% CI 63.5 to 79.5) for 8 to 14 days, 91.4% (95% CI 87.0 to 94.4) for 15 to 21 days. Estimates of accuracy beyond three weeks are based on smaller sample sizes and fewer studies. For 21 to 35 days, pooled sensitivities for IgG/IgM were 96.0% (95% CI 90.6 to 98.3). There are insufficient studies to estimate sensitivity of tests beyond 35 days post-symptom onset. Summary specificities (provided in 35 studies) exceeded 98% for all target antibodies with confidence intervals no more than 2 percentage points wide. False-positive results were more common where COVID-19 had been suspected and ruled out, but numbers were small and the difference was within the range expected by chance. Assuming a prevalence of 50%, a value considered possible in healthcare workers who have suffered respiratory symptoms, we would anticipate that 43 (28 to 65) would be missed and 7 (3 to 14) would be falsely positive in 1000 people undergoing IgG/IgM testing at days 15 to 21 post-symptom onset. At a prevalence of 20%, a likely value in surveys in high-risk settings, 17 (11 to 26) would be missed per 1000 people tested and 10 (5 to 22) would be falsely positive. At a lower prevalence of 5%, a likely value in national surveys, 4 (3 to 7) would be missed per 1000 tested, and 12 (6 to 27) would be falsely positive. Analyses showed small differences in sensitivity between assay type, but methodological concerns and sparse data prevent comparisons between test brands. AUTHORS' CONCLUSIONS: The sensitivity of antibody tests is too low in the first week since symptom onset to have a primary role for the diagnosis of COVID-19, but they may still have a role complementing other testing in individuals presenting later, when RT-PCR tests are negative, or are not done. Antibody tests are likely to have a useful role for detecting previous SARS-CoV-2 infection if used 15 or more days after the onset of symptoms. However, the duration of antibody rises is currently unknown, and we found very little data beyond 35 days post-symptom onset. We are therefore uncertain about the utility of these tests for seroprevalence surveys for public health management purposes. Concerns about high risk of bias and applicability make it likely that the accuracy of tests when used in clinical care will be lower than reported in the included studies. Sensitivity has mainly been evaluated in hospitalised patients, so it is unclear whether the tests are able to detect lower antibody levels likely seen with milder and asymptomatic COVID-19 disease. The design, execution and reporting of studies of the accuracy of COVID-19 tests requires considerable improvement. Studies must report data on sensitivity disaggregated by time since onset of symptoms. COVID-19-positive cases who are RT-PCR-negative should be included as well as those confirmed RT-PCR, in accordance with the World Health Organization (WHO) and China National Health Commission of the People's Republic of China (CDC) case definitions. We were only able to obtain data from a small proportion of available tests, and action is needed to ensure that all results of test evaluations are available in the public domain to prevent selective reporting. This is a fast-moving field and we plan ongoing updates of this living systematic review.

Ultrasound, CT, MRI, or PET-CT for staging and re-staging of adults with cutaneous melanoma.

BACKGROUND: Melanoma is one of the most aggressive forms of skin cancer, with the potential to metastasise to other parts of the body via the lymphatic system and the bloodstream. Melanoma accounts for a small percentage of skin cancer cases but is responsible for the majority of skin cancer deaths. Various imaging tests can be used with the aim of detecting metastatic spread of disease following a primary diagnosis of melanoma (primary staging) or on clinical suspicion of disease recurrence (re-staging). Accurate staging is crucial to ensuring that patients are directed to the most appropriate and effective treatment at different points on the clinical pathway. Establishing the comparative accuracy of ultrasound, computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET)-CT imaging for detection of nodal or distant metastases, or both, is critical to understanding if, how, and where on the pathway these tests might be used. OBJECTIVES: Primary objectivesWe estimated accuracy separately according to the point in the clinical pathway at which imaging tests were used. Our objectives were:• to determine the diagnostic accuracy of ultrasound or PET-CT for detection of nodal metastases before sentinel lymph node biopsy in adults with confirmed cutaneous invasive melanoma; and• to determine the diagnostic accuracy of ultrasound, CT, MRI, or PET-CT for whole body imaging in adults with cutaneous invasive melanoma:○ for detection of any metastasis in adults with a primary diagnosis of melanoma (i.e. primary staging at presentation); and○ for detection of any metastasis in adults undergoing staging of recurrence of melanoma (i.e. re-staging prompted by findings on routine follow-up).We undertook separate analyses according to whether accuracy data were reported per patient or per lesion.Secondary objectivesWe sought to determine the diagnostic accuracy of ultrasound, CT, MRI, or PET-CT for whole body imaging (detection of any metastasis) in mixed or not clearly described populations of adults with cutaneous invasive melanoma.For study participants undergoing primary staging or re-staging (for possible recurrence), and for mixed or unclear populations, our objectives were:• to determine the diagnostic accuracy of ultrasound, CT, MRI, or PET-CT for detection of nodal metastases;• to determine the diagnostic accuracy of ultrasound, CT, MRI, or PET-CT for detection of distant metastases; and• to determine the diagnostic accuracy of ultrasound, CT, MRI, or PET-CT for detection of distant metastases according to metastatic site. SEARCH METHODS: We undertook a comprehensive search of the following databases from inception up to August 2016: Cochrane Central Register of Controlled Trials; MEDLINE; Embase; CINAHL; CPCI; Zetoc; Science Citation Index; US National Institutes of Health Ongoing Trials Register; NIHR Clinical Research Network Portfolio Database; and the World Health Organization International Clinical Trials Registry Platform. We studied reference lists as well as published systematic review articles. SELECTION CRITERIA: We included studies of any design that evaluated ultrasound (with or without the use of fine needle aspiration cytology (FNAC)), CT, MRI, or PET-CT for staging of cutaneous melanoma in adults, compared with a reference standard of histological confirmation or imaging with clinical follow-up of at least three months' duration. We excluded studies reporting multiple applications of the same test in more than 10% of study participants. DATA COLLECTION AND ANALYSIS: Two review authors independently extracted all data using a standardised data extraction and quality assessment form (based on the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2)). We estimated accuracy using the bivariate hierarchical method to produce summary sensitivities and specificities with 95% confidence and prediction regions. We undertook analysis of studies allowing direct and indirect comparison between tests. We examined heterogeneity between studies by visually inspecting the forest plots of sensitivity and specificity and summary receiver operating characteristic (ROC) plots. Numbers of identified studies were insufficient to allow formal investigation of potential sources of heterogeneity. MAIN RESULTS: We included a total of 39 publications reporting on 5204 study participants; 34 studies reporting data per patient included 4980 study participants with 1265 cases of metastatic disease, and seven studies reporting data per lesion included 417 study participants with 1846 potentially metastatic lesions, 1061 of which were confirmed metastases. The risk of bias was low or unclear for all domains apart from participant flow. Concerns regarding applicability of the evidence were high or unclear for almost all domains. Participant selection from mixed or not clearly defined populations and poorly described application and interpretation of index tests were particularly problematic.The accuracy of imaging for detection of regional nodal metastases before sentinel lymph node biopsy (SLNB) was evaluated in 18 studies. In 11 studies (2614 participants; 542 cases), the summary sensitivity of ultrasound alone was 35.4% (95% confidence interval (CI) 17.0% to 59.4%) and specificity was 93.9% (95% CI 86.1% to 97.5%). Combining pre-SLNB ultrasound with FNAC revealed summary sensitivity of 18.0% (95% CI 3.58% to 56.5%) and specificity of 99.8% (95% CI 99.1% to 99.9%) (1164 participants; 259 cases). Four studies demonstrated lower sensitivity (10.2%, 95% CI 4.31% to 22.3%) and specificity (96.5%,95% CI 87.1% to 99.1%) for PET-CT before SLNB (170 participants, 49 cases). When these data are translated to a hypothetical cohort of 1000 people eligible for SLNB, 237 of whom have nodal metastases (median prevalence), the combination of ultrasound with FNAC potentially allows 43 people with nodal metastases to be triaged directly to adjuvant therapy rather than having SLNB first, at a cost of two people with false positive results (who are incorrectly managed). Those with a false negative ultrasound will be identified on subsequent SLNB.Limited test accuracy data were available for whole body imaging via PET-CT for primary staging or re-staging for disease recurrence, and none evaluated MRI. Twenty-four studies evaluated whole body imaging. Six of these studies explored primary staging following a confirmed diagnosis of melanoma (492 participants), three evaluated re-staging of disease following some clinical indication of recurrence (589 participants), and 15 included mixed or not clearly described population groups comprising participants at a number of different points on the clinical pathway and at varying stages of disease (1265 participants). Results for whole body imaging could not be translated to a hypothetical cohort of people due to paucity of data.Most of the studies (6/9) of primary disease or re-staging of disease considered PET-CT, two in comparison to CT alone, and three studies examined the use of ultrasound. No eligible evaluations of MRI in these groups were identified. All studies used histological reference standards combined with follow-up, and two included FNAC for some participants. Observed accuracy for detection of any metastases for PET-CT was higher for re-staging of disease (summary sensitivity from two studies: 92.6%, 95% CI 85.3% to 96.4%; specificity: 89.7%, 95% CI 78.8% to 95.3%; 153 participants; 95 cases) compared to primary staging (sensitivities from individual studies ranged from 30% to 47% and specificities from 73% to 88%), and was more sensitive than CT alone in both population groups, but participant numbers were very small.No conclusions can be drawn regarding routine imaging of the brain via MRI or CT. AUTHORS' CONCLUSIONS: Review authors found a disappointing lack of evidence on the accuracy of imaging in people with a diagnosis of melanoma at different points on the clinical pathway. Studies were small and often reported data according to the number of lesions rather than the number of study participants. Imaging with ultrasound combined with FNAC before SLNB may identify around one-fifth of those with nodal disease, but confidence intervals are wide and further work is needed to establish cost-effectiveness. Much of the evidence for whole body imaging for primary staging or re-staging of disease is focused on PET-CT, and comparative data with CT or MRI are lacking. Future studies should go beyond diagnostic accuracy and consider the effects of different imaging tests on disease management. The increasing availability of adjuvant therapies for people with melanoma at high risk of disease spread at presentation will have a considerable impact on imaging services, yet evidence for the relative diagnostic accuracy of available tests is limited.

Dermoscopy, with and without visual inspection, for diagnosing melanoma in adults.

BACKGROUND: Melanoma has one of the fastest rising incidence rates of any cancer. It accounts for a small percentage of skin cancer cases but is responsible for the majority of skin cancer deaths. Although history-taking and visual inspection of a suspicious lesion by a clinician are usually the first in a series of 'tests' to diagnose skin cancer, dermoscopy has become an important tool to assist diagnosis by specialist clinicians and is increasingly used in primary care settings. Dermoscopy is a magnification technique using visible light that allows more detailed examination of the skin compared to examination by the naked eye alone. Establishing the additive value of dermoscopy over and above visual inspection alone across a range of observers and settings is critical to understanding its contribution for the diagnosis of melanoma and to future understanding of the potential role of the growing number of other high-resolution image analysis techniques. OBJECTIVES: To determine the diagnostic accuracy of dermoscopy alone, or when added to visual inspection of a skin lesion, for the detection of cutaneous invasive melanoma and atypical intraepidermal melanocytic variants in adults. We separated studies according to whether the diagnosis was recorded face-to-face (in-person), or based on remote (image-based), assessment. SEARCH METHODS: We undertook a comprehensive search of the following databases from inception up to August 2016: CENTRAL; MEDLINE; Embase; CINAHL; CPCI; Zetoc; Science Citation Index; US National Institutes of Health Ongoing Trials Register; NIHR Clinical Research Network Portfolio Database; and the World Health Organization International Clinical Trials Registry Platform. We studied reference lists and published systematic review articles. SELECTION CRITERIA: Studies of any design that evaluated dermoscopy in adults with lesions suspicious for melanoma, compared with a reference standard of either histological confirmation or clinical follow-up. Data on the accuracy of visual inspection, to allow comparisons of tests, was included only if reported in the included studies of dermoscopy. DATA COLLECTION AND ANALYSIS: Two review authors independently extracted all data using a standardised data extraction and quality assessment form (based on QUADAS-2). We contacted authors of included studies where information related to the target condition or diagnostic threshold were missing. We estimated accuracy using hierarchical summary receiver operating characteristic (SROC),methods. Analysis of studies allowing direct comparison between tests was undertaken. To facilitate interpretation of results, we computed values of sensitivity at the point on the SROC curve with 80% fixed specificity and values of specificity with 80% fixed sensitivity. We investigated the impact of in-person test interpretation; use of a purposely developed algorithm to assist diagnosis; observer expertise; and dermoscopy training. MAIN RESULTS: We included a total of 104 study publications reporting on 103 study cohorts with 42,788 lesions (including 5700 cases), providing 354 datasets for dermoscopy. The risk of bias was mainly low for the index test and reference standard domains and mainly high or unclear for participant selection and participant flow. Concerns regarding the applicability of study findings were largely scored as 'high' concern in three of four domains assessed. Selective participant recruitment, lack of reproducibility of diagnostic thresholds and lack of detail on observer expertise were particularly problematic.The accuracy of dermoscopy for the detection of invasive melanoma or atypical intraepidermal melanocytic variants was reported in 86 datasets; 26 for evaluations conducted in person (dermoscopy added to visual inspection), and 60 for image-based evaluations (diagnosis based on interpretation of dermoscopic images). Analyses of studies by prior testing revealed no obvious effect on accuracy; analyses were hampered by the lack of studies in primary care, lack of relevant information and the restricted inclusion of lesions selected for biopsy or excision. Accuracy was higher for in-person diagnosis compared to image-based evaluations (relative diagnostic odds ratio (RDOR) 4.6, 95% confidence interval (CI) 2.4 to 9.0; P < 0.001).We compared accuracy for (a), in-person evaluations of dermoscopy (26 evaluations; 23,169 lesions and 1664 melanomas),versus visual inspection alone (13 evaluations; 6740 lesions and 459 melanomas), and for (b), image-based evaluations of dermoscopy (60 evaluations; 13,475 lesions and 2851 melanomas),versus image-based visual inspection (11 evaluations; 1740 lesions and 305 melanomas). For both comparisons, meta-analysis found dermoscopy to be more accurate than visual inspection alone, with RDORs of (a), 4.7 (95% CI 3.0 to 7.5; P < 0.001), and (b), 5.6 (95% CI 3.7 to 8.5; P < 0.001). For a), the predicted difference in sensitivity at a fixed specificity of 80% was 16% (95% CI 8% to 23%; 92% for dermoscopy + visual inspection versus 76% for visual inspection), and predicted difference in specificity at a fixed sensitivity of 80% was 20% (95% CI 7% to 33%; 95% for dermoscopy + visual inspection versus 75% for visual inspection). For b) the predicted differences in sensitivity was 34% (95% CI 24% to 46%; 81% for dermoscopy versus 47% for visual inspection), at a fixed specificity of 80%, and predicted difference in specificity was 40% (95% CI 27% to 57%; 82% for dermoscopy versus 42% for visual inspection), at a fixed sensitivity of 80%.Using the median prevalence of disease in each set of studies ((a), 12% for in-person and (b), 24% for image-based), for a hypothetical population of 1000 lesions, an increase in sensitivity of (a), 16% (in-person), and (b), 34% (image-based), from using dermoscopy at a fixed specificity of 80% equates to a reduction in the number of melanomas missed of (a), 19 and (b), 81 with (a), 176 and (b), 152 false positive results. An increase in specificity of (a), 20% (in-person), and (b), 40% (image-based), at a fixed sensitivity of 80% equates to a reduction in the number of unnecessary excisions from using dermoscopy of (a), 176 and (b), 304 with (a), 24 and (b), 48 melanomas missed.The use of a named or published algorithm to assist dermoscopy interpretation (as opposed to no reported algorithm or reported use of pattern analysis), had no significant impact on accuracy either for in-person (RDOR 1.4, 95% CI 0.34 to 5.6; P = 0.17), or image-based (RDOR 1.4, 95% CI 0.60 to 3.3; P = 0.22), evaluations. This result was supported by subgroup analysis according to algorithm used. We observed higher accuracy for observers reported as having high experience and for those classed as 'expert consultants' in comparison to those considered to have less experience in dermoscopy, particularly for image-based evaluations. Evidence for the effect of dermoscopy training on test accuracy was very limited but suggested associated improvements in sensitivity. AUTHORS' CONCLUSIONS: Despite the observed limitations in the evidence base, dermoscopy is a valuable tool to support the visual inspection of a suspicious skin lesion for the detection of melanoma and atypical intraepidermal melanocytic variants, particularly in referred populations and in the hands of experienced users. Data to support its use in primary care are limited, however, it may assist in triaging suspicious lesions for urgent referral when employed by suitably trained clinicians. Formal algorithms may be of most use for dermoscopy training purposes and for less expert observers, however reliable data comparing approaches using dermoscopy in person are lacking.

Visual inspection for diagnosing cutaneous melanoma in adults.

BACKGROUND: Melanoma has one of the fastest rising incidence rates of any cancer. It accounts for a small percentage of skin cancer cases but is responsible for the majority of skin cancer deaths. History-taking and visual inspection of a suspicious lesion by a clinician is usually the first in a series of 'tests' to diagnose skin cancer. Establishing the accuracy of visual inspection alone is critical to understating the potential contribution of additional tests to assist in the diagnosis of melanoma. OBJECTIVES: To determine the diagnostic accuracy of visual inspection for the detection of cutaneous invasive melanoma and atypical intraepidermal melanocytic variants in adults with limited prior testing and in those referred for further evaluation of a suspicious lesion. Studies were separated according to whether the diagnosis was recorded face-to-face (in-person) or based on remote (image-based) assessment. SEARCH METHODS: We undertook a comprehensive search of the following databases from inception up to August 2016: CENTRAL; CINAHL; CPCI; Zetoc; Science Citation Index; US National Institutes of Health Ongoing Trials Register; NIHR Clinical Research Network Portfolio Database; and the World Health Organization International Clinical Trials Registry Platform. We studied reference lists and published systematic review articles. SELECTION CRITERIA: Test accuracy studies of any design that evaluated visual inspection in adults with lesions suspicious for melanoma, compared with a reference standard of either histological confirmation or clinical follow-up. We excluded studies reporting data for 'clinical diagnosis' where dermoscopy may or may not have been used. DATA COLLECTION AND ANALYSIS: Two review authors independently extracted all data using a standardised data extraction and quality assessment form (based on QUADAS-2). We contacted authors of included studies where information related to the target condition or diagnostic threshold were missing. We estimated summary sensitivities and specificities per algorithm and threshold using the bivariate hierarchical model. We investigated the impact of: in-person test interpretation; use of a purposely developed algorithm to assist diagnosis; and observer expertise. MAIN RESULTS: We included 49 publications reporting on a total of 51 study cohorts with 34,351 lesions (including 2499 cases), providing 134 datasets for visual inspection. Across almost all study quality domains, the majority of study reports provided insufficient information to allow us to judge the risk of bias, while in three of four domains that we assessed we scored concerns regarding applicability of study findings as 'high'. Selective participant recruitment, lack of detail regarding the threshold for deciding on a positive test result, and lack of detail on observer expertise were particularly problematic.Attempts to analyse studies by degree of prior testing were hampered by a lack of relevant information and by the restricted inclusion of lesions selected for biopsy or excision. Accuracy was generally much higher for in-person diagnosis compared to image-based evaluations (relative diagnostic odds ratio of 8.54, 95% CI 2.89 to 25.3, P < 0.001). Meta-analysis of in-person evaluations that could be clearly placed on the clinical pathway showed a general trade-off between sensitivity and specificity, with the highest sensitivity (92.4%, 95% CI 26.2% to 99.8%) and lowest specificity (79.7%, 95% CI 73.7% to 84.7%) observed in participants with limited prior testing (n = 3 datasets). Summary sensitivities were lower for those referred for specialist assessment but with much higher specificities (e.g. sensitivity 76.7%, 95% CI 61.7% to 87.1%) and specificity 95.7%, 95% CI 89.7% to 98.3%) for lesions selected for excision, n = 8 datasets). These differences may be related to differences in the spectrum of included lesions, differences in the definition of a positive test result, or to variations in observer expertise. We did not find clear evidence that accuracy is improved by the use of any algorithm to assist diagnosis in all settings. Attempts to examine the effect of observer expertise in melanoma diagnosis were hindered due to poor reporting. AUTHORS' CONCLUSIONS: Visual inspection is a fundamental component of the assessment of a suspicious skin lesion; however, the evidence suggests that melanomas will be missed if visual inspection is used on its own. The evidence to support its accuracy in the range of settings in which it is used is flawed and very poorly reported. Although published algorithms do not appear to improve accuracy, there is insufficient evidence to suggest that the 'no algorithm' approach should be preferred in all settings. Despite the volume of research evaluating visual inspection, further prospective evaluation of the potential added value of using established algorithms according to the prior testing or diagnostic difficulty of lesions may be warranted.

Exfoliative cytology for diagnosing basal cell carcinoma and other skin cancers in adults.

BACKGROUND: Early accurate detection of all skin cancer types is essential to guide appropriate management, reduce morbidity and improve survival. Basal cell carcinoma (BCC) is usually localised to the skin but has potential to infiltrate and damage surrounding tissue, while cutaneous squamous cell carcinoma (cSCC) and melanoma have a much higher potential to metastasise and ultimately lead to death. Exfoliative cytology is a non-invasive test that uses the Tzanck smear technique to identify disease by examining the structure of cells obtained from scraped samples. This simple procedure is a less invasive diagnostic test than a skin biopsy, and for BCC it has the potential to provide an immediate diagnosis that avoids an additional clinic visit to receive skin biopsy results. This may benefit patients scheduled for either Mohs micrographic surgery or non-surgical treatments such as radiotherapy. A cytology scrape can never give the same information as a skin biopsy, however, so it is important to better understand in which skin cancer situations it may be helpful. OBJECTIVES: To determine the diagnostic accuracy of exfoliative cytology for detecting basal cell carcinoma (BCC) in adults, and to compare its accuracy with that of standard diagnostic practice (visual inspection with or without dermoscopy). Secondary objectives were: to determine the diagnostic accuracy of exfoliative cytology for detecting cSCC, invasive melanoma and atypical intraepidermal melanocytic variants, and any other skin cancer; and for each of these secondary conditions to compare the accuracy of exfoliative cytology with visual inspection with or without dermoscopy in direct test comparisons; and to determine the effect of observer experience. SEARCH METHODS: We undertook a comprehensive search of the following databases from inception up to August 2016: Cochrane Central Register of Controlled Trials; MEDLINE; Embase; CINAHL; CPCI; Zetoc; Science Citation Index; US National Institutes of Health Ongoing Trials Register; NIHR Clinical Research Network Portfolio Database; and the World Health Organization International Clinical Trials Registry Platform. We also studied the reference lists of published systematic review articles. SELECTION CRITERIA: Studies evaluating exfoliative cytology in adults with lesions suspicious for BCC, cSCC or melanoma, compared with a reference standard of histological confirmation. DATA COLLECTION AND ANALYSIS: Two review authors independently extracted all data using a standardised data extraction and quality assessment form (based on QUADAS-2). Where possible we estimated summary sensitivities and specificities using the bivariate hierarchical model. MAIN RESULTS: We synthesised the results of nine studies contributing a total of 1655 lesions to our analysis, including 1120 BCCs (14 datasets), 41 cSCCs (amongst 401 lesions in 2 datasets), and 10 melanomas (amongst 200 lesions in 1 dataset). Three of these datasets (one each for BCC, melanoma and any malignant condition) were derived from one study that also performed a direct comparison with dermoscopy. Studies were of moderate to poor quality, providing inadequate descriptions of participant selection, thresholds used to make cytological and histological diagnoses, and blinding. Reporting of participants' prior referral pathways was particularly poor, as were descriptions of the cytodiagnostic criteria used to make diagnoses. No studies evaluated the use of exfoliative cytology as a primary diagnostic test for detecting BCC or other skin cancers in lesions suspicious for skin cancer. Pooled data from seven studies using standard cytomorphological criteria (but various stain methods) to detect BCC in participants with a high clinical suspicion of BCC estimated the sensitivity and specificity of exfoliative cytology as 97.5% (95% CI 94.5% to 98.9%) and 90.1% (95% CI 81.1% to 95.1%). respectively. When applied to a hypothetical population of 1000 clinically suspected BCC lesions with a median observed BCC prevalence of 86%, exfoliative cytology would miss 21 BCCs and would lead to 14 false positive diagnoses of BCC. No false positive cases were histologically confirmed to be melanoma. Insufficient data are available to make summary statements regarding the accuracy of exfoliative cytology to detect melanoma or cSCC, or its accuracy compared to dermoscopy. AUTHORS' CONCLUSIONS: The utility of exfoliative cytology for the primary diagnosis of skin cancer is unknown, as all included studies focused on the use of this technique for confirming strongly suspected clinical diagnoses. For the confirmation of BCC in lesions with a high clinical suspicion, there is evidence of high sensitivity and specificity. Since decisions to treat low-risk BCCs are unlikely in practice to require diagnostic confirmation given that clinical suspicion is already high, exfoliative cytology might be most useful for cases of BCC where the treatments being contemplated require a tissue diagnosis (e.g. radiotherapy). The small number of included studies, poor reporting and varying methodological quality prevent us from drawing strong conclusions to guide clinical practice. Despite insufficient data on the use of cytology for cSCC or melanoma, it is unlikely that cytology would be useful in these scenarios since preservation of the architecture of the whole lesion that would be available from a biopsy provides crucial diagnostic information. Given the paucity of good quality data, appropriately designed prospective comparative studies may be required to evaluate both the diagnostic value of exfoliative cytology by comparison to dermoscopy, and its confirmatory value in adequately reported populations with a high probability of BCC scheduled for further treatment requiring a tissue diagnosis.

Optical coherence tomography for diagnosing skin cancer in adults.

BACKGROUND: Early accurate detection of all skin cancer types is essential to guide appropriate management and to improve morbidity and survival. Melanoma and squamous cell carcinoma (SCC) are high-risk skin cancers, which have the potential to metastasise and ultimately lead to death, whereas basal cell carcinoma (BCC) is usually localised, with potential to infiltrate and damage surrounding tissue. Anxiety around missing early cases needs to be balanced against inappropriate referral and unnecessary excision of benign lesions. Optical coherence tomography (OCT) is a microscopic imaging technique, which magnifies the surface of a skin lesion using near-infrared light. Used in conjunction with clinical or dermoscopic examination of suspected skin cancer, or both, OCT may offer additional diagnostic information compared to other technologies. OBJECTIVES: To determine the diagnostic accuracy of OCT for the detection of cutaneous invasive melanoma and atypical intraepidermal melanocytic variants, basal cell carcinoma (BCC), or cutaneous squamous cell carcinoma (cSCC) in adults. SEARCH METHODS: We undertook a comprehensive search of the following databases from inception up to August 2016: Cochrane Central Register of Controlled Trials; MEDLINE; Embase; CINAHL; CPCI; Zetoc; Science Citation Index; US National Institutes of Health Ongoing Trials Register; NIHR Clinical Research Network Portfolio Database; and the World Health Organization International Clinical Trials Registry Platform. We studied reference lists and published systematic review articles. SELECTION CRITERIA: We included studies of any design evaluating OCT in adults with lesions suspicious for invasive melanoma and atypical intraepidermal melanocytic variants, BCC or cSCC, compared with a reference standard of histological confirmation or clinical follow-up. DATA COLLECTION AND ANALYSIS: Two review authors independently extracted data using a standardised data extraction and quality assessment form (based on QUADAS-2). Our unit of analysis was lesions. Where possible, we estimated summary sensitivities and specificities using the bivariate hierarchical model. MAIN RESULTS: We included five studies with 529 cutaneous lesions (282 malignant lesions) providing nine datasets for OCT, two for visual inspection alone, and two for visual inspection plus dermoscopy. Studies were of moderate to unclear quality, using data-driven thresholds for test positivity and giving poor accounts of reference standard interpretation and blinding. Studies may not have been representative of populations eligible for OCT in practice, for example due to high disease prevalence in study populations, and may not have reflected how OCT is used in practice, for example by using previously acquired OCT images.It was not possible to make summary statements regarding accuracy of detection of melanoma or of cSCC because of the paucity of studies, small sample sizes, and for melanoma differences in the OCT technologies used (high-definition versus conventional resolution OCT), and differences in the degree of testing performed prior to OCT (i.e. visual inspection alone or visual inspection plus dermoscopy).Pooled data from two studies using conventional swept-source OCT alongside visual inspection and dermoscopy for the detection of BCC estimated the sensitivity of OCT as 95% (95% confidence interval (CI) 91% to 97%) and specificity of 77% (95% CI 69% to 83%).When applied to a hypothetical population of 1000 lesions at the mean observed BCC prevalence of 60%, OCT would miss 31 BCCs (91 fewer than would be missed by visual inspection alone and 53 fewer than would be missed by visual inspection plus dermoscopy), and OCT would lead to 93 false-positive results for BCC (a reduction in unnecessary excisions of 159 compared to using visual inspection alone and of 87 compared to visual inspection plus dermoscopy). AUTHORS' CONCLUSIONS: Insufficient data are available on the use of OCT for the detection of melanoma or cSCC. Initial data suggest conventional OCT may have a role for the diagnosis of BCC in clinically challenging lesions, with our meta-analysis showing a higher sensitivity and higher specificity when compared to visual inspection plus dermoscopy. However, the small number of studies and varying methodological quality means implications to guide practice cannot currently be drawn.Appropriately designed prospective comparative studies are required, given the paucity of data comparing OCT with dermoscopy and other similar diagnostic aids such as reflectance confocal microscopy.

Computer-assisted diagnosis techniques (dermoscopy and spectroscopy-based) for diagnosing skin cancer in adults.

BACKGROUND: Early accurate detection of all skin cancer types is essential to guide appropriate management and to improve morbidity and survival. Melanoma and cutaneous squamous cell carcinoma (cSCC) are high-risk skin cancers which have the potential to metastasise and ultimately lead to death, whereas basal cell carcinoma (BCC) is usually localised with potential to infiltrate and damage surrounding tissue. Anxiety around missing early curable cases needs to be balanced against inappropriate referral and unnecessary excision of benign lesions. Computer-assisted diagnosis (CAD) systems use artificial intelligence to analyse lesion data and arrive at a diagnosis of skin cancer. When used in unreferred settings ('primary care'), CAD may assist general practitioners (GPs) or other clinicians to more appropriately triage high-risk lesions to secondary care. Used alongside clinical and dermoscopic suspicion of malignancy, CAD may reduce unnecessary excisions without missing melanoma cases. OBJECTIVES: To determine the accuracy of CAD systems for diagnosing cutaneous invasive melanoma and atypical intraepidermal melanocytic variants, BCC or cSCC in adults, and to compare its accuracy with that of dermoscopy. SEARCH METHODS: We undertook a comprehensive search of the following databases from inception up to August 2016: Cochrane Central Register of Controlled Trials (CENTRAL); MEDLINE; Embase; CINAHL; CPCI; Zetoc; Science Citation Index; US National Institutes of Health Ongoing Trials Register; NIHR Clinical Research Network Portfolio Database; and the World Health Organization International Clinical Trials Registry Platform. We studied reference lists and published systematic review articles. SELECTION CRITERIA: Studies of any design that evaluated CAD alone, or in comparison with dermoscopy, in adults with lesions suspicious for melanoma or BCC or cSCC, and compared with a reference standard of either histological confirmation or clinical follow-up. DATA COLLECTION AND ANALYSIS: Two review authors independently extracted all data using a standardised data extraction and quality assessment form (based on QUADAS-2). We contacted authors of included studies where information related to the target condition or diagnostic threshold were missing. We estimated summary sensitivities and specificities separately by type of CAD system, using the bivariate hierarchical model. We compared CAD with dermoscopy using (a) all available CAD data (indirect comparisons), and (b) studies providing paired data for both tests (direct comparisons). We tested the contribution of human decision-making to the accuracy of CAD diagnoses in a sensitivity analysis by removing studies that gave CAD results to clinicians to guide diagnostic decision-making. MAIN RESULTS: We included 42 studies, 24 evaluating digital dermoscopy-based CAD systems (Derm-CAD) in 23 study cohorts with 9602 lesions (1220 melanomas, at least 83 BCCs, 9 cSCCs), providing 32 datasets for Derm-CAD and seven for dermoscopy. Eighteen studies evaluated spectroscopy-based CAD (Spectro-CAD) in 16 study cohorts with 6336 lesions (934 melanomas, 163 BCC, 49 cSCCs), providing 32 datasets for Spectro-CAD and six for dermoscopy. These consisted of 15 studies using multispectral imaging (MSI), two studies using electrical impedance spectroscopy (EIS) and one study using diffuse-reflectance spectroscopy. Studies were incompletely reported and at unclear to high risk of bias across all domains. Included studies inadequately address the review question, due to an abundance of low-quality studies, poor reporting, and recruitment of highly selected groups of participants.Across all CAD systems, we found considerable variation in the hardware and software technologies used, the types of classification algorithm employed, methods used to train the algorithms, and which lesion morphological features were extracted and analysed across all CAD systems, and even between studies evaluating CAD systems. Meta-analysis found CAD systems had high sensitivity for correct identification of cutaneous invasive melanoma and atypical intraepidermal melanocytic variants in highly selected populations, but with low and very variable specificity, particularly for Spectro-CAD systems. Pooled data from 22 studies estimated the sensitivity of Derm-CAD for the detection of melanoma as 90.1% (95% confidence interval (CI) 84.0% to 94.0%) and specificity as 74.3% (95% CI 63.6% to 82.7%). Pooled data from eight studies estimated the sensitivity of multispectral imaging CAD (MSI-CAD) as 92.9% (95% CI 83.7% to 97.1%) and specificity as 43.6% (95% CI 24.8% to 64.5%). When applied to a hypothetical population of 1000 lesions at the mean observed melanoma prevalence of 20%, Derm-CAD would miss 20 melanomas and would lead to 206 false-positive results for melanoma. MSI-CAD would miss 14 melanomas and would lead to 451 false diagnoses for melanoma. Preliminary findings suggest CAD systems are at least as sensitive as assessment of dermoscopic images for the diagnosis of invasive melanoma and atypical intraepidermal melanocytic variants. We are unable to make summary statements about the use of CAD in unreferred populations, or its accuracy in detecting keratinocyte cancers, or its use in any setting as a diagnostic aid, because of the paucity of studies. AUTHORS' CONCLUSIONS: In highly selected patient populations all CAD types demonstrate high sensitivity, and could prove useful as a back-up for specialist diagnosis to assist in minimising the risk of missing melanomas. However, the evidence base is currently too poor to understand whether CAD system outputs translate to different clinical decision-making in practice. Insufficient data are available on the use of CAD in community settings, or for the detection of keratinocyte cancers. The evidence base for individual systems is too limited to draw conclusions on which might be preferred for practice. Prospective comparative studies are required that evaluate the use of already evaluated CAD systems as diagnostic aids, by comparison to face-to-face dermoscopy, and in participant populations that are representative of those in which the test would be used in practice.

On the importance of considering disease subtypes: Earliest detection of a parosteal osteosarcoma? Differential diagnosis of an osteosarcoma in an Anglo-Saxon female.

A case of potentially dedifferentiated parosteal osteosarcoma was found in the proximal humerus of an adult female buried in the late Anglo-Saxon cemetery of Cherry Hinton, Cambridgeshire, UK. Key features include a large, dense, lobulated mass attached to the medial metaphysis of the proximal humerus by a broad-based attachment, accompanied by cortical destruction and widespread spiculated periosteal reaction. Radiographic images confirm medullary involvement, lack of continuity between the cortex and external mass, a radiolucent cleavage plane and possible radiolucent zones within the bony masses. Differential diagnoses considered include osteochondroma, myositis ossificans, fracture callus, as well as the primary malignancies of osteosarcoma and chondrosarcoma, and their various subtypes. The macroscopic and radiographic analysis of the tumor is described and discussed within clinical and paleopathological contexts. One of only 19 uncontested examples of osteosarcoma from past human populations, most of which remain unconfirmed, this case represents what we believe to be the earliest, and probably singular, bioarcheological example of parosteal osteosarcoma in human history.

Association between use of systematic reviews and national policy recommendations on screening newborn babies for rare diseases: systematic review and meta-analysis.

OBJECTIVE: To understand whether international differences in recommendations of whether to screen for rare diseases using the newborn blood spot test might in part be explained by use of systematic review methods. DESIGN: Systematic review and meta-analysis. DATA SOURCES: Website searches of 26 national screening organisations. ELIGIBILITY CRITERIA FOR STUDY SELECTION: Journal articles, papers, legal documents, presentations, conference abstracts, or reports relating to a national recommendation on whether to screen for any condition using the newborn blood spot test, with no restrictions on date or language. DATA EXTRACTION: Two reviewers independently assessed whether the recommendation for or against screening included systematic reviews, and data on test accuracy, benefits of early detection, and potential harms of overdiagnosis. ANALYSIS: The odds of recommending screening according to the use of systematic review methods was estimated across conditions using meta-analysis. RESULTS: 93 reports were included that assessed 104 conditions across 14 countries, totalling 276 recommendations (units of analysis). Screening was favoured in 159 (58%) recommendations, not favoured in 98 (36%), and not recommended either way in 19 (7%). Only 60 (22%) of the recommendations included a systematic review. Use of a systematic review was associated with a reduced probability of screening being recommended (23/60 (38%) v 136/216 (63%), odds ratio 0.17, 95% confidence interval 0.07 to 0.43). Of the recommendations, evidence for test accuracy, benefits of early detection, and overdiagnosis was not considered in 115 (42%), 83 (30%), and 211 (76%), respectively. CONCLUSIONS: Using systematic review methods is associated with a reduced probability of screening being recommended. Many national policy reviews of screening for rare conditions using the newborn blood spot test do not assess the evidence on the key benefits and harms of screening.

Research waste in diagnostic trials: a methods review evaluating the reporting of test-treatment interventions.

BACKGROUND: The most rigorous method for evaluating the effectiveness of diagnostic tests is through randomised trials that compare test-treatment interventions: complex interventions comprising episodes of testing, decision-making and treatment. The multi-staged nature of these interventions, combined with the need to relay diagnostic decision-making and treatment planning, has led researchers to hypothesise that test-treatment strategies may be very challenging to document. However, no reviews have yet examined the reporting quality of interventions used in test-treatment RCTs. In this study we evaluate the completeness of intervention descriptions in a systematically identified cohort of test-treatment RCTs. METHODS: We ascertained all test-treatment RCTs published 2004-2007, indexed in CENTRAL. Included trials randomized patients to diagnostic tests and measured patient outcomes after treatment. Two raters examined the completeness of test-treatment intervention descriptions in four components: 1) the test, 2) diagnostic decision-making, 3) management decision-making, 4) treatments. RESULTS: One hundred and three trials compared 105 control with 119 experimental interventions, most commonly in cardiovascular medicine (35, 34%), obstetrics and gynecology (17%), gastroenterology (14%) or orthopedics (10%). A broad range of tests were evaluated, including imaging (50, 42%), biochemical assays (21%) and clinical assessment (12%). Only five (5%) trials detailed all four components of experimental and control interventions, none of which also provided a complete care pathway diagram. Experimental arms were missing descriptions of tests, diagnostic-decision making, management planning and treatments (36%, 51%, 55% and 79% of trials respectively); control arms were missing the same details in 61%, 66%, 67% and 84% of trials. CONCLUSION: Reporting of test-treatment interventions is very poor, inadequate for understanding the results of these trials, and for comparing or translating results into clinical practice. Reporting needs to improve, with greater emphasis on describing the decision-making components of care pathways in both pragmatic and explanatory trials. Please see the companion paper to this article: http://bmcmedresmethodol.biomedcentral.com/articles/10.1186/s12874-016-0287-z .

Test-treatment RCTs are susceptible to bias: a review of the methodological quality of randomized trials that evaluate diagnostic tests.

BACKGROUND: There is a growing recognition for the need to expand our evidence base for the clinical effectiveness of diagnostic tests. Many international bodies are calling for diagnostic randomized controlled trials to provide the most rigorous evidence of impact to patient health. Although these so-called test-treatment RCTs are very challenging to undertake due to their methodological complexity, they have not been subjected to a systematic appraisal of their methodological quality. The extent to which these trials may be producing biased results therefore remains unknown. We set out to address this issue by conducting a methodological review of published test-treatment trials to determine how often they implement adequate methods to limit bias and safeguard the validity of results. METHODS: We ascertained all test-treatment RCTs published 2004-2007, indexed in CENTRAL, including RCTs which randomized patients to diagnostic tests and measured patient outcomes after treatment. Tests used for screening, monitoring or prognosis were excluded. We assessed adequacy of sequence generation, allocation concealment and intention-to-treat, appropriateness of primary analyses, blinding and reporting of power calculations, and extracted study characteristics including the primary outcome. RESULTS: One hundred three trials compared 105 control with 119 experimental interventions, and reported 150 primary outcomes. Randomization and allocation concealment were adequate in 57 and 37% of trials. Blinding was uncommon (patients 5%, clinicians 4%, outcome assessors 21%), as was an adequate intention-to-treat analysis (29%). Overall 101 of 103 trials (98%) were at risk of bias, as judged using standard Cochrane criteria. CONCLUSION: Test-treatment trials are particularly susceptible to attrition and inadequate primary analyses, lack of blinding and under-powering. These weaknesses pose much greater methodological and practical challenges to conducting reliable RCT evaluations of test-treatment strategies than standard treatment interventions. We suggest a cautious approach that first examines whether a test-treatment intervention can accommodate the methodological safeguards necessary to minimize bias, and highlight that test-treatment RCTs require different methods to ensure reliability than standard treatment trials. Please see the companion paper to this article: http://bmcmedresmethodol.biomedcentral.com/articles/10.1186/s12874-016-0286-0 .

MANAGEMENT OF ENDOCRINE DISEASE: Imaging for the diagnosis of malignancy in incidentally discovered adrenal masses: a systematic review and meta-analysis.

OBJECTIVE: Adrenal masses are incidentally discovered in 5% of CT scans. In 2013/2014, 81 million CT examinations were undertaken in the USA and 5 million in the UK. However, uncertainty remains around the optimal imaging approach for diagnosing malignancy. We aimed to review the evidence on the accuracy of imaging tests for differentiating malignant from benign adrenal masses. DESIGN: A systematic review and meta-analysis was conducted. METHODS: We searched MEDLINE, EMBASE, Cochrane CENTRAL Register of Controlled Trials, Science Citation Index, Conference Proceedings Citation Index, and ZETOC (January 1990 to August 2015). We included studies evaluating the accuracy of CT, MRI, or (18)F-fluoro-deoxyglucose (FDG)-PET compared with an adequate histological or imaging-based follow-up reference standard. RESULTS: We identified 37 studies suitable for inclusion, after screening 5469 references and 525 full-text articles. Studies evaluated the accuracy of CT (n=16), MRI (n=15), and FDG-PET (n=9) and were generally small and at high or unclear risk of bias. Only 19 studies were eligible for meta-analysis. Limited data suggest that CT density >10HU has high sensitivity for detection of adrenal malignancy in participants with no prior indication for adrenal imaging, that is, masses with ≤10HU are unlikely to be malignant. All other estimates of test performance are based on too small numbers. CONCLUSIONS: Despite their widespread use in routine assessment, there is insufficient evidence for the diagnostic value of individual imaging tests in distinguishing benign from malignant adrenal masses. Future research is urgently needed and should include prospective test validation studies for imaging and novel diagnostic approaches alongside detailed health economics analysis.