Common challenges and suggestions for risk of bias tool development: a systematic review of methodological studies.

OBJECTIVE: To review the findings of studies that have evaluated the design and/or usability of key risk of bias (RoB) tools for the assessment of RoB in primary studies, as categorised by the LATITUDES Network (a searchable library of RoB tools for evidence synthesis): PROBAST, RoB2, ROBINS-I, QUADAS-2, QUADAS-C, QUAPAS, ROBINS-E, and the COSMIN RoB checklist. STUDY DESIGN AND SETTING: Systematic review of methodological studies. We conducted a forward citation search from the primary report of each tool, to identify primary studies aiming to evaluate the design and/or usability of the tool. Two reviewers assessed studies for inclusion. We extracted tool features into Microsoft Word and used NVivo for document analysis, comprising a mix of deductive and inductive approaches. We summarised findings within each tool and explored common findings across tools. RESULTS: We identified 13 tool evaluations meeting our inclusion criteria: PROBAST (3); RoB2 (3); ROBINS-I (4); QUADAS-2 (3). We identified no evaluations for the other tools. Evaluations varied in clinical topic area, methodology, approach to bias assessment and tool user background. Some had limitations affecting generalisability. We identified common findings across tools for 6/14 themes: 1) challenging items (e.g. RoB2/ROBINS-I "deviations from intended interventions" domain), 2) overall RoB judgement (concerns with overall risk calculation in PROBAST/ROBINS-I), 3) tool usability (concerns about complexity), 4) time to complete tool (varying demands on time e.g. depending on number of outcomes assessed), 5) user agreement (varied across tools), and 6) recommendations for future use (e.g. piloting) and development (add intermediate domain answer to QUADAS-2/PROBAST; provide clearer guidance for all tools). Of the other eight themes, seven only had findings for the QUADAS-2 tool, limiting comparison across tools, and one ("re-organisation of questions") had no findings. CONCLUSION: Evaluations of key RoB tools have posited common challenges and recommendations for tool use and development. These findings may be helpful to people using or developing RoB tools. Guidance is necessary to support the design and implementation of future RoB tool evaluations.

Cost-Effectiveness of Routine Monitoring of Long-Term Conditions in Primary Care: Informing Decision Modelling with a Systematic Review in Hypertension, Type 2 Diabetes and Chronic Kidney Disease.

BACKGROUND: Long-term conditions (LTCs) are major public health problems with a considerable health-related and economic burden. Modelling is key in assessing costs and benefits of different disease management strategies, including routine monitoring, in the conditions of hypertension, type 2 diabetes mellitus (T2DM) and chronic kidney disease (CKD) in primary care. OBJECTIVE: This review aimed to identify published model-based cost-effectiveness studies of routine laboratory testing strategies in these LTCs to inform a model evaluating the cost effectiveness of testing strategies in the UK. METHODS: We searched the Medline and Embase databases from inception to July 2023; the National Institute for Health and Care Institute (NICE) website was also searched. Studies were included if they were model-based economic evaluations, evaluated testing strategies, assessed regular testing, and considered adults aged >16 years. Studies identified were summarised by testing strategies, model type, structure, inputs, assessment of uncertainty, and conclusions drawn. RESULTS: Five studies were included in the review, i.e. Markov (n = 3) and microsimulation (n = 2) models. Models were applied within T2DM (n = 2), hypertension (n = 1), T2DM/hypertension (n = 1) and CKD (n = 1). Comorbidity between all three LTCs was modelled to varying extents. All studies used a lifetime horizon, except for a 10-year horizon T2DM model, and all used quality-adjusted life-years as the effectiveness outcome, except a TD2M model that used glycaemic control. No studies explicitly provided a rationale for their selected modelling approach. UK models were available for diabetes and CKD, but these compared only a limited set of routine monitoring tests and frequencies. CONCLUSIONS: There were few studies comparing routine testing strategies in the UK, indicating a need to develop a novel model in all three LTCs. Justification for the modelling technique of the identified studies was lacking. Markov and microsimulation models, with and without comorbidities, were used; however, the findings of this review can provide data sources and inform modelling approaches for evaluating the cost effectiveness of testing strategies in all three LTCs.

Methodological review of NMA bias concepts provides groundwork for the development of a list of concepts for potential inclusion in a new risk of bias tool for network meta-analysis (RoB NMA Tool).

INTRODUCTION: Network meta-analyses (NMAs) have gained popularity and grown in number due to their ability to provide estimates of the comparative effectiveness of multiple treatments for the same condition. The aim of this study is to conduct a methodological review to compile a preliminary list of concepts related to bias in NMAs. METHODS AND ANALYSIS: We included papers that present items related to bias, reporting or methodological quality, papers assessing the quality of NMAs, or method papers. We searched MEDLINE, the Cochrane Library and unpublished literature (up to July 2020). We extracted items related to bias in NMAs. An item was excluded if it related to general systematic review quality or bias and was included in currently available tools such as ROBIS or AMSTAR 2. We reworded items, typically structured as questions, into concepts (i.e. general notions). RESULTS: One hundred eighty-one articles were assessed in full text and 58 were included. Of these articles, 12 were tools, checklists or journal standards; 13 were guidance documents for NMAs; 27 were studies related to bias or NMA methods; and 6 were papers assessing the quality of NMAs. These studies yielded 99 items of which the majority related to general systematic review quality and biases and were therefore excluded. The 22 items we included were reworded into concepts specific to bias in NMAs. CONCLUSIONS: A list of 22 concepts was included. This list is not intended to be used to assess biases in NMAs, but to inform the development of items to be included in our tool.

HIGHLIGHTS: • Our research aimed to develop a preliminary list of concepts related to bias with the goal of developing the first tool for assessing the risk of bias in the results and conclusions of a network meta-analysis (NMA).• We followed the methodology proposed by Whiting (2017) and Sanderson (2007) for creating systematically developed lists of quality items, as a first step in the development of a risk of bias tool for network meta-analysis (RoB NMA Tool).• We included items related to biases in NMAs and excluded items that are equally applicable to all systematic reviews as they are covered by other tools (e.g. ROBIS, AMSTAR 2).• Fifty-seven studies were included generating 99 items, which when screened, yielded 22 included items. These items were then reworded into concepts in preparation for a Delphi process for further vetting by external experts.• A limitation of our study is the challenge in retrieving methods studies as methods collections are not regularly updated.

Clinical effectiveness of point of care tests for diagnosing urinary tract infection: a systematic review.

BACKGROUND: Point of care tests (POCTs) have the potential to improve the urinary tract infection (UTI) diagnostic pathway, as they can provide a diagnosis quickly in near-patient settings, and some also identify causative pathogens/antimicrobial sensitivity. OBJECTIVES: To assess the clinical impact, accuracy, and technical characteristics of POCT for diagnosing UTI. METHODS OF DATA SYNTHESIS: Narrative summary and bivariate random effects meta-analyses to estimate summary sensitivity and specificity. DATA SOURCES: Five electronic databases, two clinical trial registries, study reports and review reference lists, and websites. STUDY ELIGIBILITY CRITERIA: Randomized controlled trials/non-randomized studies and diagnostic test accuracy studies published since 2000. PARTICIPANTS: People with suspected UTI. TESTS: Rapid tests (results <40 minutes): Astrego PA-100 system, Lodestar DX, Uriscreen, UTRiPLEX. Culture tests (results <24 hours): Flexicult Human, ID Flexicult, Diaslide, Dipstreak, Chromostreak, Uricult, Uricult Trio, Uricult Plus. REFERENCE STANDARD: Any. ASSESSMENT OF RISK OF BIAS: Risk of Bias-2, Quality Assessment of Diagnostic Accuracy Studies-2, Quality Assessment of Diagnostic Accuracy Studies-C. RESULTS: Two randomized controlled trials evaluated Flexicult Human (one against standard care; one against ID Flexicult). No difference was reported in antibiotic use concordant with culture results (OR 0.84 95% CI 0.58-1.20) or appropriate antibiotic prescribing (OR 1.44 95% CI 1.03-1.99). Initial antibiotic prescribing was lower with Flexicult than standard care (OR 0.56 95% CI 0.35-0.88). No difference for other measures of antibiotic use, symptom duration, patient enablement, or resource use. Fifteen studies reported accuracy data. Limited data were available, with most POCT evaluated in single studies or not evaluated at all. Uriscreen (four studies), Uricult Trio (three studies), Flexicult Human (four studies), and ID Flexicult (two studies) had modest sensitivity and specificity. POCTs were easier to use and interpret than standard culture. CONCLUSIONS: There is currently insufficient evidence to support the use of POCTs in UTI diagnosis. Due to the rapid development of POCT, this review should be updated regularly.

Liver function tests in patients with hypertension in primary care: a prospective cohort study.

BACKGROUND: Liver function tests (LFTs) are frequently used to monitor patients with hypertension in UK primary care. Evidence is lacking on whether testing improves outcomes. AIM: To estimate the diagnostic accuracy of LFTs in patients with hypertension and determine downstream consequences of testing. DESIGN & SETTING: Prospective study using the Clinical Practice Research Datalink (CPRD). METHOD: In total, 30 000 patients with hypertension who had LFTs in 2015 were randomly selected from CPRD. The diagnostic accuracy measures for eight LFT analytes and an overall LFT panel were calculated against the reference standard of liver disease. Rates of consultations, blood tests, and referrals within 6 months following testing were measured. RESULTS: The 1-year incidence of liver disease in patients with hypertension was 0.5% (95% confidence interval [CI] = 0.4% to 0.6%). Sensitivity and specificity of an LFT panel were modest: 61.3% (95% CI = 53.1% to 69.0%) and 73.8% (95% CI = 73.1% to 74.3%), respectively. The positive predictive value (PPV) of the eight individual LFT analytes were low ranging from 0.2% to 8.9%. Among patients who did not develop liver disease, mean number of consultations, referrals, and tests were higher in the 6 months following false-positives at 10.5, 0.7 and 29.8, respectively, compared with true-negatives: 8.6, 0.6, and 19.8. CONCLUSION: PPVs of LFTs in primary care were low, with high rates of false-positive results and increased rates of subsequent consultations, referrals, and blood testing. Avoiding LFTs for routine monitoring could potentially reduce patients' anxiety, GP workload, and healthcare costs.

Risk of bias assessments in individual participant data meta-analyses of test accuracy and prediction models: a review shows improvements are needed.

OBJECTIVES: Risk of bias assessments are important in meta-analyses of both aggregate and individual participant data (IPD). There is limited evidence on whether and how risk of bias of included studies or datasets in IPD meta-analyses (IPDMAs) is assessed. We review how risk of bias is currently assessed, reported, and incorporated in IPDMAs of test accuracy and clinical prediction model studies and provide recommendations for improvement. STUDY DESIGN AND SETTING: We searched PubMed (January 2018-May 2020) to identify IPDMAs of test accuracy and prediction models, then elicited whether each IPDMA assessed risk of bias of included studies and, if so, how assessments were reported and subsequently incorporated into the IPDMAs. RESULTS: Forty-nine IPDMAs were included. Nineteen of 27 (70%) test accuracy IPDMAs assessed risk of bias, compared to 5 of 22 (23%) prediction model IPDMAs. Seventeen of 19 (89%) test accuracy IPDMAs used Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2), but no tool was used consistently among prediction model IPDMAs. Of IPDMAs assessing risk of bias, 7 (37%) test accuracy IPDMAs and 1 (20%) prediction model IPDMA provided details on the information sources (e.g., the original manuscript, IPD, primary investigators) used to inform judgments, and 4 (21%) test accuracy IPDMAs and 1 (20%) prediction model IPDMA provided information or whether assessments were done before or after obtaining the IPD of the included studies or datasets. Of all included IPDMAs, only seven test accuracy IPDMAs (26%) and one prediction model IPDMA (5%) incorporated risk of bias assessments into their meta-analyses. For future IPDMA projects, we provide guidance on how to adapt tools such as Prediction model Risk Of Bias ASsessment Tool (for prediction models) and QUADAS-2 (for test accuracy) to assess risk of bias of included primary studies and their IPD. CONCLUSION: Risk of bias assessments and their reporting need to be improved in IPDMAs of test accuracy and, especially, prediction model studies. Using recommended tools, both before and after IPD are obtained, will address this.

Identifying the Optimum Strategy for Identifying Adults and Children With Celiac Disease: A Cost-Effectiveness and Value of Information Analysis.

OBJECTIVES: Celiac disease (CD) is thought to affect around 1% of people in the United Kingdom, but only approximately 30% are diagnosed. The aim of this work was to assess the cost-effectiveness of strategies for identifying adults and children with CD in terms of who to test and which tests to use. METHODS: A decision tree and Markov model were used to describe testing strategies and model long-term consequences of CD. The analysis compared a selection of pre-test probabilities of CD above which patients should be screened, as well as the use of different serological tests, with or without genetic testing. Value of information analysis was used to prioritize parameters for future research. RESULTS: Using serological testing alone in adults, immunoglobulin A (IgA) tissue transglutaminase (tTG) at a 1% pre-test probability (equivalent to population screening) was most cost-effective. If combining serological testing with genetic testing, human leukocyte antigen combined with IgA tTG at a 5% pre-test probability was most cost-effective. In children, the most cost-effective strategy was a 10% pre-test probability with human leukocyte antigen plus IgA tTG. Value of information analysis highlighted the probability of late diagnosis of CD and the accuracy of serological tests as important parameters. The analysis also suggested prioritizing research in adult women over adult men or children. CONCLUSIONS: For adults, these cost-effectiveness results suggest UK National Screening Committee Criteria for population-based screening for CD should be explored. Substantial uncertainty in the results indicate a high value in conducting further research.

Exploration of reasons for primary care testing (the Why Test study): a UK-wide audit using the Primary care Academic CollaboraTive.

BACKGROUND: Rates of blood testing have increased over the past two decades. Reasons for testing cannot easily be extracted from electronic health record databases. AIM: To explore who requests blood tests and why, and what the outcomes of testing are in UK primary care. DESIGN AND SETTING: A retrospective audit of electronic health records in general practices in England, Wales, Scotland, and Northern Ireland was undertaken. METHOD: Fifty-seven clinicians from the Primary care Academic CollaboraTive (PACT) each reviewed the electronic health records of 50 patients who had blood tests in April 2021. Anonymised data were extracted including patient characteristics, who requested the tests, reasons for testing, test results, and outcomes of testing. RESULTS: Data were collected from 2572 patients across 57 GP practices. The commonest reasons for testing in primary care were investigation of symptoms (43.2%), monitoring of existing disease (30.1%), monitoring of existing medications (10.1%), and follow up of previous abnormalities (6.8%); patient requested testing was rare in this study (1.5%). Abnormal and borderline results were common, with 26.6% of patients having completely normal test results. Around one-quarter of tests were thought to be partially or fully unnecessary when reviewed retrospectively by a clinical colleague. Overall, 6.2% of tests in primary care led to a new diagnosis or confirmation of a diagnosis. CONCLUSION: The utilisation of a national collaborative model (PACT) has enabled a unique exploration of the rationale and outcomes of blood testing in primary care, highlighting areas for future research and optimisation.

Blood test result communication in primary care: mixed-methods systematic review protocol.

BACKGROUND: After testing, ensuring test results are communicated and actioned is important for patient safety, with failure or delay in diagnosis the most common cause of malpractice claims in primary care worldwide. Identifying interventions to improve test communication from the decision to test through to sharing of results has important implications for patient safety, GP workload, and patient engagement. AIM: To assess the factors around communication of blood test results between primary care providers (for example GPs, nurses, reception staff) and their patients and carers. DESIGN & SETTING: A mixed methods systematic review including primary studies involving communication of blood test results in primary care. METHOD: The review will use a segregated convergent synthesis method. Qualitative information will be synthesised using a meta-aggregative approach, and quantitative data will be meta-analysed or synthesised if pooling of studies is appropriate and data are available. If not, data will be presented in tabular and descriptive summary form. CONCLUSION: This review has the potential to provide conclusions about blood test result communication interventions and factors important to stakeholders, including barriers and facilitators to improved communication.

How to Critically Appraise and Interpret Systematic Reviews and Meta-Analyses of Diagnostic Accuracy: A User Guide.

Systematic reviews of diagnostic accuracy studies can provide the best available evidence to inform decisions regarding the use of a diagnostic test. In this guide, the authors provide a practical approach for clinicians to appraise diagnostic accuracy systematic reviews and apply their results to patient care. The first step is to identify an appropriate systematic review with a research question matching the clinical scenario. The user should evaluate the rigor of the review methods to evaluate its credibility (Did the review use clearly defined eligibility criteria, a comprehensive search strategy, structured data collection, risk of bias and applicability appraisal, and appropriate meta-analysis methods?). If the review is credible, the next step is to decide whether the diagnostic performance is adequate for clinical use (Do sensitivity and specificity estimates exceed the threshold that makes them useful in clinical practice? Are these estimates sufficiently precise? Is variability in the estimates of diagnostic accuracy across studies explained?). Diagnostic accuracy systematic reviews that are judged to be credible and provide diagnostic accuracy estimates with sufficient certainty and relevance are the most useful to inform patient care. This review discusses comparative, noncomparative, and emerging approaches to systematic reviews of diagnostic accuracy using a clinical scenario and examples based on recent publications.

Variation in laboratory testing for patients with long-term conditions: a longitudinal cohort study in UK primary care.

BACKGROUND: Use of laboratory testing has increased in the UK over the past few decades, with considerable geographical variation. AIM: To evaluate what laboratory tests are used to monitor people with hypertension, type 2 (T2) diabetes, or chronic kidney disease (CKD) and assess variation in test use in UK primary care. DESIGN & SETTING: Longitudinal cohort study of people registered with UK general practices between June 2013 and May 2018 and previously diagnosed with hypertension, T2 diabetes, or CKD. METHOD: Clinical Practice Research Datalink (CPRD) primary care data linked to ethnic group and deprivation was used to examine testing rates over time, by GP practice, age, sex, ethnic group, and socioeconomic deprivation, with age-sex standardisation. RESULTS: Nearly 1 million patients were included, and more than 27 million tests. The most ordered tests were for renal function (1463 per 1000 person-years), liver function (1063 per 1000 person-years), and full blood count (FBC; 996 per 1000 person-years). There was evidence of undertesting (compared with current guidelines) for HbA1c and albumin:creatinine ratio (ACR) or microalbumin, and potential overtesting of lipids, FBC, liver function, and thyroid function. Some GP practices had up to 27 times higher testing rates than others (HbA1c testing among patients with CKD). CONCLUSION: Testing rates are no longer increasing, but they are not always within the guidelines for monitoring long-term conditions (LTCs). There was considerable variation by GP practice, indicating uncertainty over the most appropriate testing frequencies for different conditions. Standardising the monitoring of LTCs based on the latest evidence would provide greater consistency of access to monitoring tests.

A declaração PRISMA 2020: diretriz atualizada para relatar revisões sistemáticas*

[RESUMO]. A declaração dos Principais Itens para Relatar Revisões Sistemáticas e Meta-análises (PRISMA), publicada em 2009, foi desenvolvida para ajudar revisores sistemáticos a relatar de forma transparente por que a revisão foi feita, os métodos empregados e o que os autores encontraram. Na última década, os avanços na metodo- logia e terminologia de revisões sistemáticas exigiram a atualização da diretriz. A declaração PRISMA 2020 substitui a declaração de 2009 e inclui novas orientações para relato que refletem os avanços nos métodos para identificar, selecionar, avaliar e sintetizar estudos. A estrutura e apresentação dos itens foram modifi- cadas para facilitar a implementação. Neste artigo, apresentamos a lista de checagem PRISMA 2020 de 27 itens, uma lista de checagem expandida que detalha as recomendações para relato para cada item, a lista de checagem PRISMA 2020 para resumos e os fluxogramas revisados para novas revisões e para atualização de revisões.

[ABSTRACT]. The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement, published in 2009, was designed to help systematic reviewers transparently report why the review was done, what the authors did, and what they found. Over the past decade, advances in systematic review methodology and terminology have necessitated an update to the guideline. The PRISMA 2020 statement replaces the 2009 statement and includes new reporting guidance that reflects advances in methods to identify, select, appraise, and synthesise studies. The structure and presentation of the items have been modified to facilitate imple- mentation. In this article, we present the PRISMA 2020 27-item checklist, an expanded checklist that details reporting recommendations for each item, the PRISMA 2020 abstract checklist, and the revised flow diagrams for original and updated reviews.

[RESUMEN]. La declaración PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses), publicada en 2009, se diseñó para ayudar a los autores de revisiones sistemáticas a documentar de manera transparente el porqué de la revisión, qué hicieron los autores y qué encontraron. Durante la última década, ha habido muchos avances en la metodología y terminología de las revisiones sistemáticas, lo que ha requerido una actualización de esta guía. La declaración PRISMA 2020 sustituye a la declaración de 2009 e incluye una nueva guía de presentación de las publicaciones que refleja los avances en los métodos para identificar, seleccionar, evaluar y sintetizar estudios. La estructura y la presentación de los ítems ha sido modificada para facilitar su implementación. En este artículo, presentamos la lista de verificación PRISMA 2020 con 27 ítems, y una lista de verificación ampliada que detalla las recomendaciones en la publicación de cada ítem, la lista de verificación del resumen estructurado PRISMA 2020 y el diagrama de flujo revisado para revisiones sistemáticas.

Defining the optimum strategy for identifying adults and children with coeliac disease: systematic review and economic modelling.

BACKGROUND: Coeliac disease is an autoimmune disorder triggered by ingesting gluten. It affects approximately 1% of the UK population, but only one in three people is thought to have a diagnosis. Untreated coeliac disease may lead to malnutrition, anaemia, osteoporosis and lymphoma. OBJECTIVES: The objectives were to define at-risk groups and determine the cost-effectiveness of active case-finding strategies in primary care. DESIGN: (1) Systematic review of the accuracy of potential diagnostic indicators for coeliac disease. (2) Routine data analysis to develop prediction models for identification of people who may benefit from testing for coeliac disease. (3) Systematic review of the accuracy of diagnostic tests for coeliac disease. (4) Systematic review of the accuracy of genetic tests for coeliac disease (literature search conducted in April 2021). (5) Online survey to identify diagnostic thresholds for testing, starting treatment and referral for biopsy. (6) Economic modelling to identify the cost-effectiveness of different active case-finding strategies, informed by the findings from previous objectives. DATA SOURCES: For the first systematic review, the following databases were searched from 1997 to April 2021: MEDLINE® (National Library of Medicine, Bethesda, MD, USA), Embase® (Elsevier, Amsterdam, the Netherlands), Cochrane Library, Web of Science™ (Clarivate™, Philadelphia, PA, USA), the World Health Organization International Clinical Trials Registry Platform ( WHO ICTRP ) and the National Institutes of Health Clinical Trials database. For the second systematic review, the following databases were searched from January 1990 to August 2020: MEDLINE, Embase, Cochrane Library, Web of Science, Kleijnen Systematic Reviews ( KSR ) Evidence, WHO ICTRP and the National Institutes of Health Clinical Trials database. For prediction model development, Clinical Practice Research Datalink GOLD, Clinical Practice Research Datalink Aurum and a subcohort of the Avon Longitudinal Study of Parents and Children were used; for estimates for the economic models, Clinical Practice Research Datalink Aurum was used. REVIEW METHODS: For review 1, cohort and case-control studies reporting on a diagnostic indicator in a population with and a population without coeliac disease were eligible. For review 2, diagnostic cohort studies including patients presenting with coeliac disease symptoms who were tested with serological tests for coeliac disease and underwent a duodenal biopsy as reference standard were eligible. In both reviews, risk of bias was assessed using the quality assessment of diagnostic accuracy studies 2 tool. Bivariate random-effects meta-analyses were fitted, in which binomial likelihoods for the numbers of true positives and true negatives were assumed. RESULTS: People with dermatitis herpetiformis, a family history of coeliac disease, migraine, anaemia, type 1 diabetes, osteoporosis or chronic liver disease are 1.5-2 times more likely than the general population to have coeliac disease; individual gastrointestinal symptoms were not useful for identifying coeliac disease. For children, women and men, prediction models included 24, 24 and 21 indicators of coeliac disease, respectively. The models showed good discrimination between patients with and patients without coeliac disease, but performed less well when externally validated. Serological tests were found to have good diagnostic accuracy for coeliac disease. Immunoglobulin A tissue transglutaminase had the highest sensitivity and endomysial antibody the highest specificity. There was little improvement when tests were used in combination. Survey respondents (n = 472) wanted to be 66% certain of the diagnosis from a blood test before starting a gluten-free diet if symptomatic, and 90% certain if asymptomatic. Cost-effectiveness analyses found that, among adults, and using serological testing alone, immunoglobulin A tissue transglutaminase was most cost-effective at a 1% pre-test probability (equivalent to population screening). Strategies using immunoglobulin A endomysial antibody plus human leucocyte antigen or human leucocyte antigen plus immunoglobulin A tissue transglutaminase with any pre-test probability had similar cost-effectiveness results, which were also similar to the cost-effectiveness results of immunoglobulin A tissue transglutaminase at a 1% pre-test probability. The most practical alternative for implementation within the NHS is likely to be a combination of human leucocyte antigen and immunoglobulin A tissue transglutaminase testing among those with a pre-test probability above 1.5%. Among children, the most cost-effective strategy was a 10% pre-test probability with human leucocyte antigen plus immunoglobulin A tissue transglutaminase, but there was uncertainty around the most cost-effective pre-test probability. There was substantial uncertainty in economic model results, which means that there would be great value in conducting further research. LIMITATIONS: The interpretation of meta-analyses was limited by the substantial heterogeneity between the included studies, and most included studies were judged to be at high risk of bias. The main limitations of the prediction models were that we were restricted to diagnostic indicators that were recorded by general practitioners and that, because coeliac disease is underdiagnosed, it is also under-reported in health-care data. The cost-effectiveness model is a simplification of coeliac disease and modelled an average cohort rather than individuals. Evidence was weak on the probability of routine coeliac disease diagnosis, the accuracy of serological and genetic tests and the utility of a gluten-free diet. CONCLUSIONS: Population screening with immunoglobulin A tissue transglutaminase (1% pre-test probability) and of immunoglobulin A endomysial antibody followed by human leucocyte antigen testing or human leucocyte antigen testing followed by immunoglobulin A tissue transglutaminase with any pre-test probability appear to have similar cost-effectiveness results. As decisions to implement population screening cannot be made based on our economic analysis alone, and given the practical challenges of identifying patients with higher pre-test probabilities, we recommend that human leucocyte antigen combined with immunoglobulin A tissue transglutaminase testing should be considered for adults with at least a 1.5% pre-test probability of coeliac disease, equivalent to having at least one predictor. A more targeted strategy of 10% pre-test probability is recommended for children (e.g. children with anaemia). FUTURE WORK: Future work should consider whether or not population-based screening for coeliac disease could meet the UK National Screening Committee criteria and whether or not it necessitates a long-term randomised controlled trial of screening strategies. Large prospective cohort studies in which all participants receive accurate tests for coeliac disease are needed. STUDY REGISTRATION: This study is registered as PROSPERO CRD42019115506 and CRD42020170766. FUNDING: This project was funded by the National Institute for Health and Care Research ( NIHR ) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 26, No. 44. See the NIHR Journals Library website for further project information.

WHAT IS THE PROBLEM?: Around 1 in 100 people in the UK has coeliac disease. It develops when the immune system attacks the lining of the gut after eating gluten. It is thought that only one in three people with coeliac disease is currently diagnosed. Without treatment, people with coeliac disease are at an increased risk of anaemia, osteoporosis and cancer. Treatment is a lifelong gluten-free diet. Diagnosing coeliac disease is difficult. Some people have minimal or non-specific symptoms, such as pain, indigestion or bloating, so knowing who to test is tricky. WHAT DID WE DO?: We wanted to establish who should be tested for coeliac disease, what tests should be used and whether or not invasive testing (a gut biopsy) is necessary for everyone. We looked at existing studies and data from general practices, and conducted an online survey, and brought everything together in an economic (cost) analysis. WHAT DID WE FIND?: Using individual symptoms is not helpful to identify people who may have coeliac disease. People with coeliac disease are more likely to have a combination of symptoms. People with anaemia, type 1 diabetes, osteoporosis, thyroid disorders, immunoglobulin A deficiency, Down syndrome, Turner syndrome or a family history of coeliac disease are more likely to have coeliac disease and should be offered tests. Common blood tests for coeliac disease are very accurate, particularly when used in combination with genetic testing. Blood tests alone can be used for diagnosis for some people. Others will need a biopsy to confirm the diagnosis. Whether or not this is needed depends on their risk of coeliac disease: whether or not they have symptoms and whether or not they have a condition that puts them at higher risk. Shared decision-making is important for individuals considering an invasive test, depending on how certain they want to be about their diagnosis before starting a gluten-free diet.

Reporting guideline for overviews of reviews of healthcare interventions: development of the PRIOR statement.

OBJECTIVE: To develop a reporting guideline for overviews of reviews of healthcare interventions. DESIGN: Development of the preferred reporting items for overviews of reviews (PRIOR) statement. PARTICIPANTS: Core team (seven individuals) led day-to-day operations, and an expert advisory group (three individuals) provided methodological advice. A panel of 100 experts (authors, editors, readers including members of the public or patients) was invited to participate in a modified Delphi exercise. 11 expert panellists (chosen on the basis of expertise, and representing relevant stakeholder groups) were invited to take part in a virtual face-to-face meeting to reach agreement (≥70%) on final checklist items. 21 authors of recently published overviews were invited to pilot test the checklist. SETTING: International consensus. INTERVENTION: Four stage process established by the EQUATOR Network for developing reporting guidelines in health research: project launch (establish a core team and expert advisory group, register intent), evidence reviews (systematic review of published overviews to describe reporting quality, scoping review of methodological guidance and author reported challenges related to undertaking overviews of reviews), modified Delphi exercise (two online Delphi surveys to reach agreement (≥70%) on relevant reporting items followed by a virtual face-to-face meeting), and development of the reporting guideline. RESULTS: From the evidence reviews, we drafted an initial list of 47 potentially relevant reporting items. An international group of 52 experts participated in the first Delphi survey (52% participation rate); agreement was reached for inclusion of 43 (91%) items. 44 experts (85% retention rate) completed the second Delphi survey, which included the four items lacking agreement from the first survey and five new items based on respondent comments. During the second round, agreement was not reached for the inclusion or exclusion of the nine remaining items. 19 individuals (6 core team and 3 expert advisory group members, and 10 expert panellists) attended the virtual face-to-face meeting. Among the nine items discussed, high agreement was reached for the inclusion of three and exclusion of six. Six authors participated in pilot testing, resulting in minor wording changes. The final checklist includes 27 main items (with 19 sub-items) across all stages of an overview of reviews. CONCLUSIONS: PRIOR fills an important gap in reporting guidance for overviews of reviews of healthcare interventions. The checklist, along with rationale and example for each item, provides guidance for authors that will facilitate complete and transparent reporting. This will allow readers to assess the methods used in overviews of reviews of healthcare interventions and understand the trustworthiness and applicability of their findings.

'I guess I'll wait to hear'- communication of blood test results in primary care a qualitative study.

BACKGROUND: Rates of blood testing in primary care are rising. Communicating blood test results generates significant workload for patients, GPs, and practice staff. AIM: To explore GPs' and patients' experience of systems of blood test communication. DESIGN AND SETTING: Qualitative interviews with patients and GPs in UK primary care in both urban and rural practices in the West of England. METHOD: A total of 28 patients and 19 GPs from six practices were recruited, with a range of socioeconomic and demographic characteristics. Patients were interviewed at two time points: a) at or soon after their blood test and b) after they had received their test results. The GPs who requested the tests were also interviewed (they could complete a maximum of two interviews about different patients). Eighty qualitative interviews were undertaken; 54 patient interviews and 26 GP interviews. RESULTS: Methods of test result communication varied between doctors and were based on habits, unwritten heuristics, and personal preferences rather than protocols. Doctors expected patients to know how to access their test results. In contrast, patients were often uncertain and used guesswork to decide when and how to access their tests. Patients and doctors generally assumed that the other party would make contact, with potential implications for patient safety. Text messaging and online methods of communication have benefits, but were perceived by some patients as 'flippant' or 'confusing'. Delays and difficulties obtaining and interpreting test results can lead to anxiety and frustration for patients. CONCLUSION: Current systems of test result communication are complex and confusing, and mostly based on habits and routines rather than clear protocols. This has important implications for patient-centred care and patient safety.

Blood tests in primary care: A qualitative study of communication and decision-making between doctors and patients.

OBJECTIVE: Blood tests are commonly used in primary care as a tool to aid diagnosis, and to offer reassurance and validation for patients. If doctors and patients do not have a shared understanding of the reasons for testing and the meaning of results, these aims may not be fulfilled. Shared decision-making is widely advocated; yet, most research focusses on treatment decisions rather than diagnostic decisions. The aim of this study was to explore communication and decision-making around diagnostic blood tests in primary care. METHODS: Qualitative interviews were undertaken with patients and clinicians in UK primary care. Patients were interviewed at the time of blood testing, with a follow-up interview after they received test results. Interviews with clinicians who requested the tests provided paired data to compare clinicians' and patients' expectations, experiences and understandings of tests. Interviews were analysed thematically using inductive and deductive coding. RESULTS: A total of 80 interviews with 28 patients and 19 doctors were completed. We identified a mismatch in expectations and understanding of tests, which led to downstream consequences including frustration, anxiety and uncertainty for patients. There was no evidence of shared decision-making in consultations preceding the decision to test. Doctors adopted a paternalistic approach, believing that they were protecting patients from anxiety. CONCLUSION: Patients were not able to develop informed preferences and did not perceive that choice is possible in decisions about testing, because they did not have sufficient information and a shared understanding of tests. A lack of shared understanding at the point of decision-making led to downstream consequences when test results did not fulfil patients' expectations. Although shared decision-making is recommended as best practice, it does not reflect the reality of doctors' and patients' accounts of testing; a broader model of shared understanding seems to be more relevant to the complexity of primary care diagnosis. PATIENT OR PUBLIC CONTRIBUTION: A patient and public involvement group comprising five participants with lived experience of blood testing in primary care met regularly during the study. They contributed to the development of the research objectives, planning recruitment methods, reviewing patient information leaflets and topic guides and also contributed to discussion of emerging themes at an early stage in the analysis process.

QUAPAS: An Adaptation of the QUADAS-2 Tool to Assess Prognostic Accuracy Studies.

Whereas diagnostic tests help detect the cause of signs and symptoms, prognostic tests assist in evaluating the probable course of the disease and future outcome. Studies to evaluate prognostic tests are longitudinal, which introduces sources of bias different from those for diagnostic accuracy studies. At present, systematic reviews of prognostic tests often use the QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies 2) tool to assess risk of bias and applicability of included studies because no equivalent instrument exists for prognostic accuracy studies.QUAPAS (Quality Assessment of Prognostic Accuracy Studies) is an adaptation of QUADAS-2 for prognostic accuracy studies. Questions likely to identify bias were evaluated in parallel and collated from QUIPS (Quality in Prognosis Studies) and PROBAST (Prediction Model Risk of Bias Assessment Tool) and paired to the corresponding question (or domain) in QUADAS-2. A steering group conducted and reviewed 3 rounds of modifications before arriving at the final set of domains and signaling questions.QUAPAS follows the same steps as QUADAS-2: Specify the review question, tailor the tool, draw a flow diagram, judge risk of bias, and identify applicability concerns. Risk of bias is judged across the following 5 domains: participants, index test, outcome, flow and timing, and analysis. Signaling questions assist the final judgment for each domain. Applicability concerns are assessed for the first 4 domains.The authors used QUAPAS in parallel with QUADAS-2 and QUIPS in a systematic review of prognostic accuracy studies. QUAPAS improved the assessment of the flow and timing domain and flagged a study at risk of bias in the new analysis domain. Judgment of risk of bias in the analysis domain was challenging because of sparse reporting of statistical methods.

ESPGHAN Position Paper on Management and Follow-up of Children and Adolescents With Celiac Disease.

OBJECTIVES: To gather the current evidence and to offer recommendations for follow-up and management. METHODS: The Special Interest Group on Celiac Diseases of the European Society of Paediatric Gastroenterology Hepatology and Nutrition formulated ten questions considered to be essential for follow-up care. A literature search (January 2010-March 2020) was performed in PubMed or Medline. Relevant publications were identified and potentially eligible studies were assessed. Statements and recommendations were developed and discussed by all coauthors. Recommendations were voted upon: joint agreement was set as at least 85%. RESULTS: Publications (n = 2775) were identified and 164 were included. Using evidence or expert opinion, 37 recommendations were formulated on: The need to perform follow-up, its frequency and what should be assessed, how to assess adherence to the gluten-free diet, when to expect catch-up growth, how to treat anemia, how to approach persistent high serum levels of antibodies against tissue-transglutaminase, the indication to perform biopsies, assessment of quality of life, management of children with unclear diagnosis for which a gluten-challenge is indicated, children with associated type 1 diabetes or IgA deficiency, cases of potential celiac disease, which professionals should perform follow-up, how to improve the communication to patients and their parents/caregivers and transition from pediatric to adult health care. CONCLUSIONS: We offer recommendations to improve follow-up of children and adolescents with celiac disease and highlight gaps that should be investigated to further improve management.

Why Test study protocol: a UK-wide audit using the Primary Care Academic CollaboraTive (PACT) to explore the reasons for primary care testing.

BACKGROUND: The number of blood tests done in primary care has been increasing over the past 20 years. Some estimates suggest that up to one-quarter of these tests may not have been needed. This could lead to a cascade effect of further investigations, appointments, or referrals, as well as anxiety for patients, increased workload, and costs to the health service. To better understand the impact and sequelae of blood tests on patients, it is necessary to know why blood tests are requested and what is done with the results. AIM: To explore who orders blood tests and why, and how test results are actioned in primary care. DESIGN & SETTING: Retrospective audit of electronic health records in general practices across the UK. METHOD: The Primary care Academic CollaboraTive (PACT), a UK-wide network of primary care health professionals, will be utilised to collect data from individual practices. PACT members will be asked to review the electronic health records of 50 patients who had recent blood tests in their practice, and manually extract anonymised data on who requested the test, the indication, the result, and subsequent actions. Data will also be collected from PACT members to assess the feasibility of the collaborative model. CONCLUSION: PACT offers a unique opportunity to extract clinical data which cannot otherwise be obtained. Understanding the indications for tests will help identify priority areas for research to optimise testing and patient safety in primary care.

Development and external validation of a clinical prediction model to aid coeliac disease diagnosis in primary care: An observational study.

Background: Coeliac disease (CD) affects approximately 1% of the population, although only a fraction of patients are diagnosed. Our objective was to develop diagnostic prediction models to help decide who should be offered testing for CD in primary care. Methods: Logistic regression models were developed in Clinical Practice Research Datalink (CPRD) GOLD (between Sep 9, 1987 and Apr 4, 2021, n=107,075) and externally validated in CPRD Aurum (between Jan 1, 1995 and Jan 15, 2021, n=227,915), two UK primary care databases, using (and controlling for) 1:4 nested case-control designs. Candidate predictors included symptoms and chronic conditions identified in current guidelines and using a systematic review of the literature. We used elastic-net regression to further refine the models. Findings: The prediction model included 24, 24, and 21 predictors for children, women, and men, respectively. For children, the strongest predictors were type 1 diabetes, Turner syndrome, IgA deficiency, or first-degree relatives with CD. For women and men, these were anaemia and first-degree relatives. In the development dataset, the models showed good discrimination with a c-statistic of 0·84 (95% CI 0·83-0·84) in children, 0·77 (0·77-0·78) in women, and 0·81 (0·81-0·82) in men. External validation discrimination was lower, potentially because 'first-degree relative' was not recorded in the dataset used for validation. Model calibration was poor, tending to overestimate CD risk in all three groups in both datasets. Interpretation: These prediction models could help identify individuals with an increased risk of CD in relatively low prevalence populations such as primary care. Offering a serological test to these patients could increase case finding for CD. However, this involves offering tests to more people than is currently done. Further work is needed in prospective cohorts to refine and confirm the models and assess clinical and cost effectiveness. Funding: National Institute for Health Research Health Technology Assessment Programme (grant number NIHR129020).