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

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

Health Technology Assessment, No. 26.44

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Abstract

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.

Contents

About the Series

Health Technology Assessment
ISSN (Print): 1366-5278
ISSN (Electronic): 2046-4924

Declared competing interests of authors: Howard Thom reports grants from the National Institute for Health and Care Research (NIHR) [Health Technology Assessment (HTA) 18/134 and NIHR Bristol Biomedical Research Centre], and the Medical Research Council (MRC) (MR/S036709/1); Howard Thom is also a part owner of Clifton Insight and has received consulting fees, paid to Clifton Insight, from Novartis International AG (Basel, Switzerland), F. Hoffmann-La Roche AG (Basel, Switzerland), Pfizer Inc. (New York, NY, USA), Bristol Myers Squibb™ (BMS) (New York, NY, USA), Eisai Co., Ltd (Tokyo, Japan), Argenx (Ghent, Belgium), H. Lundbeck A/S (Copenhagen, Denmark) and Janssen Pharmaceuticals (Beerse, Belgium). He has also received other fees from Clifton Insight. Athena L Sheppard reports grants from the NIHR HTA programme (18/134), payments made to their institution, an employment contract with F. Hoffmann-La Roche (2020), a training grant from the National Centre for Research Methods and a travel grant from the Royal Statistical Society. Edna Keeney reports personal fees from Novartis International AG, F. Hoffmann-La Roche, Pfizer Inc. and BMS. Alastair D Hay reports grants from NIHR (Senior Investigator Award NIHR200151), and membership of the Efficacy and Mechanism Evaluation (EME) Funding Committee (2019 to present) and the National Institute for Health and Care Excellence managing common infections committee (2019 to present). Gerry Robins reports membership of the Trustee Board for Coeliac UK (High Wycombe, UK). Hayley E Jones reports grants from MRC-NIHR (New Investigator Research Grant MR/T044594/1) and consulting fees from Aquarius Population Health (London, UK).

Article history

The research reported in this issue of the journal was funded by the HTA programme as project number NIHR129020. The contractual start date was in January 2020. The draft report began editorial review in November 2021 and was accepted for publication in April 2022. The authors have been wholly responsible for all data collection, analysis and interpretation, and for writing up their work. The HTA editors and publisher have tried to ensure the accuracy of the authors’ report and would like to thank the reviewers for their constructive comments on the draft document. However, they do not accept liability for damages or losses arising from material published in this report.

Last reviewed: November 2021; Accepted: April 2022.

Copyright © 2022 Elwenspoek et al. This work was produced by Elwenspoek et al. under the terms of a commissioning contract issued by the Secretary of State for Health and Social Care. This is an Open Access publication distributed under the terms of the Creative Commons Attribution CC BY 4.0 licence, which permits unrestricted use, distribution, reproduction and adaption in any medium and for any purpose provided that it is properly attributed. See: https://creativecommons.org/licenses/by/4.0/. For attribution the title, original author(s), the publication source – NIHR Journals Library, and the DOI of the publication must be cited.
Bookshelf ID: NBK585899DOI: 10.3310/ZUCE8371

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