You are here

Article Text

Article menu

Download PDFPDF

Diabetes and endocrinology
Protocol
Protocol for the development of a core outcome set for type 1 diabetes risk screening
  1. Celine Chen1,2,
  2. Stephanie Luca1,
  3. Abigail Hansen1,
  4. Diane K. Wherrett3,4,
  5. Holly O. Witteman5,6,
  6. Pranesh Chakraborty7,8,
  7. Audrey L’Espérance9,
  8. Michael G. Wilson10,
  9. Jonathan McGavock11,12,
  10. Sasha Delorme13,
  11. Robin Z Hayeems1,14
  1. 1Child Health Evaluative Sciences, Hospital for Sick Children Research Institute, Toronto, Ontario, Canada
  2. 2University of Toronto Temerty Faculty of Medicine, Toronto, Ontario, Canada
  3. 3The Hospital for Sick Children Division of Endocrinology, Toronto, Ontario, Canada
  4. 4Department of Paediatrics, University of Toronto Temerty Faculty of Medicine, Toronto, Ontario, Canada
  5. 5Université Laval Faculté de Médecine, Québec, Québec, Canada
  6. 6VITAM Centre de Recherche en Santé Durable, Québec, Québec, Canada
  7. 7Department of Paediatrics, Children’s Hospital of Eastern Ontario, Ottawa, Ontario, Canada
  8. 8Division of Metabolics, University of Ottawa Faculty of Medicine, Ottawa, Ontario, Canada
  9. 9École Nationale d’Administration Publique, Québec, Québec, Canada
  10. 10McMaster Health Forum and Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Ontario, Canada
  11. 11Department of Paediatrics and Child Health, University of Manitoba Max Rady College of Medicine, Winnipeg, Manitoba, Canada
  12. 12Diabetes Research Envisioned and Accomplished in Manitoba, University of Manitoba Children’s Hospital Research Institute of Manitoba, Winnipeg, Manitoba, Canada
  13. 13Indigenous Patient Circle, Diabetes Action Canada, Toronto, Ontario, Canada
  14. 14Institute of Health Policy Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
  1. Correspondence to Dr Robin Z Hayeems; robin.hayeems{at}sickkids.ca

Abstract

Introduction Type 1 diabetes is a chronic autoimmune disease that often presents with diabetic ketoacidosis at diagnosis. Since detection of type 1 diabetes risk is possible using genetic risk scores and autoantibody assays, prevention of diabetic ketoacidosis or delayed onset of type 1 diabetes may be possible and may improve outcomes. Several pilot screening programmes for type 1 diabetes risk have emerged worldwide but outcomes measured in these screening programmes are heterogeneous, making it difficult to compare and synthesise findings across studies. To improve the standardisation of outcome reporting and measurement, we aim to develop a patient-oriented core outcome set for studies of type 1 diabetes risk screening.

Methods and analysis This five-step protocol was developed in alignment with the COS-STAndardised Protocol Statement and the Core Outcome Measures in Effectiveness Trials framework. The five steps will include: (1a) conducting a rapid literature review, (1b) gathering input on candidate outcomes from members of the public, (2) combining literature and public input to prepare a preliminary list of outcomes, (3) conducting Delphi surveys with a range of stakeholders to begin to establish consensus on outcomes, (4) holding a final consensus meeting to establish consensus on outcomes and (5) establishing the outcome measurement instruments for the core outcome set.

Ethics and dissemination Ethics approval has been provided by The Hospital for Sick Children Research Ethics Board. The core outcome set will be distributed to researchers and clinicians involved in diabetes screening and clinical care, patient and family networks, research funders, journal editors, public health experts, and policymakers. Disseminated materials will be tailored to the various end users in the form of publication through academic journals, policy briefs, conferences, educational webinars, websites and social media.

  • Paediatric endocrinology
  • GENETICS
  • Mass Screening
  • PREVENTIVE MEDICINE
  • Patient Reported Outcome Measures
  • Delphi Technique
http://creativecommons.org/licenses/by-nc/4.0/

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

https://doi-org.ezproxy.u-pec.fr/10.1136/bmjopen-2025-099537

Statistics from Altmetric.com

    Request Permissions

    If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

    Strengths and limitations of this study

    • Development of the core outcome set protocol follows the guidelines from the Core Outcome Measures in Effectiveness Trials framework.

    • Engagement of people with lived experience in the development of the core outcome set to ensure relevance.

    • Inclusion of grey literature, having two independent reviewers, and vetting by our international advisory panel of experts to mitigate the risk of missing relevant studies.

    • The extensive list of potential outcomes to be included can pose a risk of failing to reach consensus.

    • Multiple Delphi rounds and the consensus meeting provides several opportunities to reach consensus for outcomes and outcome measurement tools.

    Introduction

    Type 1 diabetes (T1D) is a chronic autoimmune disease resulting from the destruction of the pancreatic beta cells responsible for producing insulin. To address this lack of insulin, people living with T1D require life-long insulin replacement therapy. Despite the availability of therapies to manage T1D, many individuals face considerable challenges with daily management and maintaining blood glucose within a safe range. Although the incidence of diabetes-related complications has decreased, excess mortality remains a concern.1 Internationally, it is unfortunately common for both children and adults with T1D to present with diabetic ketoacidosis (DKA) at diagnosis, a life-threatening and costly condition. DKA has been reported in an average of 29.9% of patients at diagnosis across Australia, nine countries in Europe, the UK, the USA, and New Zealand.2 Notably, these numbers climbed to 55% during the COVID-19 pandemic,3 which is similar to the 52.7% DKA prevalence at diagnosis reported in China.4 Many challenges associated with DKA at diagnosis could be prevented if people living with T1D and their families were aware of their disease risk in advance of its onset. Notably, proactive metabolic monitoring of high-risk individuals can reduce the incidence of DKA at diagnosis from 18% to 2% in those without a family history of T1D.5 6 Avoiding DKA not only prevents life-threatening and traumatic healthcare encounters for families but may also decrease T1D-related morbidity, mortality and system costs in the longer term.7

    Risk for T1D is linked to the presence of diabetes-related antibodies (Ab) to glutamic acid decarboxylase, insulin, islet antigen 2 and zinc transporter 8.8 The detection of two or more of these antibodies indicates a high risk for T1D, referred to as Stage 1. Individuals with dysglycaemia alongside two or more Ab are at even greater risk, known as Stage 2. Individuals in Stage 2 have a high likelihood of progressing to clinical or Stage 3 T1D and DKA.9 10 Specifically, 11% of those at high risk will progress to Stage 3 T1D each year.8 The risk of developing T1D also has a significant genetic component.11 Polygenic in origin, genome-wide association studies have identified ~80 loci associated with T1D risk12–14 and heritability estimates are reported to be as high as 50%.15 As genetic risk scores (GRS), which summarise an individual’s risk from multiple disease-associated loci,16 have shown high accuracy in predicting early-onset T1D,17–21 assessing genetic susceptibility is appropriate for T1D screening efforts.22–25

    Since identifying individuals at risk for T1D may provide an avenue for treatment to prevent or delay disease onset, pilot programmes for general population screening are underway in several countries.26 T1D risk is identified through screening for islet Ab and/or using GRS and each programme has established follow-up strategies to assess risk, offer education and monitor for the onset of hyperglycaemia. The objectives of these screening pilots include reducing DKA rates, referring individuals to clinical trials of treatments that aim to prevent or delay the onset of T1D, and identifying those with early hyperglycaemia who may qualify for treatment with approved therapies to delay Stage 3 T1D. In November 2022, teplizumab was the first therapy approved by the US Food and Drug Administration to delay Stage 3 T1D.

    However, T1D screening programmes are controversial because they typically target children, provide crude estimates of risk and do not yet enable disease prevention. As such, ongoing monitoring of the psychological impact of T1D screening is imperative to optimise programme design and mitigate harm. Studies to date have identified cognitive, emotional and behavioural sequelae of screening; primarily on parents, and have predominantly studied mothers. Cognitively, many individuals misunderstand the notion of risk; inaccurate risk perceptions may increase over time and have been associated with early withdrawal from T1D screening studies.27 28 Emotionally, parents may experience anxiety and worry upon learning about a child’s increased T1D risk. While anxiety and worry dissipate with time for most and quality of life among those diagnosed with T1D through screening programmes compared with point of care may be higher, some sociodemographic factors are associated with prolonged emotional vulnerability.29–31 Behaviourally, some families report vigilance with risk monitoring programmes; whereas, others withdraw owing to painful or frightening procedures and/or onerous surveillance schedules.22–25 Moreover, studies to date suggest that engagement in T1D screening and patient-reported sequelae vary by population and country factors,23 calling for the integration and ongoing measurement of patient-reported outcomes in T1D risk screening programmes.

    While an understanding of the patient-reported experience of T1D screening is beginning to emerge, outcomes and outcome measurement instruments are highly variable across studies, precluding comparison and synthesis of results.32 The Core Outcome Measures in Effectiveness Trials (COMET) Initiative was developed to promote the standardised collection of outcome measurements through core outcome sets (COSs), defined as an agreed-upon standard set of outcome measures for a particular disease or condition.33 By measuring the same outcomes, irrespective of the intervention, direct comparisons are possible across a wide range of studies. This allows for a larger number of studies to be directly compared and synthesised in systematic reviews, which are often used to guide policy decision making and clinical practice guidelines.

    As a component of the Canadian Population Screening for Risk of Type 1 Diabetes Research Consortium (CanScreen T1D; www.canscreent1d.ca), this paper describes the protocol for the development of a COS for T1D screening studies that is meaningful to patients and families. While there are relevant COSs registered in the COMET database related to T1D,34–36 there is no COS that is specific to T1D risk screening studies. The existing COSs focus on clinical trials or intervention research,37 38 clinical outcomes for individuals with diabetes,39 and outcomes related to routine diabetes care.34–36 While some outcomes from existing COSs are relevant to screening, existing COSs are not sufficient for evaluating T1D risk screening programmes. As such, the development of a new COS is warranted. Publication of this protocol aims to increase transparency of this COS development process and decrease potential bias.33

    Methods and analysis

    This study was registered with the COMET initiative (registration number 3046, https://www.comet-initiative.org/Studies/Details/3046). We will follow a five-step process to develop the COS that is aligned with the COS-STAndardised Protocol (COS-STAP) Statement40 and the COMET guidelines.33 A multidisciplinary COS Advisory Committee, including people with lived experiences (PWLE), clinical experts and representation from Diabetes Action Canada’s Indigenous Patient Circle, will be formed to provide guidance on each step of this process. Planning was initiated in 2024, and the COS development process will be completed by the end of 2025.

    Step 1a: Rapid literature review

    A rapid literature review41 will be conducted to identify (i) what outcomes were measured and what qualitative dimensions were considered in recent and ongoing T1D risk screening initiatives and (ii) what instruments are being used to measure such outcomes.

    Search strategy: We will work with an experienced information specialist to develop the search strategy following an iterative process in consultation with the Advisory Committee. Example search terms will include T1D, GRS screening, autoantibody screening, children, newborns and patient-reported outcomes. The search will leverage the following databases: Medline, Embase and Web of Science. We will also perform a grey literature search to identify additional articles reporting or discussing outcomes for T1D population screening programmes. We will limit the scope of the grey literature search to the websites of existing T1D population screening programmes, guided by the status report by Sims et al.26 If we are unable to locate relevant outcomes measured on the programme websites, we will consult with the study leads, where feasible. Additionally, we will review the T1D-related COSs registered in the COMET database. In keeping with the rapid nature of this review, we will restrict our search to publications in English from 2010 and onwards to identify the most current outcomes. 2010 is selected as the starting point for our search as the first T1D population screening initiative25 launched at this time.

    Study screening and selection: Articles identified through the searches will be reviewed, removing duplicates in Covidence.42 Covidence is a web-based collaboration software platform that streamlines the production of systematic and other literature reviews.42 In screening phase one, titles and abstracts will be screened by two independent reviewers. Based on the review of a preliminary list of relevant papers, the following eligibility criteria have been created using the PICOS (population, intervention, comparator, outcome, study design) framework.43 Preliminary inclusion criteria are: (P) articles focused on populations of individuals at risk for T1D and/or (I) articles for which screening for T1D is the intervention. No criteria will be specified for comparators (C). Relevant outcomes (O) include articles reporting patient-reported outcome measures (PROMs) in screening studies for T1D, articles related to T1D risk screening acceptability, feasibility, uptake, and adherence, or provider outcome measures related to T1D risk screening. Articles will be primary, peer-reviewed, and reporting on five or more participants, or will include screening guidelines or recommendations for outcomes to be measured in future studies. Articles may also describe COSs related to T1D reported in the COMET database. Articles will be excluded if they focus exclusively on populations of individuals at risk for or diagnosed with type 2 diabetes. Studies that only focus on clinical or management-related outcomes for T1D or on genetic, molecular, cellular markers, or characterisation of T1D will be excluded. Case studies, articles with abstract only, commentaries, evidence reviews and animal studies will also be excluded. Articles considered eligible by both reviewers will move to phase two, while articles considered ineligible by both reviewers will be removed. Conflicts will be resolved during consensus discussions involving a third team member. The same strategy will be applied in phase two for full-text screening. Reasons for exclusion will be tracked in phase two.

    Data collection: Data will be extracted from included articles by one reviewer and verified by another reviewer in Covidence. The extraction will focus on the PICOS framework,43 with a detailed focus on outcome constructs, outcome measurement instruments and timepoints, as well as characteristics of the populations studied. Salient themes from qualitative studies will also be recorded.

    Analysis of findings: A list of unique outcome constructs and associated measurement instruments will be generated by scanning the outcomes identified in the literature and removing duplicates. Identical outcomes and associated measurement instruments from different publications with data from the same study will be collated to prevent overrepresentation of those constructs. Outcomes will be categorised thematically. For example, outcomes related to anxiety and worry will be grouped into a category called psychosocial impact and outcomes related to risk perception and knowledge of T1D will be grouped into a category called cognitive impact. Timepoints for outcome measurement administration will be described and compared across outcomes. Results will be analysed descriptively. Studies will be summarised by publication year, study design and participant characteristics such as age range, level of education, ethnicity, sex and T1D (risk) status. Qualitative outcomes will be summarised thematically.

    Step 1b: Input on candidate outcomes from citizen panels

    In parallel with the rapid review, we will ascertain public perspectives on outcomes that are important and may warrant inclusion in a COS for T1D risk screening. Having established a collaboration between The CanScreen T1D Consortium (www.canscreent1d.ca) and The McMaster Health Forum for the purpose of understanding public opinion on T1D screening in Canada, we will engage members of public panels to assist with this step. The McMaster Health Forum will recruit a stratified purposive sample of people in Canada, through AskingCanadians,TM a consumer research company that maintains a standing pool of ~1 million nationally representative citizens.44 The panels will balance population representativeness with maximum variation, by geography, age, gender, ethnicity and parent vs non-parent status. People and caregivers of children with T1D will also be recruited for the panels through relevant networks (eg, Diabetes Action Canada) and social media. Ethics approval for the panel recruitment process has been provided by McMaster University (REB#15193). Panellists will be asked for their perspective on outcome constructs and measurement tools that they believe to be important for gauging the benefits and potential harms of T1D risk screening for healthy children. Outcomes reported by panellists will be synthesised by the COS study team and merged with the outcomes generated through the rapid review to produce a final list of candidate outcomes. Prioritisation of the final list of candidate outcomes from the rapid review and citizen panel will be facilitated by input from the Advisory Committee.

    Step 2: Outcome preparation

    For outcome preparation, we will leverage our stakeholder dialogue participants (healthcare providers, screening experts, policy makers, PWLE), also recruited by The McMaster Health Forum (REB #15193) as part of the CanScreen T1D Consortium’s public engagement work. As a component of the stakeholder dialogue, we will ask participants to complete a short online survey to gauge whether the candidate outcomes list (developed in step 1) is comprehensive. Participants will be presented with the list of outcomes and asked if they feel that all potentially relevant outcomes have been identified. Participants who select ‘no’ will have the opportunity to list additional outcomes that will be incorporated into the final list of outcomes that will be presented in the Delphi consensus-building process (step 3). The results from the step 2 survey will be analysed descriptively. The outcomes identified from steps 1 and 2 will be synthesised by the Advisory Committee and form the basis for outcome prioritisation using a Delphi survey (step 3).

    Step 3: Delphi consensus surveys

    We will conduct a Delphi survey to begin to establish consensus on outcomes for inclusion in a final COS. Our approach follows methods recommended for COS development45 and the consensus approach used by Pugliese et al.46 Eligible participants will include parents/caregivers in the general population, parents/caregivers of individuals with T1D, healthcare providers, and health policy decision makers. Parents/caregivers of individuals with T1D, healthcare providers, and health policy decision makers will receive study invitations by email from patient advocacy organisations (eg, Diabetes Action Canada, Diabetes Canada, Breakthrough T1D), professional associations (eg, Diabetes Canada, Diabetes Action Canada, Canadian Pediatric Endocrine Group, Breakthrough T1D), or directly from CanScreen T1D using publicly available information. Parents in the general population and parents/caregivers of individuals with T1D will be recruited through Instagram, X and LinkedIn social media posts and the CanScreen Community Engagement Network. The Instagram posts will be designed with five components in mind: the objective, budget, schedule, audience and creative design.47 The objective of the post will be to increase ‘traffic’ to our study, to have individuals complete the screening questionnaire and to enrol in the Delphi consensus process. We estimate that the posts will be featured online for 6–8 weeks. We will target our audience by specifying the eligibility criteria (ie, parents of children aged 0–10 or parents/caregivers of children with T1D aged 0–10). We will engage existing parent-oriented T1D social media groups and request that they share our posts with their community. To capture potential participants’ attention, we will use engaging visuals and captions. We will also recruit parents from the public panels (step 1b). We aim to recruit parent participants that reflect diversity in geographic region, age, gender, ethnicity and language spoken at home. Clicking on the post will lead to a short demographics’ questionnaire to screen for eligibility. Based on related work, we anticipate recruiting between 75 and 100 participants for the Delphi survey. We will provide compensation of up to $100 per PWLE who participates in the Delphi process. This compensation will be determined by the number of survey rounds completed, as well as whether the participant attends the consensus meeting.

    We will conduct two rounds of Delphi surveys, with the potential for a third round if warranted.45 Each round will be open for 3 weeks, followed by a 3-week period to analyse the results and develop the next round.45 In round one, participants will be presented with the list of outcomes from step 2, along with definitions for each outcome, and asked to rate the importance of each outcome on a 9-point Likert scale.45 48 Participants will have the opportunity to list any additional outcomes that they feel are important to consider for the COS. Survey results will be analysed descriptively. Aligned with Delphi best practices, all outcomes from round one will be retained for round two45 and all additional outcomes identified by participants will be included in round two. Participants will be presented with their own scores for each outcome, and, to encourage consensus within and the group, scores summarised by the group.49 Participants will be asked to re-consider how they scored each outcome, taking into account feedback from other participants. Round two results will be analysed descriptively. To determine consensus, outcomes that are deemed ‘critical’ by at least 70% of participants and ‘of limited importance’ by fewer than 15% will move on to the next stage. Conversely, outcomes that are deemed ‘of limited importance’ by at least 70% of participants and ‘critical’ by fewer than 15% will be excluded.45

    Step 4: Final consensus meeting

    Following the Delphi surveys, a virtual consensus meeting will be held to arrive at a final set of outcomes that will comprise the COS. A representative subsample of 20–25 Delphi survey participants will have the opportunity to attend the consensus meeting.45 At the meeting, each outcome and mean importance scores from survey rounds one and two will be reviewed. Panellists will then have the opportunity to provide additional feedback on each outcome and to vote on its inclusion or exclusion from the COS. We will use a nominal group technique to allow all perspectives to be considered.

    Step 5: Establishment of outcome measurement instruments for the COS

    Following the consensus meeting and the establishment of a list of outcome constructs, the Advisory Committee will establish a set of outcome measurement instruments for the COS. A list of outcome measurement instruments identified in the rapid review will be compiled and reviewed. We will determine the relevance, feasibility (ie, burden of completion and timepoints), cost, validity and reliability of each instrument following guidance from COSMIN.50 We will also consider the feasibility of translating each instrument into Canadian French. The decision to recommend each instrument will be based on balancing trade-offs across these parameters. The final COS and potential instruments will be circulated to international colleagues (ie, through the CanScreen T1D International Advisory Board and the CanScreen Community Engagement Network) and patient organisations (ie, Diabetes Action Canada, Diabetes Canada, Breakthrough T1D) for feedback before they are finalised.

    Patient and public involvement

    PWLE will be actively involved throughout the entire COS development study and will be part of the COS advisory committee to ensure that the COS developed is meaningful to patients, parents and their families. PWLE will be involved with: (1a) providing feedback to the inclusion and exclusion criteria for the rapid literature review, (1b) completing the candidate outcome surveys, (2) providing feedback for the initial list of outcomes generated to be used in the Delphi, (3) providing feedback for the Delphi surveys, (4) participating in the consensus meeting and (5) finalising the list of outcomes and outcome measurements and disseminating the COS to patient/parent communities.

    Ethics and dissemination

    The study will follow guiding ethical principles of The Tri-Council Policy Statement: Ethical Conduct for Research Involving Humans (TCPS2)51 and align with ethical standards for the use and reporting of data from Indigenous people.52 Ethics approval has been obtained from The Hospital for Sick Children Research Ethics Board (1000081969).

    We will disseminate the COS to end users in ways that are tailored to each group, including but not limited to researcher and clinicians involved in diabetes screening and clinical care, patient and family networks, research funders, journal editors, public health experts, and policymakers. We will publish the results of the rapid review, as well as the final COS in open-access academic journals and present our results at webinars and conferences. We will also liaise with patient groups and social media to share family-centred guidelines regarding monitoring and supporting individuals at risk for T1D.

    Ethics statements

    Patient consent for publication

    References

    1. ↵
      1. Groop PH,
      2. Thomas M,
      3. Feodoroff M, et al
      . Excess Mortality in Patients With Type 1 Diabetes Without Albuminuria-Separating the Contribution of Early and Late Risks. Diabetes Care 2018;41:748–54. doi:10.2337/dc17-1618
      OpenUrlAbstract/FREE Full Text
    2. ↵
      1. Cherubini V,
      2. Grimsmann JM,
      3. Åkesson K, et al
      . Temporal trends in diabetic ketoacidosis at diagnosis of paediatric type 1 diabetes between 2006 and 2016: results from 13 countries in three continents. Diabetologia 2020;63:1530–41. doi:10.1007/s00125-020-05152-1
      OpenUrlCrossRefPubMed
    3. ↵
      1. Sellers EAC,
      2. Pacaud D
      . Diabetic ketoacidosis at presentation of type 1 diabetes in children in Canada during the COVID-19 pandemic. Paediatr Child Health 2021;26:208–9. doi:10.1093/pch/pxab017
      OpenUrl
    4. ↵
      1. Li G-H,
      2. Huang K,
      3. Dong G-P, et al
      . Clinical Incidence and Characteristics of Newly Diagnosed Type 1 Diabetes in Chinese Children and Adolescents: A Nationwide Registry Study of 34 Medical Centers. Front Pediatr 2022;10:888370. doi:10.3389/fped.2022.888370
    5. ↵
      1. Jacobsen LM,
      2. Vehik K,
      3. Veijola R, et al
      . Heterogeneity of DKA Incidence and Age-Specific Clinical Characteristics in Children Diagnosed With Type 1 Diabetes in the TEDDY Study. Diabetes Care 2022;45:624–33. doi:10.2337/dc21-0422
      OpenUrlPubMed
    6. ↵
      1. Lundgren M,
      2. Sahlin Å,
      3. Svensson C, et al
      . Reduced morbidity at diagnosis and improved glycemic control in children previously enrolled in DiPiS follow-up. Pediatr Diabetes 2014;15:494–501. doi:10.1111/pedi.12151
      OpenUrlCrossRefPubMed
    7. ↵
      1. Duca LM,
      2. Wang B,
      3. Rewers M, et al
      . Diabetic Ketoacidosis at Diagnosis of Type 1 Diabetes Predicts Poor Long-term Glycemic Control. Diabetes Care 2017;40:1249–55. doi:10.2337/dc17-0558
      OpenUrlAbstract/FREE Full Text
    8. ↵
      1. Anand V,
      2. Li Y,
      3. Liu B, et al
      . Islet Autoimmunity and HLA Markers of Presymptomatic and Clinical Type 1 Diabetes: Joint Analyses of Prospective Cohort Studies in Finland, Germany, Sweden, and the U.S. Diabetes Care 2021;44:2269–76. doi:10.2337/dc20-1836
      OpenUrlAbstract/FREE Full Text
    9. ↵
      1. Besser REJ,
      2. Bell KJ,
      3. Couper JJ, et al
      . ISPAD Clinical Practice Consensus Guidelines 2022: Stages of type 1 diabetes in children and adolescents. Pediatr Diabetes 2022;23:1175–87. doi:10.1111/pedi.13410
      OpenUrlPubMed
    10. ↵
      1. Insel RA,
      2. Dunne JL,
      3. Atkinson MA, et al
      . Staging presymptomatic type 1 diabetes: a scientific statement of JDRF, the Endocrine Society, and the American Diabetes Association. Diabetes Care 2015;38:1964–74. doi:10.2337/dc15-1419
      OpenUrlAbstract/FREE Full Text
    11. ↵
      1. Redondo MJ,
      2. Gignoux CR,
      3. Dabelea D, et al
      . Type 1 diabetes in diverse ancestries and the use of genetic risk scores. Lancet Diabetes Endocrinol 2022;10:597–608. doi:10.1016/S2213-8587(22)00159-0
      OpenUrlCrossRefPubMed
    12. ↵
      1. Chiou J,
      2. Geusz RJ,
      3. Okino M-L, et al
      . Interpreting type 1 diabetes risk with genetics and single-cell epigenomics. Nature New Biol 2021;594:398–402. doi:10.1038/s41586-021-03552-w
      OpenUrl
    13. ↵
      1. Pociot F
      . Type 1 diabetes genome-wide association studies: not to be lost in translation. Clin Transl Immunology 2017;6:e162. doi:10.1038/cti.2017.51
    14. ↵
      1. Robertson CC,
      2. Inshaw JRJ,
      3. Onengut-Gumuscu S, et al
      . Fine-mapping, trans-ancestral and genomic analyses identify causal variants, cells, genes and drug targets for type 1 diabetes. Nat Genet 2021;53:962–71. doi:10.1038/s41588-021-00880-5
      OpenUrlCrossRefPubMed
    15. ↵
      1. Redondo MJ,
      2. Jeffrey J,
      3. Fain PR, et al
      . Concordance for islet autoimmunity among monozygotic twins. N Engl J Med 2008;359:2849–50. doi:10.1056/NEJMc0805398
      OpenUrlCrossRefPubMedWeb of Science
    16. ↵
      1. Sugrue LP,
      2. Desikan RS
      . What Are Polygenic Scores and Why Are They Important? JAMA 2019;321:1820–1. doi:10.1001/jama.2019.3893
      OpenUrlCrossRefPubMed
    17. ↵
      1. Oram RA,
      2. Patel K,
      3. Hill A, et al
      . A Type 1 Diabetes Genetic Risk Score Can Aid Discrimination Between Type 1 and Type 2 Diabetes in Young Adults. Diabetes Care 2016;39:337–44. doi:10.2337/dc15-1111
      OpenUrlAbstract/FREE Full Text
    18. ↵
      1. Patel KA,
      2. Oram RA,
      3. Flanagan SE, et al
      . Type 1 Diabetes Genetic Risk Score: A Novel Tool to Discriminate Monogenic and Type 1 Diabetes. Diabetes 2016;65:2094–9. doi:10.2337/db15-1690
      OpenUrlAbstract/FREE Full Text
    19. ↵
      1. Perry DJ,
      2. Wasserfall CH,
      3. Oram RA, et al
      . Application of a Genetic Risk Score to Racially Diverse Type 1 Diabetes Populations Demonstrates the Need for Diversity in Risk-Modeling. Sci Rep 2018;8:4529. doi:10.1038/s41598-018-22574-5
    20. ↵
      1. Sharp SA,
      2. Rich SS,
      3. Wood AR, et al
      . Development and Standardization of an Improved Type 1 Diabetes Genetic Risk Score for Use in Newborn Screening and Incident Diagnosis. Diabetes Care 2019;42:200–7. doi:10.2337/dc18-1785
      OpenUrlAbstract/FREE Full Text
    21. ↵
      1. Winkler C,
      2. Krumsiek J,
      3. Buettner F, et al
      . Feature ranking of type 1 diabetes susceptibility genes improves prediction of type 1 diabetes. Diabetologia 2014;57:2521–9. doi:10.1007/s00125-014-3362-1
      OpenUrl
    22. ↵
      1. Johnson SB,
      2. Lynch KF,
      3. Baxter J, et al
      . Predicting Later Study Withdrawal in Participants Active in a Longitudinal Birth Cohort Study for 1 Year: The TEDDY Study. J Pediatr Psychol 2016;41:373–83. doi:10.1093/jpepsy/jsv092
      OpenUrlCrossRefPubMed
    23. ↵
      1. Lernmark B,
      2. Johnson SB,
      3. Vehik K, et al
      . Enrollment experiences in a pediatric longitudinal observational study: The Environmental Determinants of Diabetes in the Young (TEDDY) study. Contemp Clin Trials 2011;32:517–23. doi:10.1016/j.cct.2011.03.009
      OpenUrlCrossRefPubMedWeb of Science
    24. ↵
      1. Lernmark B,
      2. Lynch K,
      3. Baxter J, et al
      . Participant Experiences in the Environmental Determinants of Diabetes in the Young Study: Common Reasons for Withdrawing. J Diabetes Res 2016;2016:2720650. doi:10.1155/2016/2720650
    25. ↵
      1. TEDDY Study Group
      . The Environmental Determinants of Diabetes in the Young (TEDDY) Study. Ann N Y Acad Sci 2008;1150:1–13. doi:10.1196/annals.1447.062
      OpenUrlCrossRefPubMedWeb of Science
    26. ↵
      1. Sims EK,
      2. Besser REJ,
      3. Dayan C, et al
      . Screening for Type 1 Diabetes in the General Population: A Status Report and Perspective. Diabetes 2022;71:610–23. doi:10.2337/dbi20-0054
      OpenUrlCrossRefPubMed
    27. ↵
      1. Johnson SB
      . Psychological impact of screening and prediction in type 1 diabetes. Curr Diab Rep 2011;11:454–9. doi:10.1007/s11892-011-0208-9
      OpenUrlCrossRefPubMed
    28. ↵
      1. Swartling U,
      2. Lynch K,
      3. Smith L, et al
      . Parental Estimation of Their Child’s Increased Type 1 Diabetes Risk During the First 2 Years of Participation in an International Observational Study: Results From the TEDDY study. J Empir Res Hum Res Ethics 2016;11:106–14. doi:10.1177/1556264616648589
      OpenUrlCrossRefPubMed
    29. ↵
      1. Johnson SB,
      2. Lynch KF,
      3. Roth R, et al
      . My Child Is Islet Autoantibody Positive: Impact on Parental Anxiety. Diabetes Care 2017;40:1167–72. doi:10.2337/dc17-0166
      OpenUrlAbstract/FREE Full Text
    30. ↵
      1. Roth R,
      2. Lynch K,
      3. Lernmark B, et al
      . Maternal anxiety about a child’s diabetes risk in the TEDDY study: the potential role of life stress, postpartum depression, and risk perception. Pediatr Diabetes 2015;16:287–98. doi:10.1111/pedi.12168
      OpenUrlPubMed
    31. ↵
      1. Smith LB,
      2. Liu X,
      3. Johnson SB, et al
      . Family adjustment to diabetes diagnosis in children: Can participation in a study on type 1 diabetes genetic risk be helpful? Pediatr Diabetes 2018;19:1025–33. doi:10.1111/pedi.12674
      OpenUrlCrossRef
    32. ↵
      1. Webbe J,
      2. Sinha I,
      3. Gale C
      . Core Outcome Sets. Arch Dis Child Educ Pract Ed 2018;103:163–6. doi:10.1136/archdischild-2016-312117
      OpenUrlFREE Full Text
    33. ↵
      1. Williamson PR,
      2. Altman DG,
      3. Blazeby JM, et al
      . The COMET (core outcome measures in effectiveness trials) initiative. Trials 2011;12:A70. doi:10.1186/1745-6215-12-S1-A70
    34. ↵
      1. Nano J,
      2. Carinci F,
      3. Okunade O, et al
      . A standard set of person-centred outcomes for diabetes mellitus: results of an international and unified approach. Diabet Med 2020;37:2009–18. doi:10.1111/dme.14286
      OpenUrlPubMed
    35. ↵
      1. Porth A-K,
      2. Huberts AS,
      3. Rogge A, et al
      . Standardising personalised diabetes care across European health settings: A person-centred outcome set agreed in a multinational Delphi study. Diabet Med 2024;41:e15259. doi:10.1111/dme.15259
    36. ↵
      1. Skovlund SE,
      2. Troelsen LH,
      3. Klim L, et al
      . The participatory development of a national core set of person-centred diabetes outcome constructs for use in routine diabetes care across healthcare sectors. Res Involv Engagem 2021;7:62. doi:10.1186/s40900-021-00309-7
    37. ↵
      1. Byrne M,
      2. O’Connell A,
      3. Egan AM, et al
      . A core outcomes set for clinical trials of interventions for young adults with type 1 diabetes: an international, multi-perspective Delphi consensus study. Trials 2017;18:602. doi:10.1186/s13063-017-2364-y
    38. ↵
      1. de Wit M,
      2. van Luik S,
      3. Marrero D, et al
      . Person-reported outcomes in registered randomised diabetes trials: A mapping review of constructs. Diabet Med 2024;41:e15385. doi:10.1111/dme.15385
    39. ↵
      1. Agiostratidou G,
      2. Anhalt H,
      3. Ball D, et al
      . Standardizing Clinically Meaningful Outcome Measures Beyond HbA1c for Type 1 Diabetes: A Consensus Report of the American Association of Clinical Endocrinologists, the American Association of Diabetes Educators, the American Diabetes Association, the Endocrine Society, JDRF International, The Leona M. and Harry B. Helmsley Charitable Trust, the Pediatric Endocrine Society, and the T1D Exchange. Diabetes Care 2017;40:1622–30. doi:10.2337/dc17-1624
      OpenUrlAbstract/FREE Full Text
    40. ↵
      1. Kirkham JJ,
      2. Gorst S,
      3. Altman DG, et al
      . Core Outcome Set-STAndardised Protocol Items: the COS-STAP Statement. Trials 2019;20:116. doi:10.1186/s13063-019-3230-x
    41. ↵
      1. Hamel C,
      2. Michaud A,
      3. Thuku M, et al
      . Defining Rapid Reviews: a systematic scoping review and thematic analysis of definitions and defining characteristics of rapid reviews. J Clin Epidemiol 2021;129:74–85. doi:10.1016/j.jclinepi.2020.09.041
      OpenUrlCrossRefPubMed
    42. ↵
      1. Veritas Health Innovation
      . Covidence systematic review software. Melbourne, Australia: Veritas Health Innovation, 2024. Available: www.covidence.org
    43. ↵
      1. Methley AM,
      2. Campbell S,
      3. Chew-Graham C, et al
      . PICO, PICOS and SPIDER: a comparison study of specificity and sensitivity in three search tools for qualitative systematic reviews. BMC Health Serv Res 2014;14:579. doi:10.1186/s12913-014-0579-0
    44. ↵
      1. SAGO
      . Panel - asking Canadians. 2024.
    45. ↵
      1. Williamson PR,
      2. Altman DG,
      3. Bagley H, et al
      . The COMET Handbook: version 1.0. Trials 2017;18:280. doi:10.1186/s13063-017-1978-4
    46. ↵
      1. Pugliese M,
      2. Tingley K,
      3. Chow A, et al
      . Core Outcome Sets for Medium-Chain Acyl-CoA Dehydrogenase Deficiency and Phenylketonuria. Pediatrics 2021;148:e2020037747. doi:10.1542/peds.2020-037747
    47. ↵
      1. Meta
      . The ad auction explained.
    48. ↵
      GRADE home. 2022. Available: https://www.gradeworkinggroup.org/
    49. ↵
      1. Monga S,
      2. Monsour A,
      3. Stallwood E, et al
      . Core Outcome Set Development for Adolescent Major Depressive Disorder Clinical Trials: A Registered Report. J Am Acad Child Adolesc Psychiatry 2020;59:1297–8. doi:10.1016/j.jaac.2020.07.905
      OpenUrl
    50. ↵
      1. Prinsen CAC,
      2. Vohra S,
      3. Rose MR, et al
      . How to select outcome measurement instruments for outcomes included in a “Core Outcome Set” - a practical guideline. Trials 2016;17:449. doi:10.1186/s13063-016-1555-2
    51. ↵
      1. Canadian Institutes of Health Research, Natural Sciences and Engineering Research Council of Canada, and Social Sciences and Humanities Research Council
      . Tri-council policy statement: ethical conduct for research involving humans. 2018. Available: https://ethics.gc.ca/eng/policy-politique_tcps2-eptc2_2022.html [Accessed 01 Apr 2024].
    52. ↵
      1. Yracheta J,
      2. Morriseau T,
      3. Dale K, et al
      . Scientists and scientific journals should adhere to ethical standards for the use and reporting of data from Indigenous people. Diabetologia 2024;67:2404–7. doi:10.1007/s00125-024-06236-y
      OpenUrl

    Footnotes

    • X @Wilson_MichaelG

    • Contributors RZH and CC conceptualised the study. CC, SL, AH and RZH will be involved in data collection, analysis and interpretation of data. DW, HW, PC, AL, MW, JM and SD will provide expert guidance throughout the project. CC drafted the manuscript. All authors reviewed and provided critical feedback on the manuscript. All authors have read and approved the manuscript. RZH is the guarantor.

    • Funding This work was supported by The CanScreen T1D Consortium, for which funding has been provided by the Canadian Institutes of Health Research T1D-189647 and Breakthrough T1D (formerly Juvenile Diabetes Research Foundation Canada) 4-SRA-2023-1456-S-N. RZ Hayeems is supported by a Canada Research Chair in Genomics and Health Policy.

    • Competing interests None declared.

    • Patient and public involvement Patients and/or the public were involved in the design, or conduct, or reporting, or dissemination plans of this research. Refer to the Methods section for further details.

    • Provenance and peer review Not commissioned; externally peer reviewed.