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. 2022 Feb 21:2021:516-525.
eCollection 2021.

Simulating Screening for Risk of Childhood Diabetes: The Collaborative Open Outcomes tooL (COOL)

Mohamed Ghalwash  1 , Eileen Koski  1 , Riitta Veijola  2 , Jorma Toppari  3 , William Hagopian  4 , Marian Rewers  5 , Vibha Anand  6
Affiliations

Simulating Screening for Risk of Childhood Diabetes: The Collaborative Open Outcomes tooL (COOL)

Mohamed Ghalwash et al. AMIA Annu Symp Proc. .

Abstract

The Collaborative Open Outcomes tooL (COOL) is a novel, highly configurable application to simulate, evaluate and compare potential population-level screening schedules. Its first application is type 1 diabetes (T1D) screening, where known biomarkers for risk exist but clinical application lags behind. COOL was developed with the T1DI Study Group, in order to assess screening schedules for islet autoimmunity development based on existing datasets. This work shows clinical research utility, but the tool can be applied in other contexts. COOL helps the user define and evaluate a domain knowledge-driven screening schedule, which can be further refined with data-driven insights. COOL can also compare performance of alternative schedules using adjusted sensitivity, specificity, PPV and NPV metrics. Insights from COOL may support a variety of needs in disease screening and surveillance.

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Figures

Figure 1:
Figure 1:
Screening for multiple biomarkers at age 5. COOL has 10 main panels - P1-P10. P1 defines the evaluation cohort. P2 defines the screening schedules. P3 allows the user to evaluate and explore the screening results. P4 shows the screening performance. P5-P7 show high level information about the cohort. P8 shows the number of subjects by category based on screening results. P9-P10 show further insights that could guide the user to refine the screening.
Figure 2:
Figure 2:
Chain screening tests.
Figure 3:
Figure 3:
(a) COOL provides five confirmation options. No confirmation: no confirmation required for positive screens. Confirm for any IAb: positive screen confirmed if any confirmatory sample biomarker is positive. Confirm for at least one initial positive IAb: positive screen confirmed only if at least one positive screening biomarker is positive in confirmatory sample. Confirm for at least two positive IAb: positive screen is confirmed only if at least two positive screening biomarkers are positive in confirmatory sample. Confirm for all IAb: the positive screen is confirmed only if all positive screening biomarkers are positive in confirmatory sample. (b) Blue columns show the status of four biomarkers, B1-B4, for subjects S1-S6. Green columns show biomarker status in the confirmatory sample. 1=positive(+), 0=negative(-). Screening results (+/-) are shown for each subject and confirmation strategy.
Figure 4:
Figure 4:
(a) Panels 1-2: parameters to define a screening schedule. (b) Different screening strategies based on three biomarkers IAA, GADA, and IA2.
Figure 5:
Figure 5:
(a) Screening results: sensitivity, specificity, ppv and npv. (b) Number of subjects who test positive (red), negative (green), missed the test (blue). The number of cases and controls are between parentheses subgroup.
Figure 6:
Figure 6:
Insights from evaluated screening schedule by sub-groups - tested positive (red), negative (green), and missed the test (blue). (a) Distribution of T1D onset age (b) Distribution of age for multiple IAb
Figure 7:
Figure 7:
(a) Chain screen tests. (b) Compare screening schedules.
Figure 8:
Figure 8:
Comparing different screen tests.
Figure 9:
Figure 9:
Various screen tests at different ages.
Figure 10:
Figure 10:
Evaluation of different confirmation strategies.
See this image and copyright information in PMC

References

    1. Duca LM, Reboussin BA, Pihoker C, Imperatore G, Saydah S, Mayer-Davis E. Diabetic ketoacidosis at diagnosis of type 1 diabetes and glycemic control over time: The SEARCH for diabetes in youth study. 20(2):172–179. - PMC - PubMed
    1. Insel RA, Dunne JL, Atkinson MA, Chiang JL, Dabelea D, Gottlieb PA. Staging presymptomatic type 1 diabetes: a scientific statement of JDRF, the Endocrine Society, and the American Diabetes Association. Diabetes care. 2015;38(10):1964–1974. - PMC - PubMed
    1. Hagopian WA, Erlich H, Lernmark Å, Rewers M, Ziegler AG, Simell O. The Environmental Determinants of Diabetes in the Young (TEDDY): genetic criteria and international diabetes risk screening of 421 000 infants. Pediatric diabetes. 2011;12(8):733–743. - PMC - PubMed
    1. Herold KC, Bundy BN, Long SA, Bluestone JA, DiMeglio LA, Dufort MJ. An anti-CD3 antibody, teplizumab, in relatives at risk for type 1 diabetes. New Engl and Journal of Medicine. 2019;381(7):603–613. - PMC - PubMed
    1. Anand V, Liu B, Ghalwash M, Koski E, Ng K, Dunne JL. 1345-P: Presymptomatic and Clinical T1D in The US, Sweden, and Finland: Joint Analysis of Four Birth Cohort Studies. Am Diabetes Assoc. 2019

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