Eye-Tracking Biomarkers and Autism Diagnosis in Primary Care

被引:0
|
作者
Keehn, Brandon [1 ,2 ]
Monahan, Patrick [3 ]
Enneking, Brett [4 ]
Ryan, Tybytha [4 ]
Swigonski, Nancy [4 ]
Keehn, Rebecca McNally [4 ]
机构
[1] Purdue Univ, Dept Speech Language & Hearing Sci, 715 Clin Dr,Lyles Porter Hall, W Lafayette, IN 47907 USA
[2] Purdue Univ, Dept Psychol Sci, W Lafayette, IN USA
[3] Indiana Univ Sch Med, Dept Biostat & Hlth Data Sci, Indianapolis, IN USA
[4] Indiana Univ, Sch Med, Indianapolis, IN USA
关键词
SPECTRUM DISORDER; CHILDREN; RISK; MODEL; INTERVENTION; ATTENTION; SERVICES; INFANTS; ACCESS;
D O I
10.1001/jamanetworkopen.2024.11190
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Importance Finding effective and scalable solutions to address diagnostic delays and disparities in autism is a public health imperative. Approaches that integrate eye-tracking biomarkers into tiered community-based models of autism evaluation hold promise for addressing this problem. Objective To determine whether a battery of eye-tracking biomarkers can reliably differentiate young children with and without autism in a community-referred sample collected during clinical evaluation in the primary care setting and to evaluate whether combining eye-tracking biomarkers with primary care practitioner (PCP) diagnosis and diagnostic certainty is associated with diagnostic outcome. Design, Setting, and Participants Early Autism Evaluation (EAE) Hub system PCPs referred a consecutive sample of children to this prospective diagnostic study for blinded eye-tracking index test and follow-up expert evaluation from June 7, 2019, to September 23, 2022. Participants included 146 children (aged 14-48 months) consecutively referred by 7 EAE Hubs. Of 154 children enrolled, 146 provided usable data for at least 1 eye-tracking measure. Main Outcomes and Measures The primary outcomes were sensitivity and specificity of a composite eye-tracking (ie, index) test, which was a consolidated measure based on significant eye-tracking indices, compared with reference standard expert clinical autism diagnosis. Secondary outcome measures were sensitivity and specificity of an integrated approach using an index test and PCP diagnosis and certainty. Results Among 146 children (mean [SD] age, 2.6 [0.6] years; 104 [71%] male; 21 [14%] Hispanic or Latine and 96 [66%] non-Latine White; 102 [70%] with a reference standard autism diagnosis), 113 (77%) had concordant autism outcomes between the index (composite biomarker) and reference outcomes, with 77.5% sensitivity (95% CI, 68.4%-84.5%) and 77.3% specificity (95% CI, 63.0%-87.2%). When index diagnosis was based on the combination of a composite biomarker, PCP diagnosis, and diagnostic certainty, outcomes were concordant with reference standard for 114 of 127 cases (90%) with a sensitivity of 90.7% (95% CI, 83.3%-95.0%) and a specificity of 86.7% (95% CI, 70.3%-94.7%). Conclusions and Relevance In this prospective diagnostic study, a composite eye-tracking biomarker was associated with a best-estimate clinical diagnosis of autism, and an integrated diagnostic model including PCP diagnosis and diagnostic certainty demonstrated improved sensitivity and specificity. These findings suggest that equipping PCPs with a multimethod diagnostic approach has the potential to substantially improve access to timely, accurate diagnosis in local communities.
引用
收藏
页数:14
相关论文
共 50 条
  • [1] Autism, Eye-Tracking, Entropy
    Shic, Frederick
    Chawarska, Katarzyna
    Bradshaw, Jessica
    Scassellati, Brian
    2008 IEEE 7TH INTERNATIONAL CONFERENCE ON DEVELOPMENT AND LEARNING, 2008, : 73 - 78
  • [2] Eye-tracking technique as an instrument in the diagnosis of autism spectrum disorder
    Alves da Silva, A. Ciccarelli
    Varanda, C.
    EUROPEAN PSYCHIATRY, 2018, 48 : S478 - S479
  • [3] The autism biomarkers consortium for clinical trials: evaluation of a battery of candidate eye-tracking biomarkers for use in autism clinical trials
    Shic, Frederick
    Naples, Adam J.
    Barney, Erin C.
    Chang, Shou An
    Li, Beibin
    McAllister, Takumi
    Kim, Minah
    Dommer, Kelsey J.
    Hasselmo, Simone
    Atyabi, Adham
    Wang, Quan
    Helleman, Gerhard
    Levin, April R.
    Seow, Helen
    Bernier, Raphael
    Charwaska, Katarzyna
    Dawson, Geraldine
    Dziura, James
    Faja, Susan
    Jeste, Shafali Spurling
    Johnson, Scott P.
    Murias, Michael
    Nelson, Charles A.
    Sabatos-DeVito, Maura
    Senturk, Damla
    Sugar, Catherine A.
    Webb, Sara J.
    McPartland, James C.
    MOLECULAR AUTISM, 2022, 13 (01)
  • [4] The Autism Biomarkers Consortium for Clinical Trials: evaluation of a battery of candidate eye-tracking biomarkers for use in autism clinical trials
    Frederick Shic
    Adam J. Naples
    Erin C. Barney
    Shou An Chang
    Beibin Li
    Takumi McAllister
    Minah Kim
    Kelsey J. Dommer
    Simone Hasselmo
    Adham Atyabi
    Quan Wang
    Gerhard Helleman
    April R. Levin
    Helen Seow
    Raphael Bernier
    Katarzyna Charwaska
    Geraldine Dawson
    James Dziura
    Susan Faja
    Shafali Spurling Jeste
    Scott P. Johnson
    Michael Murias
    Charles A. Nelson
    Maura Sabatos-DeVito
    Damla Senturk
    Catherine A. Sugar
    Sara J. Webb
    James C. McPartland
    Molecular Autism, 13
  • [5] Accessible Texts for Autism: An Eye-Tracking Study
    Yaneva, Victoria
    Temnikova, Irina
    Mitkov, Ruslan
    ASSETS'15: PROCEEDINGS OF THE 17TH INTERNATIONAL ACM SIGACCESS CONFERENCE ON COMPUTERS & ACCESSIBILITY, 2015, : 49 - 57
  • [6] The application of eye-tracking technology in the study of autism
    Boraston, Zillah
    Blakemore, Sarah-Jayne
    JOURNAL OF PHYSIOLOGY-LONDON, 2007, 581 (03): : 893 - 898
  • [7] Eye-tracking devices in intensive care
    Flint, Lewis
    SURGERY, 2016, 159 (03) : 945 - 946
  • [8] Vision-based Approach for Autism Diagnosis using Transfer Learning and Eye-tracking
    Elbattah, Mahmoud
    Guerin, Jean-Luc
    Carette, Romuald
    Cilia, Federica
    Dequen, Gilles
    HEALTHINF: PROCEEDINGS OF THE 15TH INTERNATIONAL JOINT CONFERENCE ON BIOMEDICAL ENGINEERING SYSTEMS AND TECHNOLOGIES - VOL 5: HEALTHINF, 2021, : 256 - 263
  • [9] New Approaches to Eye-Tracking Analysis in Autism Research
    Falck-Ytter, Terje
    BIOLOGICAL PSYCHIATRY-COGNITIVE NEUROSCIENCE AND NEUROIMAGING, 2025, 10 (01) : 3 - 4
  • [10] Utilizing deep learning models in an intelligent eye-tracking system for autism spectrum disorder diagnosis
    Alsharif, Nizar
    Al-Adhaileh, Mosleh Hmoud
    Al-Yaari, Mohammed
    Farhah, Nesren
    Khan, Zafar Iqbal
    FRONTIERS IN MEDICINE, 2024, 11