What are we optimizing for in autism screening? Examination of algorithmic changes in the M-CHAT.

Autor: Schjølberg S; Mental Health, Norwegian Institute of Public Health, Oslo, Norway., Shic F; Seattle Children's Research Institute, University of Washington School of Medicine, Seattle, Washington, USA., Volkmar FR; Yale University, New Haven, Connecticut, USA.; Southern Connecticut University, New Haven, Connecticut, USA., Nordahl-Hansen A; Education, Østfold University College, Halden, Norway., Stenberg N; Oslo University Hospital, Oslo, Norway., Torske T; Vestre Viken Hospital, Drammen, Norway., Larsen K; Education, UiT-The Arctic University of Norway, Tromso, Norway., Riley K; Seattle Children's Research Institute, University of Washington School of Medicine, Seattle, Washington, USA., Sukhodolsky DG; Yale University, New Haven, Connecticut, USA., Leckman JF; Yale University, New Haven, Connecticut, USA., Chawarska K; Yale University, New Haven, Connecticut, USA., Øien RA; Yale University, New Haven, Connecticut, USA.; Education, UiT-The Arctic University of Norway, Tromso, Norway.
Jazyk: angličtina
Zdroj: Autism research : official journal of the International Society for Autism Research [Autism Res] 2022 Feb; Vol. 15 (2), pp. 296-304. Date of Electronic Publication: 2021 Nov 26.
DOI: 10.1002/aur.2643
Abstrakt: The present study objectives were to examine the performance of the new M-CHAT-R algorithm to the original M-CHAT algorithm. The main purpose was to examine if the algorithmic changes increase identification of children later diagnosed with ASD, and to examine if there is a trade-off when changing algorithms. We included 54,463 screened cases from the Norwegian Mother and Child Cohort Study. Children were screened using the 23 items of the M-CHAT at 18 months. Further, the performance of the M-CHAT-R algorithm was compared to the M-CHAT algorithm on the 23-items. In total, 337 individuals were later diagnosed with ASD. Using M-CHAT-R algorithm decreased the number of correctly identified ASD children by 12 compared to M-CHAT, with no children with ASD screening negative on the M-CHAT criteria subsequently screening positive utilizing the M-CHAT-R algorithm. A nonparametric McNemar's test determined a statistically significant difference in identifying ASD utilizing the M-CHAT-R algorithm. The present study examined the application of 20-item MCHAT-R scoring criterion to the 23-item MCHAT. We found that this resulted in decreased sensitivity and increased specificity for identifying children with ASD, which is a trade-off that needs further investigation in terms of cost-effectiveness. However, further research is needed to optimize screening for ASD in the early developmental period to increase identification of false negatives.
(© 2021 The Authors. Autism Research published by International Society for Autism Research and Wiley Periodicals LLC.)
Databáze: MEDLINE
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