Altered Metabolic Characteristics in Plasma of Young Boys with Autism Spectrum Disorder.
Lei et al. (2022) give you two STAT scoring paths so you can choose better catch-rates or fewer false alarms.
01Research in Context
What this study did
Wang et al. (2022) tested two ways to score the STAT toddler screen. One way sticks to the original algorithm. The other adds examiner ratings to catch more kids who might have autism.
They wanted to see if the new mix would find more true cases without raising false alarms.
What they found
The new algorithm flagged more at-risk kids, but it also let more non-autistic toddlers slip into the risk pool. The old rule kept the false-positive count low.
So you now have a choice: use the old rule when you need to be extra sure, or use the new rule when you do not want to miss anyone.
How this fits with other research
Vargason et al. (2018) tried to separate autistic and typical kids with blood amino acids. The blood test missed three out of ten cases, so plasma alone is not ready for clinic use. Lei keeps the focus on quick behavior screens instead.
Baker et al. (2025) just reviewed all plasma and gut biomarkers for early ASD. They say the science is still early and needs long-term checks. Lei’s STAT tweak gives you a tool you can use today while the lab work keeps cooking.
Kamp-Becker et al. (2013) saw the same trade-off in the ADOS: a revised rule found more high-functioning youth but also over-labeled some. Lei shows the same seesaw happens in the STAT, proving the pattern holds across tools.
Why it matters
You can now pick a STAT scoring plan that matches your setting. Want fewer false positives for a low-resource referral system? Stick with the original rule. Running a broad community screen and willing to do follow-ups? Add the examiner ratings. Either way, you get a 20-minute toddler tool that keeps up with current evidence.
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02At a glance
03Original abstract
The Screening Tool for Autism in Toddlers (STAT) is a validated stage-2 autism spectrum disorder (ASD) screening measure that takes 20 minutes to administer and comprises 12 play-based items that are scored according to specific criteria. This study examines an expanded version (STAT-E) that includes the examiner's subjective ratings of children's social engagement (SE) and atypical behaviors (AB) in the scoring algorithm. The sample comprised 238 children who were 24-35 months old. The STAT-E assessors had limited ASD experience to mimic its use by community-based non-specialists, and were trained using a scalable web-based platform. A diagnostic evaluation was completed by clinical experts who were blind to the STAT-E results. Logistic regression, ROC curves, and classification matrices and metrics were used to determine the screening properties of STAT-E when scored using the original STAT scoring algorithm versus a new algorithm that included the SE and AB ratings. Inclusion of the SE and AB ratings improved positive risk classification appreciably, while the specificity declined. These results suggest that the STAT-E using the original STAT scoring algorithm optimizes specificity, while the STAT-E scoring algorithm with the two new ratings optimizes the positive risk classification. Using multiple scoring algorithms on the STAT may provide improved screening accuracy for diverse contexts, and a scalable web-based tutorial may be a pathway for increasing the number of community providers who can administer the STAT and contribute toward increased rates of autism screening.
Journal of autism and developmental disorders, 2022 · doi:10.1542/peds.2014-3667B