IMFAR, the autism numbers game and 12% showing 'optimal outcome'

A post recently published on the Spectrum website led to my blogging entry today, and the observation that: 'Alternative screen finds high autism prevalence in U.S. state'.

Discussing results delivered at IMFAR 2017 the research in question was that presented by Laura Carpenter and colleagues [1] (someone with quite a track record in autism research). This was a conference presentation and seemingly not yet peer-reviewed publication, so one needs to be a little cautious about making big claims just yet. That being said, there have been research hints that these results would be forthcoming [2] around this time.

The headline finding was that the prevalence of autism spectrum disorder (ASD) in one particular part of the United States for the birth year 2004 was probably quite a bit higher than that previously reported/estimated based on initial screening for possible ASD and then actual assessment. Details of the initiative used in this research - the South Carolina Children’s Educational Surveillance Study (SUCCESS) - can be found here.

Some 4100 children were "screened for ASD using the Social Communication Questionnaire." Those who were deemed 'at risk' for autism and a small proportion of those not hitting those *might be autism* thresholds were asked back for a more detailed interview. Although the number of children actually followed-up and interviewed who were eligible for further assessment was not particularly great, the authors were able to draw up an estimated prevalence of autism based on those who did complete the study. The figure: "ASD prevalence in this sample is 3.62%" roughly equivalent to 1 in 28 children. I say this in the context that in the United States and elsewhere, autism rates and/or numbers of cases are still high (see here and see here) and acknowledgement of the implications of such increases when it comes to services such as education, healthcare and the like.

The Spectrum article focuses quite a bit on the participation rate noted in the Carpenter study but another snippet of information is also included in the conference abstract that is worthy of discussion. A detail that reads: "Six children (6/52; 12%) had a clear developmental history of ASD but did not display clinically significant symptoms at the time of participation in this study." Further: "12% with a history of ASD no longer had significant ASD-related symptoms, providing further support for the potential for optimal outcomes in some individuals."

I'm rather interested in that 12% figure with 'optimal outcome'. Optimal outcome describes cases where a clear indication/diagnosis of autism has been seen/received, but for whatever reason(s) diagnostic thresholds are not longer met at a future assessment point. I've covered this group quite a few times on this blog, most notably in relation to a previous estimate of 9% of those diagnosed with autism potentially falling into this category (see here). Appreciating that such data challenges the assumption that *all* autism is a lifelong condition (indeed, stretching across the entire autism spectrum - see here), I'd reiterate that those described as being 'optimal outcomers' represent an important subgroup on the autism spectrum in these days of plural autisms (see here). Not least is the question: Why? Why do these children not maintain their diagnosis and what lessons (if any) can be learned for the wider autism spectrum, particularly also in the context that various quite disabling comorbidities might also be 'reduced' alongside core autism symptoms in this group.

We await formal peer-reviewed publication of the Carpenter findings and perhaps some further details.

To close, upon introducing my brood to the music of Kate Bush, I am yet again reminded just how good a singer/performer she really is...

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[1] Carpenter LA. et al. The Prevalence of Autism Spectrum Disorder in School Aged Children: Population Based Screening and Direct Assessment. IMFAR 2017.

[2] Carpenter LA. et al. Screening and direct assessment methodology to determine the prevalence of autism spectrum disorders. Ann Epidemiol. 2016 Jun;26(6):395-400.

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Carpenter LA, Boan AD, Wahlquist AE, Cohen A, Charles J, Jenner W, & Bradley CC (2016). Screening and direct assessment methodology to determine the prevalence of autism spectrum disorders. Annals of epidemiology, 26 (6), 395-400 PMID: 27230493