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High-Profile Autism Study Has Skeptics

One author examines the study and find the conclusion overstated

A recent study reported that mothers who take antidepressants increase the risk of autism in their unborn children by up to 87%, but one scientist has explained his doubts in a Forbes article.

Many scientists read the news of the study with skepticism. Exactly two years ago, another large study reported exactly the opposite conclusion. The 2013 study, published in the New England Journal of Medicine, found that antidepressant use during pregnancy was NOT associated with an increased risk of autism. What’s more, the 2013 study looked at exactly the same class of antidepressants, selective serotonin reuptake inhibitors (SSRIs), as the new study.

So what’s going on? Was the 2013 study just wrong? Looking at the numbers in the new study, written by Anick Bérard and colleagues, Forbes contributor Steven Salzberg concluded that the researchers  tortured the data until they got the results — and the headlines — that they wanted.

Bérard and colleagues looked at 145,456 children born in Quebec between 1998 and 2009. From this total, 4,724 were born to mothers who took SSRIs at some time during pregnancy. The number of children diagnosed with autism was 1,054, about 0.7% of all babies. Only 46 of the 1,054 were born to mothers who had taken antidepressants. The study’s main results concern mothers who took antidepressants in the second or third trimester; these women accounted for 2,532 infants, of whom 31 were diagnosed with autism.

Salzberg recommends focusing on one number: 31. The study’s main conclusion — and the headlines — are based on those 31 children diagnosed with autism whose mothers took antidepressants in their second or third trimesters.

Out of 9,207 infants whose mothers took antidepressants one year before getting pregnant, 82 were later diagnosed with autism. Bérard et al. found that, after adjusting for various confounders, this group of infants had no increased risk of autism. Another group was infants whose mothers took antidepressants in the first trimester: of these 4,200 infants, 40 were diagnosed with autism. Bérard et al. computed that the adjusted risk for this group was 16% lower than average. This difference was not statistically significant, though.

Finally, there’s the third group of 2,532 children whose mothers took antidepressants during the second or third trimesters; 31 of these children were later diagnosed with autism, which worked out to an increase in relative risk of 87%.

The first thing to note here is that the increase is relative, not absolute. The overall risk of autism in this study, which was consistent with other studies, was 0.7%. An 87% increase works out to a risk of 1.3% — that’s an increase of 0.6% in the rate of autism. This doesn’t sound nearly so dramatic as 87%.

Apparently this means only that the children were evaluated for autism, as Dr. Alison Stuebe at the Huffington Post pointed out. Bérard et al. state this in their paper where they report that when they restricted their analysis to children whose diagnoses were confirmed by a psychiatrist or neurologist, the number of children with autism was smaller and the increased risk was not statistically significant. In other words, if they looked only at children with confirmed autism, their main conclusion would fade away.

Bérard et al. divided the data up in multiple ways to look for an increase in autism, looking at mothers who took antidepressants before getting pregnant, during the first trimester, and during the second and third trimesters. They don’t report any findings for the second trimester alone, or for the third trimester alone, which would have involved smaller numbers.

This raises a potentially fatal problem with the study: multiple testing. Whenever a study considers more than one hypothesis, the statistics must be adjusted to account for that, Salzberg writes. If you look for an effect in ten different ways, you’re more likely to find something by chance alone, so you have to find a much stronger effect in order for it to be valid.

Source: Forbes, December 21, 2015.

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