Single 2006 trial in Iran skewed medical evidence supporting Prozac use for youth depression

A single clinical trial conducted in Iran and published in 2006 on 40 children may have wrongly swayed medical evidence in favour of using the antidepressant Prozac, known generically as fluoxetine, to treat depression in children and adolescents. A group of researchers has called the trial's findings into question, suggesting that Prozac's recommendation in paediatric clinical guidelines lacks sufficient supporting evidence.

Findings

The controversial 2006 trial found that Prozac had an enormous advantage over another antidepressant called nortriptyline. Martin Plöderl, a clinical psychotherapist at Paracelsus Medical Private University in Salzburg, Austria, and a co-author of the latest study, stated that the effect size was so large as to be unheard of in biomedical science. When Plöderl and his colleagues re-ran major meta-analyses from 2016 and 2020 while excluding data from the 2006 trial, Prozac's outsized benefits completely disappeared.

Reactions

Richard Lyus, a consultant child and adolescent psychiatrist in Cambridge, UK, and co-author of the new study published in Cochrane Evidence Synthesis and Methods, urges guideline committees to review their recommendations and weigh up whether the drug's use can still be justified. The researchers stopped short of calling for clinicians to stop prescribing Prozac entirely. Florian Naudet, a psychiatrist at the University of Rennes in France, described the trial as a 'zombie' trial with data too flawed to be trustworthy. Elia Abi-Jaoude, a psychiatrist at the Hospital for Sick Children in Toronto, Canada, called the paper a slam-dunk study.

Context

Clinical guidelines often rely on systematic reviews and meta-analyses that combine data from multiple individual studies to reach broad medical conclusions. When a flawed or untrustworthy study enters this evidence pool, it can distort the final conclusions and influence medical practices globally. Scientific bodies are increasingly adopting specific protocols to identify and exclude such problematic data before recommendations are finalized.