Restoring the two pivotal fluoxetine trials in children and adolescents with depression
Bibliographic record
Abstract
BACKGROUND: Fluoxetine was approved for depression in children and adolescents based on two placebo-controlled trials, X065 and HCJE, with 96 and 219 participants, respectively. OBJECTIVE: To review these trials, which appear to have been misreported. METHODS: Systematic review of the clinical study reports and publications. The primary outcomes were the efficacy variables in the trial protocols, suicidal events, and precursors to suicidality or violence. RESULTS: Essential information was missing and there were unexplained numerical inconsistencies. (1) The efficacy outcomes were biased in favour of fluoxetine by differential dropouts and missing data. The efficacy on the Children's Depression Rating Scale-Revised was 4% of the baseline score, which is not clinically relevant. Patient ratings did not find fluoxetine effective. (2) Suicidal events were missing in the publications and the study reports. Precursors to suicidality or violence occurred more often on fluoxetine than on placebo. For trial HCJE, the number needed to harm was 6 for nervous system events, 7 for moderate or severe harm, and 10 for severe harm. Fluoxetine reduced height and weight over 19 weeks by 1.0 cm and 1.1 kg, respectively, and prolonged the QT interval. CONCLUSIONS: Our reanalysis of the two pivotal trials showed that fluoxetine is unsafe and ineffective.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.032 | 0.079 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".