Prognostic factors of improvement in health-related quality of life in atomoxetine-treated children and adolescents with attention-deficit/hyperactivity disorder, based on a pooled analysis
Bibliographic record
Abstract
The objective of this study is to identify prognostic factors of treatment response to atomoxetine in improvement of health-related quality of life (HR-QoL), measured by the Child Health and Illness Profile-Child Edition Parent Report Form (CHIP-CE PRF) Achievement and Risk Avoidance domains, in children and adolescents with attention-deficit/hyperactivity disorder (ADHD). Pooled data from 3 placebo-controlled trials and separate data from 3 open-label trials of atomoxetine in children and adolescents with ADHD were analyzed using logistic regression methods. Based on baseline impairment in the Achievement and/or Risk Avoidance domains (CHIP-CE PRF < 40 points), 2 subsamples of subjects were included. Treatment outcome was categorized as <5 points or ≥5 points increase in the CHIP-CE PRF Achievement and Risk Avoidance domains. Data of 190 and 183 subjects from the pooled sample, and 422 and 355 subjects from the open-label trials were included in the analysis of Achievement and Risk Avoidance domains. Baseline CHIP-CE subdomain scores proved to be the most robust prognostic factors for treatment outcome in both domains, based on data from the pooled sample of double-blind studies and from the individual open-label studies (odds ratios [OR] 0.74-1.56, p < 0.05; OR < 1, indicating a worse baseline score associated with worse odds of responding). Initial treatment response (≥25 % reduction in ADHD Rating Scale scores in the first 4-6 weeks) was another robust prognostic factor, based on data from the open-label studies (OR 2.99-6.19, p < 0.05). Baseline impairment in HR-QoL and initial treatment response can be early prognostic factors of atomoxetine treatment outcome in HR-QoL in children and adolescents with ADHD.
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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 | 0.010 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.008 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".