Early Symptom Improvement as a Predictor of Response to Extended Release Quetiapine in Major Depressive Disorder
Bibliographic record
Abstract
The aim of this post-hoc analysis was to determine whether early symptom improvement with extended release quetiapine (quetiapine XR) may predict treatment outcome in patients with major depressive disorder. Data were from 6, double-blind, placebo-controlled studies of quetiapine XR (2 fixed-dose and 2 flexible-dose monotherapy and 2 adjunct studies) in adult patients with major depressive disorder. Montgomery-Åsberg Depression Rating Scale (MADRS) and Clinical Global Impression-Severity Score (CGI-S) were assessed at baseline, weeks 2, 4, and 6. Hamilton Rating Scale for Depression (HAM-D) was assessed at baseline and week 6. The MADRS improvement at week 2 (15%, 20%, 25%, 30%) was used to predict response and remission, based on MADRS (50% improvement; total score ≤ 12) or HAM-D (50% improvement; total score ≤ 7). The CGI-S improvement (1 point) at week 2 was used to predict final outcome (CGI-S score ≤ 2). The predictive value for early improvement with quetiapine XR was found to be "very strong" (Yule's Q coefficient, a combined measure of sensitivity and specificity) using 30% MADRS improvement as the threshold. This was relatively comparable for response and remission and for fixed-dose, flexible-dose, and adjunct studies. This was also observed for placebo. Exceptions were: adjunct studies (where predictivity was lower for ongoing antidepressant/placebo), and for remission (predictivity for remission appeared lower than for response with placebo). In conclusion, outcome at week 6 with quetiapine XR for a major depressive episode could be predicted by 30% improvement after 2 weeks, a finding that could give doctors confidence to continue treatment and may facilitate adherence in patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".