Concentration-Response Relationship for Fluvoxamine Using Remission as an Endpoint
Bibliographic record
Abstract
Therapeutic drug monitoring studies of selective serotonin reuptake inhibitor (SSRI) antidepressants thus far failed to identify a clear concentration-response relationship in major depression. Majority of the previous studies defined clinical response as 50% or greater reduction from baseline in depression rating scale scores. Because many patients who meet these criteria still present symptoms associated with functional impairment, there is a need to consider "remission" as an alternative end point in concentration-response analyses of SSRIs. The present 12-week prospective study investigated the relationship between fluvoxamine (an SSRI) plasma concentration and remission in outpatients with depression. We used a flexible dose titration study designed to mimic clinical practice within the therapeutic dose range of fluvoxamine (25-200 mg/d). Receiver operating characteristics (ROC) curve was computed to determine the optimal fluvoxamine plasma concentration for remission using 269 concentration data obtained from 80 patients. Analysis of the ROC curve from the entire study sample did not reveal a fluvoxamine concentration significantly predicting remission. By contrast, ROC analysis specifically in patients with moderate to severe depression (N = 51; baseline 17-item Hamilton Rating Scale for Depression score > or = 20) found a fluvoxamine concentration of 61.4 ng/mL as a significant predictor of remission. In conclusion, therapeutic drug monitoring may be useful for rational titration and individualization of fluvoxamine dose and predicting remission in patients with moderate to severe depression, who may presumably display lesser placebo component in pharmacodynamic response.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".