Evidence-Based Review of Clinical Outcomes of Guideline-Recommended Pharmacotherapies for Generalized Anxiety Disorder
Bibliographic record
Abstract
OBJECTIVE: To quantify the rates of clinical outcomes of Canadian Psychiatric Association (CPA) guideline-recommended pharmacotherapies for generalized anxiety disorder (GAD) by drug classification within each treatment line. METHODS: Evidence from original research cited by the CPA was included. Pooled analyses, duplicates, and studies with nonextractable data were excluded. Response, remission, and baseline-endpoint or mean reductions scores of the Hamilton Anxiety Rating Scale (HARS) were extracted. The Cochrane Collaboration's computer program, Review Manager, version 5, with a random effects model, was used to pool results. RESULTS: A total of 50 articles were cited as evidence for managing GAD by the CPA. There was sufficient evidence of remission with first- or third-line agents to pool reported rates, and with agents from all 3 treatment lines to pool response rates and reduction in HARS scores. The mean range of effect size varied considerably from study to study within each treatment line. Comparison of pooled remission rates between first- and second-line agents was not possible. While the range of values by drug and drug class overlapped, the summary results for the probability of response and reduction in HARS scores was greater for first-line, compared with second-line, treatments. Drug components for third-line treatments were heterogeneous and produced mixed results. CONCLUSION: Despite the abundance of evidence in its totality presented in the CPA guidelines, there is inadequate evidence to formulate recommendations based on the pooled results from this study alone. However, such analysis provides an additional resource for clinicians to make more effective treatment decisions for individual patients with GAD.
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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 | 0.015 | 0.083 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.011 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".