Multicenter, Randomized, Cross-Over Clinical Trial of Venlafaxine Versus Gabapentin for the Management of Hot Flashes in Breast Cancer Survivors
Bibliographic record
Abstract
PURPOSE: Nonhormonal pharmacologic interventions are recommended for the treatment of hot flashes in breast cancer survivors. Antidepressants and gabapentin have been shown to be both effective and well tolerated; however, it is not clear which is preferred. PATIENTS AND METHODS: This was a group-sequential, open-label, randomized, cross-over trial of 4 weeks of venlafaxine (37.5 mg daily for 7 days followed by 75 mg daily for 21 days) versus gabapentin (300 mg once per day for 3 days, then 300 mg twice per day for 3 days, then 300 mg three times per day for 22 days), with patient preference as the primary outcome. Postmenopausal women with at least 14 bothersome hot flashes per week for the prior month were eligible. A 2-week baseline period and a 2-week tapering/washout time was used before the first and second treatment periods, respectively. Diaries were used to measure hot flashes and potential toxicities throughout the study. Participants completed a preference questionnaire at the end of the study. A predefined Pocock stopping rule was applied. Patient preference and hot flash and toxicity outcomes were compared between treatments. RESULTS: Sixty-six patients were randomly assigned, 56 of whom provided a preference (eight dropped out and two had no preference); 18 (32%) preferred gabapentin and 38 (68%) preferred venlafaxine (P = .01). Both agents reduced hot flash scores to a similar extent (66% reduction). Venlafaxine was associated with increased nausea, appetite loss, constipation, and reduced negative mood changes compared with gabapentin, whereas gabapentin was associated with increased dizziness and appetite compared with venlafaxine (all P < .05). CONCLUSION: Breast cancer survivors prefer venlafaxine over gabapentin for treating hot flashes.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".