Characterising treatment pathways for natural menopausal symptoms in UK women
Bibliographic record
Abstract
Objectives: Treatments for menopause symptoms include hormone therapy (HT) and nonhormonal treatments (non-HTs); clonidine is the only UK-approved non-HT for vasomotor symptoms (VMS). Real-world data on medication use are limited. This study described treatment pathways for menopause symptoms in UK women. Methods: This retrospective cohort study was conducted with Clinical Practice Research Datalink Aurum (01/2009-03/2021). Treatment pathways for menopause symptoms followed by >30 women were assessed in women aged 40-65 after first diagnosis of natural menopause. Gaps of <30 days between prescriptions indicated a combination of treatments; ≥30 days, a switch. Sensitivity analyses with increased gaps (60, 90, 180 days) were conducted. Results: The study included 214,374 women (57.2% aged 50-59). 79,826 (37.2%) followed a treatment pathway consisting of >30 women. Of these, 55,761 (69.9%) had only one treatment line; most prescribed were estrogens alone (19.9%), combined progestogens+estrogens (9.1%), amitriptyline (8.6%), sertraline (6.1%), and citalopram (5.5%). Two or more treatment lines were reported in 24,065 (30.1%); first-line estrogens and second-line progestogens+estrogens (3.5%) was the most common pathway, followed by switches from estrogens to amitriptyline (1.1%) or sertraline (1.0%). Across all treatment pathways, amitriptyline was the most prescribed non-HT (15.8%), with fewer clonidine prescriptions (7.3%). Sensitivity analyses yielded similar results.
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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 | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".