Continuation of postmenopausal hormone replacement therapy: comparison of cyclic versus continuous combined schedules
Bibliographic record
Abstract
Discontinuation of hormone replacement therapy (HRT) is much more common than what is reported in randomized, double-blind clinical trials. Our purpose in this retrospective study, using a prescription database, was to compare the continuation rate among women who took cyclic combination therapy adding progesterone to estrogen (CYC-PERT) or continuous combined estrogen progestin therapy (CC-PERT). The study subjects were 1,532 women, ≥45 years old, who initially filled index prescriptions for 0.625 mg conjugated estrogens. They were divided into two groups (CYC-PERT = 644, CC-PERT = 888) on the basis of coprescribed medroxyprogesterone. We found that for all women initiating therapy, 35-40% did not return for a refill and 76-81% stopped therapy within 3 years. Those prescribed CC-PERT initially were more likely to stop than those prescribed CYC-PERT (rate ratio [RR] = 1.20; 95% confidence interval [CI] = 1.06-1.35). Adjustments for age, year of starting medication, cost of medication, and prescriber specialty did not affect the difference in discontinuation between the two regimens (RR 1.18, 95% CI = 1.04-1.34). We conclude that the likelihood of women continuing HRT beyond 3 years of initiation is low. Furthermore, compared with CYC-PERT users, those receiving CC-PERT have a slightly higher probability of discontinuation. Efforts should be made to understand why three quarters of women beginning HRT will stop it long before it can provide major long-term benefit.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".