Thromboembolic safety profile of low-dose estradiol (valerate) in combined hormonal preparations: Implications for the development of new hormonal endometriosis and uterine fibroid therapies
Bibliographic record
Abstract
Background: Several promising new medications containing low-dose estradiol (E2) in combination with a progestin and an additional component, such as gonadotropin-releasing hormone antagonists, are currently being developed for use in pre-menopausal women. Objective: This pooled analysis was designed to estimate the thromboembolic safety profile of E2 and its ester, estradiol valerate (E2Val), when used in combined hormonal treatments in a pre-menopausal population. Methods: Data regarding users of combined oral contraceptives (COCs) and combined menopausal hormonal therapy (MHT) containing either E2/E2Val or ethinylestradiol (EE) ⩽ 30 µg were retrieved from five large prospective, non-interventional, cohort studies in Europe, US, and Canada with similar study design but differing medication cohorts. Propensity score sub-classification was applied to balance baseline parameters between cohorts and time-to-event analysis of venous thromboembolic events (VTE) was carried out based on the extended Cox model to calculate crude and adjusted hazard ratios (HR). Results: (1) Crude incidence rates of VTE were higher in MHT users compared to pre-menopausal COC users, (2) the VTE risk in menopausal users of E2/E2Val-norethindrone acetate was not higher than that in menopausal users of E2/E2Val-progestin (adjusted HR 0.71; 95% confidence interval, 0.41-1.26) and (3) the VTE risk in pre-menopausal users of E2/E2Val-progestin was similar, or lower, than pre-menopausal users of EE⩽30µg-progestin (adjusted HR 0.49; 95% confidence interval, 0.28–0.84). Conclusion: Our data presents a solid safety assessment of combined hormonal preparations containing E2/E2Val. We conclude that the risk of E2/E2Val-norethindrone acetate in pre-menopausal users is unlikely to be higher than the known risk of COCs containing EE ⩽ 30 µg-progestin.
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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 | 0.017 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".