Comparative efficacy and safety of estradiol transdermal preparations for the treatment of vasomotor symptoms in postmenopausal women
Bibliographic record
Abstract
OBJECTIVE: Divigel and Estrogel are estradiol gels for the treatment of postmenopausal women with moderate to severe vasomotor symptoms. They differ with respect to several factors including estradiol concentration and surface application, and cannot be compared solely on the basis of their estradiol dose. No randomized clinical trials have compared them head to head, but both have been compared with placebo. Therefore, the objective of this study was to conduct a systematic review and network meta-analysis of the two estradiol gels. METHODS: We performed a comprehensive systematic literature review. One publication reporting on one Divigel trial, three publications reporting on two Estrogel trials, and five publications reporting on other estradiol transdermal preparations were identified. Efficacy outcomes were change from baseline in daily hot flush frequency and change from baseline in daily hot flush severity. Safety outcomes were frequency of treatment-related adverse events (AEs) and frequency of treatment-emergent AEs leading to discontinuation. Bayesian indirect treatment comparison meta-analysis of trial-level data was performed in accordance with the International Society for Pharmacoeconomics and Outcomes Research, Academy of Managed Care Pharmacy, National Pharmaceutical Council (ISPOR-AMCP-NPC) Good Practice Questionnaire. All outcomes were compared with respect to doses of the considered preparations. RESULTS: For hot flush frequency, Divigel 0.25 mg was similar to Divigel 0.5 mg and to Estrogel 0.75 mg, and was statistically significantly superior to Estrogel 1.5 mg. The largest effect was observed with Divigel 1.0 mg (mean difference of 3.91 hot flushes/wk vs placebo), and was statistically significantly superior to all other interventions. The 1.5 mg Estrogel dose was associated with the smallest estimate of efficacy. For hot flush severity, Divigel 0.25 mg was similar to the efficacy of Divigel 0.5 mg, and for 0.25 mg and 0.5 mg of other estradiol gels, but was statistically inferior to Divigel 1.0 mg, Estrogel 0.75 mg, Estrogel 1.5 mg, and the 1.0 and 1.5 mg doses of all other estradiol gels. The estimated efficacy of Divigel 0.5 mg was similar to that of Estrogel 0.75 mg, Estrogel 1.5 mg, and the 0.25 and 0.5 mg doses of other transdermal estradiol preparations. Risks of treatment-related AEs for Divigel 0.25 mg, Divigel 0.5 mg, Estrogel 0.75 mg, and Estrogel 1.5 mg were similar and all were of a slightly higher risk than placebo. Among these, Divigel 1.0 mg, Estrogel 1.5 mg, and other gels 0.5 mg were statistically significantly less safe than placebo. However, for treatment-emergent AEs leading to discontinuation, none of the gels were associated with statistically significantly higher relative risks compared with placebo. In this study, statistically significant refers to the 95% credible intervals used in the Bayesian Network Analysis. CONCLUSIONS: Using network meta-analysis for indirect treatment comparison, we have shown that the efficacy of Divigel 0.25 mg, as measured by reduced hot flush frequency and severity, was similar to that of Divigel 0.5 mg and of Estrogel 0.75 and 1.5 mg. Overall, our analysis showed that Divigel 1.0 mg provided the best efficacy profile, but that this treatment was also associated with a higher risk of AEs. The network meta-analysis also showed that treatment with Estrogel 1.5 mg was associated with the smallest estimate of reduction in frequency of hot flushes.
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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 | 0.014 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.014 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".