Vilaprisan, a New Selective Progesterone Receptor Modulator in Uterine Fibroid Pharmacotherapy-Will it Really be a Breakthrough?
Bibliographic record
Abstract
BACKGROUND: Vilaprisan (VPR) is a new orally available selective progesterone receptor modulator (SPRM), with anti-proliferative activity against uterine fibroids (UFs). It definitively causes suppression of ovulation and inhibition of proliferation of endometrial, myometrial and UF cells. PURPOSE: This review aims to summarize current knowledge on VPR from all studies, including clinical trials, conducted to date and to contextualize the potential role of VPR in future medical regimens for the treatment of UFs. METHODS: We performed a literature search in PubMed US National Library of Medicine and Google Scholar databases. Both databases were extensively searched for all original and review articles/book chapters as well as congress abstracts published in English until July 2019. The use of VPR for UF therapy was identified by using the keywords: "uterine fibroids" and "vilaprisan". RESULTS: In phase I and II clinical trials, VPR was shown to be effective in ameliorating UF-related clinical symptoms, especially abnormal or excessive uterine bleeding and in shrinking UFs. The tolerability of VPR is roughly similar to that of ulipristal acetate (UPA) and it tends to be more favorable than that of GnRH-agonists. CONCLUSION: Presently, all trials examining the utility of VPR for the treatment of UF are halted; likely, due to the recently reported cases of hepato-toxicity with UPA, in addition to non reassuring toxicology results from preclinical long-term testing on rodents, carried out in parallel with late stage testing on humans. An accurate summary of robust data related to the safety of VPR is urgently needed to draw definitive conclusions on the future clinical development of this drug for UF therapy.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".