Use of dienogest in endometriosis. A narrative literature review and expert commentary
Bibliographic record
Abstract
Objective: Endometriosis affects up to 10% of women of reproductive age, and the main goal of treatment is to relieve symptoms. Progestins have been the mainstay of endometriosis suppression, of which dienogest has become an important option in many parts of the world. This is an expert literature review, with recommendations on the use of dienogest in the context of various clinical considerations when treating endometriosis.Methods: A search of PubMed was conducted for papers published between 2007 and 2019 on the use of dienogest in endometriosis. Experts reviewed these and included those they considered most relevant in clinical practice, according to their own clinical experience.Results: Evidence regarding the long-term use (>15 months) of dienogest for the management of endometriosis is presented, with experts concluding that the efficacy of dienogest should be assessed primarily on its impact on pain and quality of life. Fertility preservation, the option to avoid or delay surgery, and managing bleeding irregularities that can occur with this treatment are also considered. Counseling women on potential bleeding risks before starting treatment may be helpful, and evidence suggests that few women discontinue treatment for this reason, with the benefits of treatment outweighing any impact of bleeding irregularities.Conclusions: Overall, the evidence demonstrates that dienogest offers an effective and tolerable alternative or adjunct to surgery and provides many advantages over combined hormonal contraceptives for the treatment of endometriosis. It is important that treatment guidelines are followed and care is tailored to the woman’s individual needs and desires.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".