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Record W3088950237 · doi:10.1089/jwh.2019.8096

A Clinician's Guide to the Treatment of Endometriosis with Elagolix

2020· review· en· W3088950237 on OpenAlexaff
Nicholas Leyland, Stephanie J. Estes, Bruce A. Lessey, Arnold P. Advincula, Hugh S. Taylor

Bibliographic record

VenueJournal of Women s Health · 2020
Typereview
Languageen
FieldMedicine
TopicEndometriosis Research and Treatment
Canadian institutionsMcMaster University
FundersNational Center for Advancing Translational Sciences
KeywordsEndometriosisMedicinePelvic painQuality of life (healthcare)DosingInternal medicineSurgery

Abstract

fetched live from OpenAlex

Pain associated with endometriosis is a considerable burden for women, permeating all aspects of their lives, from their ability to perform daily activities to their quality of life. Although there are many options for endometriosis-associated pain management, they are often limited by insufficient efficacy, inconvenient routes of administration, and/or intolerable side effects. Elagolix, a nonpeptide, small-molecule gonadotropin-releasing hormone (GnRH) receptor antagonist, is the first new oral therapy to be approved for the treatment of endometriosis-associated pain in the United States in more than a decade. Modulation of estradiol with elagolix is dose dependent and ranges from partial to full suppression. Clinical evidence has shown that elagolix at both approved doses (150 mg once daily and 200 mg twice daily) is effective for reducing symptoms of pelvic pain (dysmenorrhea, nonmenstrual pelvic pain, and dyspareunia), improving quality of life, and decreasing use of rescue analgesics (nonsteroidal anti-inflammatory drugs and/or opioids). The availability of two dosing options allows for individualization of treatment based on baseline clinical factors and response to therapy. Elagolix is well tolerated, with less pronounced hypoestrogenic effects compared with GnRH agonists. This review provides an overview of elagolix, highlighting currently available treatment options and the application of this new treatment for women with endometriosis-associated pain.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.985
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.089
GPT teacher head0.469
Teacher spread0.380 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreReview

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".

Quick stats

Citations33
Published2020
Admission routes1
Has abstractyes

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