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Record W2616333165 · doi:10.1056/nejmoa1700089

Treatment of Endometriosis-Associated Pain with Elagolix, an Oral GnRH Antagonist

2017· article· en· W2616333165 on OpenAlexaff
Hugh S. Taylor, Linda C. Giudice, Bruce A. Lessey, Maurício Simões Abrão, Jan Kotarski, David F. Archer, Michael P. Diamond, Eric S. Surrey, Neil P. Johnson, Nelson B. Watts, John C. Gallagher, James A. Simon, Bruce R. Carr, W. Paul Dmowski, Nicholas Leyland, J.P. Rowan, W. Rachel Duan, Juki Ng, Brittany Schwefel, James W. Thomas, Rita I. Jain, Kristof Chwalisż

Bibliographic record

VenueNew England Journal of Medicine · 2017
Typearticle
Languageen
FieldMedicine
TopicEndometriosis Research and Treatment
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineEndometriosisAntagonistHormone antagonistGonadotropin-releasing hormoneGonadotropin-releasing hormone antagonistInternal medicineGynecologyHormoneLuteinizing hormoneReceptor

Abstract

fetched live from OpenAlex

BACKGROUND: Endometriosis is a chronic, estrogen-dependent condition that causes dysmenorrhea and pelvic pain. Elagolix, an oral, nonpeptide, gonadotropin-releasing hormone (GnRH) antagonist, produced partial to nearly full estrogen suppression in previous studies. METHODS: We performed two similar, double-blind, randomized, 6-month phase 3 trials (Elaris Endometriosis I and II [EM-I and EM-II]) to evaluate the effects of two doses of elagolix - 150 mg once daily (lower-dose group) and 200 mg twice daily (higher-dose group) - as compared with placebo in women with surgically diagnosed endometriosis and moderate or severe endometriosis-associated pain. The two primary efficacy end points were the proportion of women who had a clinical response with respect to dysmenorrhea and the proportion who had a clinical response with respect to nonmenstrual pelvic pain at 3 months. Each of these end points was measured as a clinically meaningful reduction in the pain score and a decreased or stable use of rescue analgesic agents, as recorded in a daily electronic diary. RESULTS: A total of 872 women underwent randomization in Elaris EM-I and 817 in Elaris EM-II; of these women, 653 (74.9%) and 632 (77.4%), respectively, completed the intervention. At 3 months, a significantly greater proportion of women who received each elagolix dose met the clinical response criteria for the two primary end points than did those who received placebo. In Elaris EM-I, the percentage of women who had a clinical response with respect to dysmenorrhea was 46.4% in the lower-dose elagolix group and 75.8% in the higher-dose elagolix group, as compared with 19.6% in the placebo group; in Elaris EM-II, the corresponding percentages were 43.4% and 72.4%, as compared with 22.7% (P<0.001 for all comparisons). In Elaris EM-I, the percentage of women who had a clinical response with respect to nonmenstrual pelvic pain was 50.4% in the lower-dose elagolix group and 54.5% in the higher-dose elagolix group, as compared with 36.5% in the placebo group (P<0.001 for all comparisons); in Elaris EM-II, the corresponding percentages were 49.8% and 57.8%, as compared with 36.5% (P=0.003 and P<0.001, respectively). The responses with respect to dysmenorrhea and nonmenstrual pelvic pain were sustained at 6 months. Women who received elagolix had higher rates of hot flushes (mostly mild or moderate), higher levels of serum lipids, and greater decreases from baseline in bone mineral density than did those who received placebo; there were no adverse endometrial findings. CONCLUSIONS: Both higher and lower doses of elagolix were effective in improving dysmenorrhea and nonmenstrual pelvic pain during a 6-month period in women with endometriosis-associated pain. The two doses of elagolix were associated with hypoestrogenic adverse effects. (Funded by AbbVie; Elaris EM-I and EM-II ClinicalTrials.gov numbers, NCT01620528 and NCT01931670 .).

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.048
GPT teacher head0.354
Teacher spread0.306 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreEmpirical

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

Citations493
Published2017
Admission routes1
Has abstractyes

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