Treatment patterns of women with endometriosis in Canada
Bibliographic record
Abstract
Introduction:We aimed to characterize the treatment patterns of women with a self-reported diagnosis of endometriosis in Canada.Methods:Between December 2018 and January 2019 an online cross-sectional survey was administered to women aged 18 to 49 who were members of the Survey Sampling International and two partner panels in Canada. The survey included a prevalence screener and an endometriosis-focused section. Self-reported treatment patterns among women reporting endometriosis diagnosis were analyzed descriptively.Results:Of 30,000 survey respondents, 2004 reported an endometriosis diagnosis (prevalence after weighting of 7%). Treatment status reported by these women was: 34.2% currently treated, 35.9% with prior but no current treatment, and 27.1% never treated. Among women with prior or current treatment, over-the-counter (OTC) medications, contraceptive pills/patches, and surgical procedures were used by 42.0%, 37.1%, and 26.4%, respectively, prior to diagnosis and by 39.9%, 33.0%, and 43.5%, respectively, following diagnosis. First treatments for endometriosis most commonly reported were OTC medications (28.9%) and surgical procedures (21.6%). Second treatments were reported by 46.5% of women, with surgical procedures (26.1%) being the most frequently reported. The most commonly reported endometriosis-associated surgeries were surgical ablation/excision (37.4%).Conclusion:A relevant proportion of women with endometriosis in Canada have multiple therapies with medical management as a first line followed by surgical options. These results emphasize the need to identify more effective and specific endometriosis treatment options and novel strategies.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".