Uterine fibroids with heavy menstrual bleeding stratified by race in a commercial and Medicaid database
Bibliographic record
Abstract
Background: Historically, the clinical characteristics and treatment pathways for patients with uterine fibroids and heavy menstrual bleeding have differed between White and Black women. Objective: To provide a contemporary comparison of patient characteristics and treatment patterns among White and Black women with uterine fibroids and heavy menstrual bleeding in the United States. Study Design: This retrospective cohort study included administrative claims data from 46,139 White and 17,297 Black women with uterine fibroids and heavy menstrual bleeding from the Optum Clinformatics database (January 2011-December 2020) and 7353 White and 16,776 Black women from the IBM MarketScan Multi-State Medicaid Insurance database (January 2010-December 2019). Patients were indexed at their initial uterine fibroid diagnosis claim and were required to have a claim for heavy menstrual bleeding and ≥12 months of continuous enrollment pre- and postindex. Patients were followed until the earliest of death, disenrollment, hysterectomy date, or end of study database. Outcomes were stratified by race and included patient demographics, clinical characteristics, pharmacologic treatment patterns, and surgeries/procedures. Pearson's Chi-square test for categorical variables and Student's t-test for continuous data were used to evaluate differences in baseline characteristics. Descriptive statistics were used to characterize treatment pathways for hormonal contraceptive use in women with ≥24 months of follow-up. Kaplan-Meier survival analysis was used to estimate time until hysterectomy, with log-rank testing to assess between-group differences. Results: <.0001). Approximately 40% of all patients received hormonal drug therapies as initial treatment, most commonly hormonal contraceptives. However, discontinuation of hormonal contraceptive therapy was nearly universal, with one-half discontinuing within a median treatment duration of ∼5 months. Most women stopped treatment after 1 or 2 agents (commercial: White, 89.9% [9757/10,857]; Black, 90.0% [3594/3993]; Medicaid: White, 92.2% [1635/1773]; Black, 94.2% [4454/4726]). Hysterectomy was the most common procedure, and was more common among White vs Black women (commercial: 43.9% [20,235/46,139] vs 37.8% [6536/17,297]; Medicaid: 46.8% [3444/7353] vs 32.0% [5364/16,776]). Conclusions: Black women with UF-HMB were diagnosed at a younger age than White women, and White women had higher hysterectomy rates than Black women, representing a shift from earlier researched treatment patterns. Patients with UF-HMB were also highly reliant on hormonal contraceptives, followed by nearly universal therapeutic discontinuation.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".