Uterine fibroids — why you should choose tailored therapies based on the joint decision of the physician and the patient
Bibliographic record
Abstract
Uterine fibroids (UFs) are the most common benign tumors of the myometrium, affecting up to 70% women by age 50. Although many cases remain asymptomatic, symptomatic UFs can significantly reduce quality of life through excessive bleeding, anemia, pelvic pain, infertility, and obstetric complications. Despite the availability of various conservative treatments - including pharmacotherapy, uterine artery embolization, and ultrasound thermoablation - surgical interventions, particularly hysterectomy, remain the dominant approach in many countries. This discrepancy between evidence-based recommendations and routine practice highlights the persistence of a paternalistic model of care, where patients are often excluded from treatment decisions and not informed about alternatives. Emerging concepts such as shared decision making (SDM) and personalized therapy emphasize the need to adapt treatment plans to each woman's clinical profile, reproductive goals, and preferences. SDM fosters trust, better adherence to therapy, and improved acceptance of complications by actively involving patients in choosing their care. The development of modern pharmacological options, like GnRH analogs, further expands possibilities for effective, reversible, fertility-preserving treatments. A paradigm shift toward patient-centered, individualized management is essential to address ethical challenges, reduce unnecessary hysterectomies, and improve outcomes. Implementing SDM and expanding access to conservative therapies require systemic changes in reimbursement, training, and patient education to ensure that care focuses not only on the disease but on the woman as a whole.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 teacher head, 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".