Physicians’ Opinion on Intraoperative Radiotherapy as a Therapeutic De-Escalation Option in Older Women with Early Breast Cancer
Bibliographic record
Abstract
BACKGROUND: Intraoperative radiotherapy (IORT) is a therapeutic de-escalation option in older women with low-risk early breast cancer (EBC). A qualitative study was implemented to describe EBC physicians' points of view on IORT as a de-escalation option. METHODS: Recorded face-to-face and telephone semi-structured interviews were conducted among diverse physicians from seven French comprehensive cancer centers. Interview transcripts were grouped as corpus to construct a typology. Thematic analysis was performed. RESULTS: Positions toward IORT were contrasted between the 16 participating physicians. Five fully supported IORT as a de-escalation option, four were not in favor, and seven had a more reserved or neutral opinion. Points of divergence concerned treatment efficacy, treatment duration, side effects and sequelae, psychological impact, compliance with adjuvant endocrine therapy, logistical constraints, financial cost, and availability of other techniques of partial breast irradiation. Physicians in favor of IORT emphasized direct benefits for the patient, and those against pointed the lack of specific guidelines, risk of lost opportunity in older women with long life expectancy, and challenges of shared decision making. CONCLUSIONS: Despite national policies to preserve cancer patients' quality of life and increase their participation in medical decision making, therapeutic de-escalation using IORT is not consensual among physicians. Further efforts are needed to promote patient-centered care.
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".