Implications of Oncoplastic Breast Surgery on Radiation Boost Delivery in Localized Breast Cancer
Bibliographic record
Abstract
Background Oncoplastic partial mastectomy (OPM) is a technique utilized to improve aesthetic and survivorship outcomes in patients with localized breast cancer. This technique leads to breast tissue rearrangement, which can have an impact on target definition for boost radiotherapy (BRT). The aim of this study was to determine if the choice of surgical technique independently affected the decision to deliver a radiation boost. Materials and methods This was a retrospective study of patients treated between January 2017 and December 2018. We selected consecutive patients based on surgical procedure: 50 undergoing standard breast-conserving surgery and 50 having had an OPM. The primary outcome was average treatment effect (ATE) of surgery type on reception of BRT. Secondary outcomes included ATE of surgery type on the time to reception of radiotherapy and incidence of ipsilateral breast tumor recurrence (IBTR). The ratio of boost clinical target volume (CTV) to pathologic tumor size was also compared between the two groups. Treatment effects regression adjustment and inverse-probability weighted analysis was used to estimate ATEs for both primary and secondary outcomes. Results For the entire cohort, the median age was 64 years (range: 37-88 years). The median tumor size was 1.5 cm (range: 0.1-6.5 cm). The majority of patients were with ≤ stage IIA (78%), invasive ductal subtype (80%), negative lymphovascular space invasion (78%), negative margin (90%), and positive ER/PR (estrogen receptor/progesterone receptor) (69%). Overall, surgical technique was not associated with differences in the proportion of patients receiving BRT (ATE: 6.0% [95% CI: -4.5 to 16.0]). There were no differences in delays to radiation treatment between the two groups (ATE: 32.8 days [95% CI: -22.1 to 87.7]). With a median follow-up time of 419 days (range: 30-793 days), there were only five recurrences, with one case of IBTR in each group. There was no difference in the ratio of CTV volume to tumor size between the two groups (p=0.38). Conclusions OPM did not affect the decision to offer localized BRT following standard whole breast radiotherapy or significantly affect treatment times or radiation volumes. The decision to offer OPM should include a multi-disciplinary approach.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.002 | 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".