Patient-Reported Satisfaction Following Radiation of Implant-Based Breast Reconstruction
Bibliographic record
Abstract
Background: Little is known with regard to patient-reported outcomes (PROs) in the setting of implant-based reconstruction (IBR) with post-mastectomy radiation therapy (PMRT). Methods: We identified patients who underwent immediate IBR from a prospectively compiled database. The Breast Reconstruction Satisfaction Questionnaire (BRECON-31) was scored and compared between patients with and without PMRT. Results: Sixty-four women met the study criteria. Forty-eight did not receive PMRT and 16 did. Nine women had an unanticipated indication for PMRT. The PMRT group was similar to the control group with regard to baseline characteristics (ie, age, marital status, body mass index, tobacco use, and comorbidities). However, treatment and oncologic characteristics (eg, diagnosis, tumour characteristics, systemic therapy use) differed. Of all complications, only capsular contracture rates differed (1.2% vs 13%; P = .01). Of the 9 subscales, 7 showed no difference in satisfaction between the groups. Radiated women scored lower in the arm concerns and breast appearance subscales. Scores were similar whether the indication for PMRT had been anticipated or not. Discussion: Women with immediate IBR scored similarly to their nonradiated counterparts across 7 of 9 domains of satisfaction. Arm concerns and breast appearance scores are lower with PMRT, likely secondarily to more extensive nodal procedures in higher stage patients and to the side effect profile of radiotherapy. Our findings are in line with the few available studies using other PRO tools to evaluate the impact of PMRT on patient satisfaction and studies objectively measuring the effect of PMRT on arm morbidity and cosmetic outcomes.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.003 | 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".