Capturing longer term surgical outcome measures as part of routine care of breast cancer patients
Bibliographic record
Abstract
INTRODUCTION: The transition away from routine clinical follow up after breast cancer towards imaging surveillance and patient-initiated contact limits opportunities for patients and doctors to communicate about the long-term effects of treatment. The ABS oncoplastic guidelines (2021) recommend that post-operative 2D images and patient-reported outcomes (PROMs) are routinely collected but give no guidance as to how best to implement this. METHODS: From December 2019 until March 2024, women due for their year 3 or 5 surveillance mammogram at The Royal Marsden Sutton site were invited to complete a BREAST-Q questionnaire and attend medical photography. Panel assessment of photographs was undertaken. Results were presented to the oncoplastic MDT, including summary PROMs and illustrative case presentations. Free-text comments were shared with the relevant teams. Associations between demographic or clinic-pathological factors and uptake were investigated. RESULTS: Of the 1211 women invited, 246 patients (20.3 %) completed BREAST-Q questionnaires, 182 (15.0 %) attended for medical photography and 114 (9.4 %) completed both. Uptake was not associated with age, ethnicity or surgical factors but patients with higher BMI were less likely to respond to the questionnaire. Patients who had undergone complex oncoplastic procedures were more likely to respond than those who had simple procedures. Patient-reported outcome results were in line with the published literature. CONCLUSION: Reviewing images with their paired PROMs and discussing free-text feedback was instructive for the team. Work is needed to identify barriers to patient participation and improve uptake to be representative of the overall patient population. Quantifying appearance in photographs would help summarise aesthetic outcome data.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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".