Is contralateral breast ultrasound worthwhile in preoperative staging of breast cancer?
Bibliographic record
Abstract
BACKGROUND: Women with invasive breast cancer are at higher risk of contralateral synchronous cancer. This study aimed at determining if contralateral breast ultrasound (CBUS) examination should be routinely performed in the preoperative evaluation of breast cancer patients. METHODS: This is a retrospective study of preoperative CBUS examinations performed between January 2012 and April 2015. The charts of patients presenting for biopsy of a Breast Imaging Reporting and Data System (BIRADS) 5 lesion and who had undergone a concomitant contralateral breast US examination were reviewed. Index tumor, lymph node status, American College of Radiology (ACR) breast density on mammogram, total scanning time, and results of CBUS were recorded. RESULTS: Of the 3007 patients who underwent breast biopsies during the study period, 360 patients met the inclusion criteria. Index mass size was 19 ± 10 mm. CBUS examination led to 76 biopsies, of which 12 were positive in 11 patients. Detection rate for mammographically occult contralateral invasive cancers was 3.1% (11/360). Contralateral lesion size was 13 ± 10 mm. Breast density was rated ACR C/D for nine women and ACR B for two. In the ACR C/D subgroup (82%), the contralateral cancer detection rate was 4.1%. Average additional scanning time spent required to perform CBUS examination was 3.1 ± 4.9 min. Patients diagnosed with contralateral invasive breast cancer underwent surgery and/or chemotherapy. The treatment strategy was changed in all 11 patients after the detection of a second primary cancer. CONCLUSION: Preoperative CBUS is effective and most beneficial with women presenting ACR C/D breast density. Given its impact on decreasing future morbidity, its routine use should be considered to improve quality healthcare for women diagnosed with breast cancer.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".