Outcomes of Surveillance for Contralateral Breast Cancer in Patients Less than Age 60 at the Time of Initial Diagnosis
Bibliographic record
Abstract
BACKGROUND: After an initial diagnosis of breast cancer, the risk of contralateral breast cancer is approximately 0.5% per year. Annual mammography is recommended to identify local recurrences and contralateral new primaries. Because the sensitivity of mammography tends to be lower in younger women, we conducted a retrospective review of the method of detection and pathologic stage of metachronous contralateral primary breast cancers according to age at diagnosis in a cohort of breast cancer patients. METHODS: The Henrietta Banting Database contains information on cases of breast cancer diagnosed at Women's College Hospital from 1987 to 2004. From among 1992 women in the database, 71 patients were identified who were initially diagnosed before age 60 and who subsequently developed a contralateral breast cancer. Medical records were obtained for 53 of the 71 patients. RESULTS: Of the 53 contralateral cancers, 33 (62%) were detected by mammography, including 4 in 16 patients (25%) diagnosed before age 50 and 29 in 37 patients (78%) diagnosed at age 50 or older (p ≤ 0.001). CONCLUSIONS: Mammography has poor sensitivity for the surveillance of contralateral breast cancer in early-onset breast cancer patients. Other imaging modalities should be evaluated in this setting.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".