The Breast Cancer Hormone Receptor Retesting Controversy in Newfoundland and Labrador, Canada: Lessons for the Health System
Bibliographic record
Abstract
The treatment of newly diagnosed breast cancer patients with hormonal treatment is determined by the presence of estrogen receptor and progesterone receptor status in breast cancer. In Newfoundland and Labrador (NL), 425 of 1088 (39.1%) patients who had original "negative" receptor tests conducted between 1997 and 2005, had positive results upon retesting in a specialized laboratory. This commentary addresses (1) the diagnostic utility of estrogen and progesterone testing for breast cancer in general, (2) specific testing problems that occurred in NL, (3) scientific problems associated with retesting, and (4) the impact on public trust and the resulting legal and political responses that occurred as a result of the adverse events associated with false-negative hormone receptor tests. Finally, the lessons learned will be discussed including known high false-negative rates associated with the tests and the bias associated with retesting, the need for quality assurance and national standards, public education, and appropriate communication with patients and the public.
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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 | 0.027 | 0.062 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.020 | 0.022 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.020 | 0.019 |
| Insufficient payload (model declined to judge) | 0.004 | 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".