Discordance between hormone receptor profile of primary breast cancer and metastatic bone disease: should bone marrow biopsy be considered a standard of care?
Bibliographic record
Abstract
The treatment of bone metastases in breast cancer patients is based on the hormone receptor status of the primary tumour. Discordant receptor expression between primary and metastatic tumours has been reported in around 20 to 60% of cases. The present study, therefore, aimed to prospectively explore the incidence of discordant receptor status in primary and metastatic bone disease, and to evaluate the role of bone marrow biopsies for the reassessment of receptor status. Nineteen patients with known bone metastases underwent both a CT-guided bone metastasis biopsy as well as bone marrow aspirate and trephine. The estrogen receptor (ER) and progesterone receptor (PR) of these samples was assessed and compared with those of primary breast cancer. Tumor cells were found in 13 (68.4%) bone metastasis samples and in nine (47.4%) bone marrow biopsies. Discordance between the primary and metastatic samples was seen in 10 patients (52.6%). Among these, ER and PR changed from positive to negative in seven cases and from negative to positive in one case. In six cases (31.6%), malignant cells were identified in both bone metastasis and bone marrow samples from the same patient. Among these, ER and PR were concordant in 100% and 83% of cases. Given that the receptor profile of metastatic disease is assumed to be the same as the primary tumour, discordance between primary and metastatic cancer can have a significant impact on the outcome of treatment choices. Receptor discordance rates in this analysis were similar to that which has been reported in previous studies. There appeared to be good concordance between bone metastasis and bone marrow biopsies. Bone marrow biopsy may therefore be a simple, safe and well-tolerated way to obtain tissue to reassess receptor status of metastatic breast cancer, and should be considered before the more invasive bone metastasis biopsy.
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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 | 0.011 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".