Study to explore the willingness of patients (pts) to undergo biopsy at the time of breast cancer (BC) recurrence.
Bibliographic record
Abstract
1102 Background: Physicians (MDs) may not request a biopsy (BX) when metastatic (M1) diagnosis is certain, however, there is increasing awareness of the value of tissue for cancer discovery. In addition, biomarkers can change from initial BC to M1 in 20%, affecting treatment. With ethics approval we investigated under what conditions BC pts would agree to a BX of recurrent cancer, to guide MD practice. Methods: Consenting English speaking pts with M1, or at least 3 months post adjuvant therapy, were asked to complete a survey (at home or with research assistant) about willingness to undergo BX at M1. Demographic and disease information was collected. The BX scenarios increased in inconvenience/discomfort and decreased in direct benefit to pt. Results: Among 204 participants, mean age was 60 (29-92), 71% were caucasian, 73% completed more than high school, 84% lived within 1 hour of the cancer centre. 87 (43%) pts had no relapse (M0) and 116 (57%) had M1 (including 20 [17%] with local relapse only, 21 [18%] de novo M1). 82 (71%) of M1 pts reported having had a BX for M1. When it required only image guidance and minimal discomfort (eg ultrasound guided liver BX), 86% of M1 pts would have a BX to join a trial and 81% would for pure research; 69% and 76% of M0 pts would have a BX to join a trial, or for research only, respectively. The Table shows the responses for the most invasive BX. Conclusions: Two thirds of BC pts would undergo the most invasive/inconvenient BX to join a trial, and half would for pure research. This demonstrates a large degree of altruism in this BC population. Willingness increased as direct benefit increased and the pain/inconvenience decreased. This data suggests MDs should not be hesitant to ask BC pts for a BX at M1. This study was limited to English speaking pts and most were well educated, thus it may not reflect all cultural attitudes toward BX. [Table: see text]
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".