Views of female breast cancer patients who donated biologic samples regarding storage and use of samples for genetic research
Bibliographic record
Abstract
Although social and ethical issues related to the storage and use of biologic specimens for genetic research have been discussed extensively in the medical literature, few empiric data exist describing patients' views. This qualitative study explored the views of 26 female breast cancer patients who had consented to donate blood or tissue samples for breast cancer research. Participants generally did not expect personal benefits from research and had few unprompted concerns. Few participants had concerns about use of samples for studies not planned at the time of consent. Some participants did express concerns about insurance or employment discrimination, while others believed that current privacy protections might actually slow breast cancer research. Participants were generally more interested in receiving individual genetic test results from research studies than aggregate results. Most participants did not want individual results of uncertain clinical significance, although others believed that they should be able to receive such information. These data examined the range of participants' views regarding the storage and use of biologic samples. Further research with different and diverse patient populations is critical to establishing an appropriate balance between protecting the rights of human subjects in genetic research and allowing research to progress.
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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 | 0.016 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".