Dying with breast cancer: An audit
Bibliographic record
Abstract
8154 Background: Most patients dying of metastatic breast cancer (MBC) would prefer to die at home if possible. Unfortunately, significant discordance exists between preferred & actual location of death, with less than 30% of pts dying at home. The low incidence of home death is associated with a low rate of palliative care referral & a high rate of specialist care at the end of life. At our centre coordination of palliative care & supportive care services is facilitated by a dedicated social work (SW) team. The purpose of our study was to review the management of end of life care of MBC pts to determine if it was consistent with their wishes & to identify areas of improvement. Methods: Pts with MBC who died under the care of one oncology team between October 2001 & October 2004 were identified. Pt demographics, place of death, & expressed preference for place of death were recorded. Health care professionals involved with each pt were interviewed. Results: 63 pts died during the audit period. Mean age was 60 yrs (30–92 range). Median time with metastatic disease was 25 months (range 1 week-125 months). 82% had end of life discussions with the oncologist, & this took place a median of 75 days before death (range 2–983 days). While 71% of pts expressed that they wished to die at home, only 33% actually did. 26% died in a palliative care unit, & 40% died in an acute care setting. 85% of pts were seen by SW prior to death. Health care professionals felt earlier referral to SW & earlier discussion of palliative care services may help meet pts needs. Conclusions: Despite the presence of a coordinating supportive care team, there remains a significant discordance between pt wishes & actual place of death. From clinical experience, while many acute hospital admissions at the end of life occur due to poor coordination of palliative resources or primary care-giver distress, earlier referral to SW may help in the coordination of resources to improve pt management. No significant financial relationships to disclose.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".