Goals of care designation associated with improved survival and indicators of quality end-of-life care in pancreatic cancer (PC) patients (pts) undergoing palliative chemotherapy.
Bibliographic record
Abstract
11532 Background: Discussion of goals of care (GoC) is a key part of quality care for pts with palliative cancer. Numerous studies have shown that documentation of GoC in this population remains low. Here we describe changes in GoC documentation and other indicators of quality end-of-life care in PC pts undergoing palliative chemotherapy during a health-system wide initiative to improve advanced care planning (ACP). Methods: This is a retrospective cohort analysis of 106 pts with locally advanced or metastatic PC treated with palliative chemotherapy from 2012-2015 in Northern Alberta (Canada). In 2014, an initiative was launched to provide pts with hard copies of their GoC designation intended to be available at all health-system interactions. Data were obtained from outpatient medical oncology (MO) and palliative care (PAL) notes and the provincial cancer registry. Survival analysis used a multivariate Cox-regression. All other tests were Chi-squared. Results: 50% (53/106) of pts had a documented GoC discussion, with 45% (48/106) receiving a specific GoC designation. In 2012, 31% (6/19) of pts had a GoC designation, which increased to 61% (20/33) in 2015. Of 84 individual GoC discussions documented, 34% (29/84) were by MO, 62% (52/84) were by PAL, and at least 8% (7/84) referenced prior discussions with a family physician or discussion while admitted to hospital. Pts with a GoC designation had increased median overall survival (287 vs 216 days; HR = 0.62; p = 0.041), and were less likely to receive chemotherapy in the last two weeks of life (p = 0.016). Conclusions: Rates of GoC discussions for PC pts undergoing palliative chemotherapy increased during a health-system wide ACP initiative. Having a GoC designation was associated with greater overall survival and indicators of higher quality end-of-life care.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".