Prognosis, treatment benefit, and goals of care: what do oncologists discuss with patients who have terminal cancer?
Bibliographic record
Abstract
e20509 Background: Despite being a marker of quality care, documentation of advance directives among patients with terminal cancer is known to be poor. Here we describe the documentation of prognosis, treatment benefit, and goals of care (GOC) discussions in patients with advanced cancer seen in the out-patient setting at a comprehensive cancer centre. Methods: All patients who initiated palliative chemotherapy for metastatic pancreas or lung cancers during 2010-2013 at the Cancer Centre of Southeastern Ontario were identified from electronic pharmacy records. Patients treated with first-line palliative chemotherapy who had at least 4 clinic visits with medical oncology (MO) were eligible. Clinical notes from MO were reviewed to identify documentation of discussions regarding prognosis, treatment benefit, estimates of survival, and GOC. Clinical notes from palliative care (PC) were also reviewed. Differences between groups were tested using the chi-square test. Results: 222 patients were included; 80% (177/222) with lung cancer and 20% (45/222) with pancreas cancer. The mean number of MO clinic visits was 4.6. MO notes documented discussion of prognosis in 64% (142/222), palliative intent of therapy in 82% (182/222), magnitude of treatment benefit in 29% (64/222), and GOC in 4% (9/222) of patients. An estimate of survival was documented in 36% (79/222) of cases. Across MO providers there was substantial variation in frequency of discussing prognosis (range 33-90%, p < 0.001), treatment intent (range 55-100%, p < 0.001), and GOC (range 0-17%, p = 0.034). Only 41% (93/222) of patients were seen by PC; substantial MO provider variation was observed (range 27-58%, p = 0.020). Referral rates to PC did not increase over time (41 to 44%, p = 0.250). Among those patients seen by PC, GOC were documented by PC in 32% (29/93) of cases; substantial PC provider variation was observed (range 0-57%, p = 0.015). Conclusions: In this cohort of patients with an estimated life expectancy of one year or less, MO documentation of prognosis, treatment benefit, and GOC was poor. Less than half of patients were seen by PC. Initiatives to improve documentation of GOC and referral to PC are needed.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".