Impact of palliative care (PC) consultation on quality of end-of-life (EOL) care in advanced cancer patients receiving care at a tertiary cancer center (TCC).
Bibliographic record
Abstract
129 Background: Early integration of PC with oncological care has been shown to improve outcomes in patients with advanced cancer, including quality of life and mood. It has also been suggested to have a positive impact on quality of EOL care. The purpose of our study was to examine how occurrence and timing of PC consultation are associated with quality of EOL care in advanced cancer patients receiving care at a Canadian TCC. Methods: In this retrospective study, patients who died between April 1, 2013 and March 31, 2014, had advanced cancer while receiving care at our TCC, and lived in the catchment area of our urban comprehensive integrated PC program were eligible. Date of death, demographics, and cancer type were obtained from the cancer registry. Date of diagnosis of advanced cancer was determined from electronic medical records. Occurrence and date of PC consultation were identified from the PC database. Data on quality of EOL care indicators were retrieved from the cancer registry, including, in the last 30 days of life: emergency room visits, hospital admission, hospitalization > 14 days, ICU admission, death in hospital, and chemotherapy use. Results: Of 1414 eligible patients, 1101 (77.9%) received PC consultation in hospital, outpatient clinic, or community. Patients who received PC consultation were younger than those who did not receive PC consultation (age 68.8 vs. 71.0, p = 0.01), and differed in the frequency of cancer types (p < 0.001), but not sex, marital status, or income. 679 patients (48.0%) had at least 1 indicator of quality of EOL care. Patients who did and did not receive PC consultation did not differ in the frequency of any indicators of quality of EOL care. There were also no differences in frequency of quality of EOL care indicators between patients who received their first PC consultation > 3 months vs. ≤3 months or > 6 months vs. ≤6 months before death. Conclusions: Among advanced cancer patients receiving care at our TCC, occurrence and timing of PC consultation did not affect quality of EOL care. Methodological and healthcare system differences may explain the discrepancy between our results and those of other investigators. Further research is 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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".