Trajectory of End-of-Life Pain and Other Physical Symptoms among Cancer Patients Receiving Home Care
Bibliographic record
Abstract
PURPOSE: To describe the trajectory of physical symptoms among cancer decedents who were receiving home care in the six months before death. PATIENTS AND METHODS: An observational cohort study of cancer decedents in Ontario, Canada, who received home care services between 2007 and 2014. To be included, decedents had to use at least one home care service in the last six months of life. Outcomes were the presence of pain and several other physical symptoms at each week before death. RESULTS: Our cohort included 27,295 cancer decedents (30,368 assessments). Forty-seven percent were female and 56% were age 75 years or older. The prevalence of all physical symptoms increased as one approached death, particularly in the last month of life. In the last weeks of life, 69% of patients reported having moderate-severe pain; however, only 20% reported that the pain was not controlled. Loss of appetite (63%), shortness of breath (59%), high health instability (50%), and self-reported poor health (44%) were also highly prevalent in the last week of life. Multivariate regression showed that caregiver distress, high health instability, social decline, uncontrolled pain, and signs of depression all worsened the odds of having a physical symptom in the last 3 months of life. CONCLUSION: In this large home care cancer cohort, trajectories of physical symptoms worsened close to death. While presence of moderate-severe pain was common, it was also reported as mostly controlled. Covariates, such as caregiver distress and social decline, were associated with having more physical symptoms at end of life.
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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 | 0.002 |
| 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 | 0.000 |
| 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".