Palliative radiotherapy utilization for cancer patients at end of life in British Columbia: retrospective cohort study
Bibliographic record
Abstract
BACKGROUND: The use of palliative radiotherapy (PRT) is variable in advanced cancer. Little is known about PRT utilization by end-of-life (EOL) cancer patients in Canada. This study examined the PRT utilization rates and factors associated with its use in a cohort of cancer patients who died in British Columbia (BC). METHODS: BC residents with invasive cancer who died between April 1, 2010 and March 31, 2011 were included in the study. Their cancer registry and radiotherapy treatment records were extracted from the BC Cancer Agency information systems and linked for the analysis. The PRT utilization rates by age, sex, primary cancer diagnosis, geographic region, survival time and travel time to the cancer centre were examined. Multivariable logistic regression was used to determine the factors that influenced the PRT utilization rates. RESULTS: Of the 12,300 decedents in the study 2,669 (21.7%) had received at least one course of PRT in their last year of life. The utilization rates dropped to 5.0% and 2.2% in the last 30 and 14 days of life, respectively. PRT utilization varied across diagnosis and was highest for lung cancer (45.7%) and lowest for colorectal cancer (8.9%). The rates also varied by age, survival time and travel time to the nearest radiotherapy centre. There was a greater odds of receiving PRT for those with primary lung cancer, survival time between 1.5-26 months from diagnosis or living within 2 hours from a cancer centre. The 85+ age group was least likely to receive PRT in their last year of life. CONCLUSIONS: This study found PRT utilization rates of EOL cancer decedents to be variable across the province of BC. Age, diagnosis, survival time and travel time to the nearest radiotherapy centre were found to influence the odds of PRT treatment. Further work is still needed to establish the appropriate PRT utilization rates for the EOL cancer population.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".