Variation in Access to Palliative Radiotherapy in Prostate Cancer: A Population-Based Study in Canada
Bibliographic record
Abstract
BACKGROUND: As a result of improvements in cancer therapies, patients with metastatic malignancies are living longer, and the role of palliative radiotherapy has become increasingly recognized. However, access to adequate palliative radiotherapy may continue to be a challenge, as is evident from the high proportion of patients dying of prostate cancer who never receive palliative radiotherapy. The main objective of this investigation is to identify and describe the factors associated with the receipt of palliative radiation treatment in a decedent cohort of prostate cancer patients in Ontario. METHODOLOGY: Population-based administrative databases from Ontario, Canada, were used to identify prostate cancer decedents, 65 years or older who received androgen deprivation therapy between January 1, 2013, and December 31, 2018. Baseline and treatment characteristics were analyzed using univariate and multivariate logistic regression models for association with receipt of radiotherapy in a two-year observation period before death. RESULTS: We identified 3,788 prostate cancer decedents between 2013 and 2018; among these, 49.9% received radiotherapy in the two years preceding death. There were statistically significant positive associations between receipt of radiotherapy and younger age at diagnosis (odds ratio [OR] 1.6, 95% confidence interval [CI] 1.1-2.3); higher stage at diagnosis (OR 1.3, 95% CI 1.1-1.7); receipt of care at a regional cancer center (OR 1.8, 95% CI 1.3-2.4); and involvement of radiation oncologists (OR 155.1, 95% CI 83.3-288.7) or medical oncologists (OR 1.4, 95% CI 1.1-1.8). However, there were no associations between receipt of radiotherapy and income, distance to the nearest cancer center, involvement of urologists in cancer care, healthcare administrative region, home-care involvement, or number of hospitalizations in the observation period. CONCLUSIONS: We found the utilization of palliative radiotherapy for prostate cancer patients in Ontario varies depending on age, stage at diagnosis, number of comorbidities, registration at regional cancer centers, and involvement of oncologists. There were no differences detected based on income or distance from a cancer center. The findings of this study represent an important opportunity to facilitate better access to palliative radiotherapy and referrals to multidisciplinary regional cancer centers, to improve the quality of life of this patient 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".