Patterns of Radiotherapy Utilization for Lung Cancer Patients with Brain Metastases: A Population-based Analysis
Bibliographic record
Abstract
INTRODUCTION: Brain metastases occur in 15%-20% of lung cancer patients. Recently, studies have suggested that whole-brain radiotherapy (WBRT) may not prolong survival for a subset of patients, and is associated with significant side-effects. Furthermore, it is hypothesized that radiotherapy is often given near the end-of-life when the potential for benefit is minimal. Therefore, this study investigates how frequently radiotherapy for brain metastases is given near the end-of-life in a population-based cohort. MATERIALS AND METHODS: All lung cancer patients who received radiotherapy in British Columbia for brain metastases in 2014-2015 were identified. Patient and treatment characteristics were collected and analyzed to assess associations with death within 90 days of first radiation treatment. RESULTS: In total, 740 patients were identified, with a total of 826 courses of brain radiation. The 90-day mortality rate was 40% (n=330). Multivariable analysis demonstrated higher odds for age (odds ratio (OR) = 1.04, 95% confidence interval (CI) 1.02-1.05), Eastern Cooperative Oncology Group (ECOG) performance score of 2 or higher (OR = 1.59, 95% CI 1.09-2.31) and squamous cell carcinoma (OR = 2.10, 95% CI 1.13-3.90) and lower odds for initial systemic therapy (OR = 0.48, 95% CI 0.34-0.68), more than five fractions of radiotherapy (OR = 0.25, 95% CI 0.16-0.39) and stereotactic radiation (OR = 0.29, 95% CI 0.13-0.65). CONCLUSION: In our population-based study, WBRT is given in 86% of radiotherapy courses for brain metastases from lung cancer. Of these patients, 40% received treatment near the end-of-life. We identified several factors associated with shortened survival. Using these factors and already established prognostic tools, WBRT utilization should be decreased in the future, improving individualized treatment for patients with brain metastases from lung cancer.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".