Use of Palliative Chemotherapy for Advanced Bladder Cancer: Patterns of Care in Routine Clinical Practice
Bibliographic record
Abstract
BACKGROUND: Palliative chemotherapy for advanced bladder cancer is recommended in clinical practice guidelines. Patterns of care in routine clinical practice have not been well described. This article describes use rates of chemotherapy and referral rates to medical oncology in the last year of life among patients who have died of bladder cancer. METHODS: A population-based cohort of patients with bladder cancer was identified from the Ontario Cancer Registry; the study population included patients who died of bladder cancer between 1995 and 2009. Electronic records of treatment and physician billing records were used to identify treatment patterns and referral to medical oncology. Log-binomial and modified Poisson regression were used to examine factors associated with chemotherapy use and medical oncology consultation. RESULTS: A total of 8,005 patients died of bladder cancer, 25% (n=1,964) of whom received chemotherapy in the last year of life. Use was independently associated with patient age, comorbidities, socioeconomic status, sex, time period, and treatment region. A total of 68% (n=5,426) of patients were seen by a medical oncologist. Referral to medical oncology was associated with age, comorbidities, year of death. Geographic variation was seen with chemotherapy use-from 18% to 30%-that persisted on adjusted analysis. CONCLUSIONS: The efficacy of palliative chemotherapy demonstrated in clinical trials and recommended in guidelines has not translated into widespread use in practice. Understanding the extent to which patient preferences and health system factors influence use is needed. Access to acceptable palliative systemic treatments remains an unmet need for most patients dying of bladder 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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".