Practice patterns and predictors of treatment intensification in patients with metastatic castration-sensitive prostate cancer
Bibliographic record
Abstract
INTRODUCTION: Treatment intensification beyond androgen deprivation therapy (ADT) has shown survival benefit in patients with metastatic castration-sensitive prostate cancer (mCSPC). There is a need to better understand how these novel treatments fit in real-world practice. METHODS: Using electronic medical records and administrative data, a population-based, retrospective cohort study of patients diagnosed with de novo mCSPC between 2010 and 2020 in Alberta, Canada, and initiated on ADT was conducted. Treatment intensification was defined as the receipt of apalutamide, abiraterone acetate, enzalutamide, or chemotherapy (e.g., docetaxel) within 180 days of ADT initiation. RESULTS: A total of 2515 de novo mCSPC were identified, with 2098 (83%) patients initiating ADT post-diagnosis. Of those, 525 (25%) received intensification beyond ADT. Three percent of patients were intensified in 2010-2013; this increased to 67% in 2020. From 2014-2017, docetaxel was the most used approach, although it was supplanted by abiraterone acetate, apalutamide, and enzalutamide from 2018 onwards. In multivariable logistic regression analyses of patients diagnosed from 2014-2020, significant predictors of intensification were younger age at diagnosis, lower Charlson comorbidity index, greater number of metastatic sites, shorter time to ADT initiation, referral to a medical oncologist, transurethral resection of the prostate or radiation prior to ADT, and more recent year of diagnosis (all p<0.05). CONCLUSIONS: There has been a considerable increase in the use of ADT intensification therapies that correspond with the timing of clinical trial data and approvals of novel agents.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".