Real-World Use of Androgen-Deprivation Therapy: Intensification Among Older Canadian Men With de Novo Metastatic Prostate Cancer
Bibliographic record
Abstract
Background: Despite the wealth of evidence demonstrating the efficacy of treatment intensification beyond androgen-deprivation therapy (ADT) among patients with de novo metastatic castration-sensitive prostate cancer (mCSPC), little is known of its real-world use. This study examined the real-world uptake of ADT treatment intensification among older men in a large Canadian province. Methods: We performed a retrospective population-based cohort study using province-wide linked administrative data in Ontario, Canada. Patients 66 years of age and older with de novo mCSPC were included and their treatment with conventional ADT-based regimens, ADT plus next-generation androgen receptor axis-targeted therapy, and ADT plus docetaxel were identified and stratified by time. Results: From 2014 to 2019, 3556 patients were identified with de novo mCSPC. Most patients (n = 2794 [78.6%]) were treated with a conventional ADT regimen, whereas 399 (11.2%) patients received ADT intensification with docetaxel and 52 (1.5%) patients received abiraterone acetate plus prednisone. In a time-stratified analysis of ADT intensification before and after the pivotal AA+P trial (LATITUDE), AA+P uptake increased from 0.5% to 3.0%, whereas docetaxel use dropped from 12.0% to 10.0%. The median survival of the study population was 18 months (interquartile range = 10-31). Conclusions: The majority of patients with de novo mCSPC are treated with ADT alone in the Canadian real-world setting, despite randomized clinical trial evidence of benefit with the use of ADT-intensified regimens. As ADT treatment intensification is substantially underused, better understanding of the barriers to treatment and targeted education to address them are needed.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 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".