Real world evidence: Abiraterone use post-docetaxel in metastatic castrate-resistant prostate cancer
Bibliographic record
Abstract
OBJECTIVES: The COU-AA-301 trial demonstrated that in men with metastatic castrate-resistant prostate cancer using abiraterone post-docetaxel increased overall survival. This study aims to assess this conclusion in a real world context. DESIGN: Retrospective chart review of a provincial Pharmacy BDM Database (a pharmacy dispensing software) and a provincial Electronic Chart (ARIA). Dispensing data, information on the state of the disease before and after abiraterone use, and information regarding effects of abiraterone were gathered. SETTING: Cancer centers in Alberta, Canada. PATIENTS: Metastatic castrate-resistant prostate cancer (CRPC) patients on abiraterone outside of a clinical trial who have previously had docetaxel chemotherapy for CRPC between February 2012 and May 2014. PRIMARY OUTCOME: Overall survival from the time of abiraterone initiation. RESULTS: Overall survival increase of 17 months was consistent with the survival increase of 14.8 months observed in the pivotal trial. CONCLUSION: Abiraterone is a valuable therapy post-docetaxel for metastatic CRPC, as in a real world context it demonstrated an increase in overall survival that was consistent with the findings of the clinical trial despite including a patient population of older age and lower performance status.
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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 | 0.016 | 0.087 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".