Dose-modified abiraterone acetate (AA) in men with metastatic castration-resistant prostate cancer (mCRPC): The Princess Margaret Cancer Centre (PM) experience.
Bibliographic record
Abstract
61 Background: AA prolongs survival in mCRPC and is used pre- and post-chemotherapy. In the phase I trial, AA showed anti-tumor activity at 250 or 500 mg daily (‘low doses’). In addition, pharmacokinetic analysis showed that when AA was administered with a high-fat meal vs the fasting state, drug exposure was increased by 4.4-fold [ Attard G et al. Phase I clinical trial of a selective inhibitor of CYP17, abiraterone acetate, confirms that castration-resistant prostate cancer commonly remains hormone driven. J Clin Oncol 2008; 26: 4563-4571.]. Based on this, at our cancer centre low-dose AA is sometimes prescribed with high-fat meals to men who otherwise cannot access the drug due to funding constraints, particularly in the pre-chemotherapy setting. Our aim was to study the association between AA dose, PSA response and progression-free survival (PFS). Methods: All men receiving AA at PM (Nov2009-Mar2013) were reviewed retrospectively. PSA response rate (PSA-RR) was defined according to PCWG2 criteria as a confirmed decrease ≥50% in PSA. PFS was defined from start of AA to PSA progression, clinical progression, drug cessation or death. Associations between dose, PSA-RR and PFS were assessed using chi-square and logrank tests, respectively, for all patients and for the sub-group of chemo-naive patients. Results: 109 men were treated with AA, 89 at a full dose of 1000 mg in the fasting state, 20 at low doses with high-fat meals. There was no significant difference in PFS between the two dose levels for all men. PSA-RR was non-significantly lower in chemo-naive men treated with low doses compared to full dose (p=0.09; table). Conclusions: Administration of low dose AA with high-fat meals is not associated with shorter PFS despite a trend to lower PSA-RR. These results are clinically relevant in resource-limited settings and warrant further prospective clinical research. [Table: see text]
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".