Statin use and outcomes of patients (pts) with metastatic castration resistant prostate cancer (mCRPC) being treated with abiraterone (Abi).
Bibliographic record
Abstract
277 Background: Epidemiologic studies support an association between statin use and improved prostate cancer specific mortality. Several different biologic mechanisms for such an effect have been proposed, including a potential role in reducing androgen precursor bioavailability. It is hypothesized that statins may therefore improve outcomes specifically in patients treated with the CYP17 inhibitor Abi. Di Lorenzo (2017) recently published an analysis of 187 pts showing a relationship between Abi and improved survival (OS). We report the results of a larger confirmatory analysis in a separate cohort. Methods: Disease outcome and statin use were assessed retrospectively in locally advanced or metastatic CRPC patients receiving Abi in British Columbia, Canada. The Kaplan-Meier method was used to estimate survival times, Cox proportional hazards and logistic regression were used to investigate factors potentially prognostic of overall survival and PSA response respectively. A multivariable model was constructed using factors with limited missing data and known biologic rationale. Impact of statins was then assessed adjusting for factors included in the multivariable model. Results: 301 patients receiving Abi were assessed, of whom 84 (28%) were statin users. Median OS of Abi patients was 11.3 months for non-statin users and 16.2 months for statin users (hazard ratio = 0.79, 95% CI = 0.61-1.03, p = 0.079). Effect of statin use remained borderline after adjusting (n = 279, hazard ratio = 0.78, 95% CI = 0.59-1.04, p = 0.087) for age, prior prostatectomy, radiation, Docetaxel, time from diagnosis, neutrophils-lymphocyte ratio and presence of metastases. Forty-eight percent of statin users and 37% of non-statin users had a PSA response (multivariable odds ratio = 1.59, 95% CI = 0.91-2.78, p = 0.11). Conclusions: Although limited by sample size, our data showed a trend that statins may mildly enhance the anti-tumor effects of Abi in CRPC patients. These results support the findings of Di Lorenzo et al. (2017), and suggest that depletion of de novo cholesterol production may further limit androgen synthesis in concert with CYP17A1 inhibition. Further studies are warranted.
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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 | 0.000 | 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 | 0.001 |
| 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".