The Effect of Corticosteroids on Prostate Cancer Outcome Following Treatment with Enzalutamide: A Multivariate Analysis of the Phase III AFFIRM Trial
Bibliographic record
Abstract
PURPOSE: The clinical impact of concurrent corticosteroid use (CCU) on enzalutamide-treated patients with metastatic castration-resistant prostate cancer (mCRPC) is unknown. We investigated the association of CCU with overall survival (OS), radiographic progression-free survival (rPFS), and time to prostate-specific antigen progression (TTPP) in post-chemotherapy, enzalutamide-treated patients with mCRPC. PATIENTS AND METHODS: Post hoc analysis of AFFIRM (NCT00974311) with patients (n = 1,199) randomized 2:1 to enzalutamide 160 mg/day or placebo. Treatment group, CCU, and known prognostic factors were evaluated for impact on OS, rPFS, and TTPP using a multivariate Cox proportional hazards model. CCU was defined as "baseline" (use started at baseline) or "on-study" (baseline plus use that was started during the trial). RESULTS: Enzalutamide significantly improved OS, rPFS, and TTPP independent of baseline CCU but was associated with inferior clinical outcomes when compared with no baseline CCU, including a shorter OS [10.8 months vs. not reached (NR); HR for use vs. no use, 2.13; 95% confidence interval (CI), 1.79-2.54], rPFS (5.2 months vs. 8.0 months; HR, 1.49; 95% CI, 1.29-1.72], and TTPP (4.6 months vs. 5.7 months; HR, 1.50; 95% CI, 1.25-1.81). These findings held in a multivariate analysis adjusting for baseline prognostic factors wherein baseline CCU was independently associated with decreased OS (HR, 1.71; 95% CI, 1.43-2.04; P < 0.0001) and rPFS (HR, 1.28; 95% CI, 1.11-1.48; P = 0.0007). CONCLUSIONS: Patients with mCRPC benefited from enzalutamide treatment independent of CCU, but CCU was associated with worse baseline prognostic factors and outcomes.
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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 | 0.007 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".