A prognostic model for stratifying clinical outcomes in chemotherapy-naive metastatic castration-resistant prostate cancer patients treated with abiraterone acetate
Bibliographic record
Abstract
Introduction: Recently, a prognostic index including six risk factors (RFs) (unfavourable Eastern Cooperative Oncology Group performance status [ECOG PS], presence of liver metastases, short response to luteinizing hormone-releasing hormone [LHRH] agonists/ antagonists, low albumin, increased alkaline phosphatase [ALP] and lactate dehydrogenase [LDH]) was developed from the COUAA- 301 trial in post-chemotherapy metastatic castration-resistant prostate cancer (mCRPC) patients treated with abiraterone acetate. Our primary objective was to evaluate this model in a cohort of chemotherapy-naive mCRPC patients receiving abiraterone.Methods: We identified 197 chemotherapy-naive patients who received abiraterone at six BC Cancer Agency centres and who had complete information on all six RFs. Study endpoints were prostate-specific antigen (PSA) response rate (RR), time to PSA progression, time on treatment, and overall survival (OS). PSA RR and survival outcomes were compared using Χ2 test and log-rank test. Multivariable Cox proportional hazard analysis was performed to identify RFs independently associated with OS.Results: Patients were classified into good (0‒1 RFs), intermediate (2‒3 RFs), and poor (4‒6 RFs) prognostic groups (33%, 52%, and 15%, respectively). For good-, intermediate-, and poor-risk patients, PSA RR (≥50% decline) was 60% vs. 42% vs. 40% (p=0.05); median time to PSA progression was 7.3 vs. 5.3 vs. 5.0 months (p=0.02); and median OS was 29.4 vs. 13.8 vs. 8.7 months (p<0.0001).Conclusions: The six-factor prognostic index model stratifies clinical outcomes in chemotherapy-naive mCRPC patients treated with abiraterone. Identifying patients at risk of poor outcome is important for informing clinical practice and clinical trial design.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 teacher head, 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".