Analysis of prevalence and prognostic implications of early versus delayed PSA declines during radium-223 (Ra223) treatment among men with metastatic castration-resistant prostate cancer (mCRPC).
Bibliographic record
Abstract
117 Background: Ra233 is a well-tolerated, bone-seeking alpha emitter that prolongs the survival of men with mCRPC. Since there is a lack of validated biomarkers useful for disease monitoring during Ra223 therapy, we sought to characterize prostate-specific antigen (PSA) response patterns within a retrospective cohort study of real-world Ra223 treatment in four cancer centres across Ontario. Methods: Of 198 patients (pts) overall, 64 were not included due to incomplete data. The remaining 134 pts were grouped into (i) early PSA responders with a ≥30% PSA decrease (PSA30) within 12 weeks of treatment start, (ii) pts with an initial PSA flare followed by decreasing PSA, and (iii) non-responders. We analyzed the overall survival (OS) of these three cohorts using the Kaplan-Meier method and log-rank testing. Results: PSA30 responses were rare (n = 11; 8.2%), PSA flares were seen in 20.2% of pts (n = 27), but the majority of pts did not achieve a PSA response (n = 96; 71.7%). Of the pts identified as having a PSA flare, 11/27 (40.7%) presented with a post-flare PSA decrease below baseline, whereas in 16/27 (59.3%) the PSA decreased below the flare peak but not below baseline. 5/27 (18.5%) pts with a PSA flare achieved a PSA30. The median OS was not reached, 15.8 months and 14.7 months in responders, flare pts and non-responders, respectively (p > 0.05). Similarly, one year OS was 90.9%, 67.7% and 63.9% in responders, flare pts and non-responders. Conclusions: PSA flares are seen in one fifth of men undergoing Ra223 therapy for mCRPC. Despite delayed PSA declines of varying degrees, the survival of PSA flare pts is comparable to men without any PSA decline.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".