Prognostic factors for overall survival in patients with metastatic castration-resistant prostate cancer treated with radium-223: a meta-analysis of real-world evidence
Bibliographic record
Abstract
Background: Metastatic castration-resistant prostate cancer (mCRPC) remains a lethal disease with limited treatment options. Radium-223 (Ra-223) improves survival in bone-predominant mCRPC, but real-world outcomes vary widely. This meta-analysis synthesizes real-world evidence to identify prognostic factors for overall survival (OS) in Ra-223-treated patients. Methods: Following PRISMA guidelines, we systematically searched PubMed, Embase, Web of Science, and Cochrane Library for observational studies reporting OS-associated prognostic factors in mCRPC patients receiving Ra-223. Pooled hazard ratios (HRs) were calculated. Study quality was assessed via Newcastle-Ottawa Scale. Results: Among 25 studies (n=8,795 patients), the pooled Ra-223 completion rate was 52.6% (95% CI: 48.9-56.3%). Each additional Ra-223 injection significantly improved OS (HR = 0.478, 95% CI: 0.362-0.630). Poorer OS correlated with older age (HR = 1.012/year), higher ECOG (HR = 2.078), elevated baseline PSA (HR = 1.922), ALP (HR = 1.981), LDH (HR = 1.702), NLR (HR = 2.255), and visceral metastases (HR = 2.342). Protective factors included hemoglobin levels (HR = 0.756/g/dL) and PSA/ALP declines during therapy (HR = 0.386 and 0.701, respectively). Prior chemotherapy predicted worse outcomes (HR = 1.425), while Gleason score and concurrent bone protectants showed no significant association. Conclusion: Real-world data confirm Ra-223's survival benefit is closely associated with treatment completion and baseline clinical factors. The findings support risk-stratified patient selection and tailored management in mCRPC.
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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 | 0.016 | 0.025 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.059 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".