A population-based study of the use of radium 223 in metastatic castration-resistant prostate cancer: Factors associated with treatment completion
Bibliographic record
Abstract
INTRODUCTION: Radium 223 (Ra223) given for six cycles has proven efficacy in clinical trials, but its population-level generalizability has not been well-described. The objectives of this study were to describe population-based Ra223 use in the abiraterone and enzalutamide era and identify factors associated with completion. METHODS: All Ra223 patients at the British Columbia Cancer Agency between September 2013 and February 2016 were identified. Patients who completed <5 vs. ≥5 cycles were compared on patient characteristics, lines of prior therapy, prostate-specific antigen (PSA) and alkaline phosphatase (ALP) decline >30% from baseline (R30%), and survival, to identify factors associated with therapy completion. RESULTS: Ninety-one patients were identified; 48 (52.7%) completed >5 cycles. Median overall survival (mOS) was 10.7 months, PSA and ALP R30% were 21% and 52%, respectively. Completion of <5 cycles was associated with higher baseline ALP (p=0.05) and lower baseline hemoglobin (Hb) levels (p=0.03). Patients in the ≥5 cycles group had longer mOS than those in the <5 cycles group (16.2 vs. 5.9 months; p<0.0001), as well as higher PSA R30% (33.3% vs. 7.0%; p=0.002) and ALP R30% (66.7% vs. 34.9%; p=0.03). Patients with ALP ≥220 and Hb ≤118 had 3.85 times the odds of not completing ≥5 cycles vs. ALP <220 and Hb >118. CONCLUSIONS: Compared to clinical trials, patients in a population-based setting had more lines of therapy and shorter survival. Lower ALP and higher hemoglobin were associated with completion of >5 cycles, longer mOS, and greater incidence of PSA and ALP response.
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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 | 0.003 |
| 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 | 0.001 | 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".