The Contemporary Use of Radium-223 in Metastatic Castration-resistant Prostate Cancer
Bibliographic record
Abstract
Radium-223 dichloride (radium-223) was approved for the treatment of patients with castration-resistant prostate cancer (CRPC) and symptomatic bone metastases in the United States and Europe in 2013. This followed a reported overall survival benefit for patients treated with radium-223 and best standard of care (BSoC) when compared with placebo and BSoC in the ALpharadin in SYMptomatic Prostate CAncer (ALSYMPCA) trial. At that time, docetaxel was the standard first-line choice for patients with metastatic CRPC (mCRPC). Since then, the treatment landscape has changed dramatically with new hormonal agents (abiraterone and enzalutamide) considered to be the first-line choice for many patients. The optimal patient profile for radium-223 in the modern setting, and its best use either in sequence or in combination with other approved agents are unclear, with few definitive guidelines available. This article reports on the views of a group of urologists and medical oncologists experienced in treating patients with mCRPC with radium-223 in routine clinical practice. The aim is to provide an overview of the current use of radium-223 in the treatment of patients with mCRPC, and to discuss best practices for patient selection and on-treatment monitoring. Where agreement was reached, guidance on the optimal use of radium-223 is provided.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".