Pain response in a population-based study of radium-223 (Ra223) for metastatic castration-resistant prostate cancer
Bibliographic record
Abstract
INTRODUCTION: Clinical trials have shown that radium-223 (Ra223) can prolong survival and improve quality of life in patients with metastatic castration-resistant prostate cancer (mCRPC). The objectives of this study were to evaluate pain responses with Ra223 at a population-based level and to determine if there is an association between pain response and alkaline phosphatase (ALP) response. METHODS: All patients from the Vancouver and Kelowna Cancer Centers (CC) in British Columbia who were treated with Ra223 between June 2015 and December 2016 were identified. Patients completed the Brief Pain Inventory (BPI) just prior to each Ra223 injection. Pain response was defined as a two or more point improvement in worst pain relative to baseline, without an increase in pain medication level. ALP was determined at each visit, with a response threshold defined as a 30% decrease from baseline, consistent with the definition of response used in the ALSYMPCA trial. RESULTS: A total of 65 patients in Vancouver and Kelowna CC received Ra223 during the study period and 56 patients had at least one BPI record, of which 44 (79%) patients were assessable for change in worst pain. Of the assessable patients, 23 (52%, 95% confidence interval [CI] 38-67) had a pain response, although the use of concurrent external beam radiotherapy was a confounder in four cases. Of the 44 patients assessable for change in worst pain, 59% had ALP responses greater than 30%. An ALP response was seen in 56% of pain-responders vs. 43% of non-pain-responders. There was no association between pain response and ALP response (Phi =-0.05; p=0.77). CONCLUSIONS: Ra223 administration was associated with a meaningful pain response rate in this cohort. There was no correlation between pain response 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 | 0.002 |
| 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 | 0.000 |
| 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".