Safety and efficacy of repeat administration of samarium Sm‐153 lexidronam to patients with metastatic bone pain
Bibliographic record
Abstract
BACKGROUND: Samarium Sm 153 lexidronam (Sm-153) is an effective and well-tolerated treatment for painful bone metastases. The purpose of the analysis was to assess the safety and efficacy of repeated doses of Sm-153 in patients with metastatic bone pain. METHODS: Data were collected prospectively for 202 patients administered 1.0 mCi/kg of Sm-153. Particular emphasis was placed on analysis of data from 55 patients receiving > or = 2 doses. Pain scores, adverse events, and hematologic parameters were assessed after each dose. RESULTS: Mild, transient suppression of platelets and white blood cell counts was the most common adverse event after treatment. Nadirs were approximately half of baseline at 4 weeks after dosing with recovery by Week 8 in 90% of patients. Temporary grade 3 thrombocytopenia occurred in 11%, 12%, and 17% of patients after the first, second, and third drug administration, respectively. Grade 3 leukopenia occurred in less than 7% of patients independent of the number of administrations. Significant decreases in pain scores (P < .001) were observed at Week 4 after each of the first 3 doses and maintained at Week 8 after the first 2 doses (P < .003) but not the third. Decreases in pain scores were observed in 70%, 63%, and 80% of patients, respectively, at Week 4 after the first 3 administrations. CONCLUSIONS: Repeated dosing of 1.0 mCi/kg of Sm-153 was both safe and effective and is a reasonable treatment option in patients whose bone pain responds and then recurs after an initial dose provided that adequate hematologic function is present at the time of drug administration.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".