Improvement in Sensory Pain Rating After Palliative Systemic Radionuclide Therapy in Patients With Advanced Prostate Cancer
Bibliographic record
Abstract
This study assessed whether baseline and short-term patient-reported quality of life (QOL) differs in patients with symptomatic metastatic prostate cancer undergoing palliative management using opioids, nonsteroidal anti-inflammatory agents (NSAIDs), (89)strontium chloride ((89)Sr), and samarium-lexidronam ((153)Sm). Males were grouped according to primary palliative intervention: opioids (n = 40), NSAIDs (n = 40), (89)Sr chloride (n = 25), and (153)Sm (n = 25). The short form of the self-administered McGill Pain Questionnaire was used to measure QOL at baseline, 4 and 8 weeks after initiation of treatment. Clinical data were collected from patients' medical records. Statistical analyses were conducted using descriptive methods and the Student t test. A significant increase in the sensory pain rating was observed in the patients treated by NSAIDs ([upward arrow]21%) and (89)Sr ([upward arrow]46%), whereas those treated by opioids ([downward arrow]27%) and (153)Sm ([downward arrow]27%) demonstrated a significant (P < 0.05) decrease in this subscore. There was a longitudinal decrease in QOL over time in patients treated by NSAIDs and (89)Sr as measured by the total pain rating score, whereas those treated with the other agents experienced improved QOL. This study demonstrates improvement in QOL achieved using (153)Sm, which is comparable to that achieved with the use of opioids during this observation interval.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".