Effects of circadian rhythms and treatment times on the response of radiotherapy for painful bone metastases
Bibliographic record
Abstract
BACKGROUND: Previous studies have observed how the time of radiotherapy delivery can impact toxicities and outcomes. The goal of this study was to determine whether treatment time influenced radiotherapy response for bone metastases. METHODS: Patients who received radiation treatment to painful bone metastases from January 2000 to December 2010 were included in our analysis. Demographic and treatment information including performance status, primary site, treatment dose and fraction, and response were collected prospectively. Treatment times were extracted from patient medical records. Patients were allocated to 8:00 AM-11:00 AM, 11:01 AM-2:00 PM, or 2:01 PM-5:00 PM cohorts based on their treatment times. To compare treatment response between the three cohorts, the Fisher exact test was used. A two-sided P value of <0.05 was considered statistically significant. Analysis was repeated with males and females separately. RESULTS: A total of 194 patients were included. The median age was 68 years and 55.5% of patients responded to treatment. The dose and fraction of radiation received differed significantly between treatment cohorts using all allocation methods. Females in the 11:01 AM-2:00 PM cohort exhibited a significantly higher response rate (P=0.02) and differing proportions of response types (P=0.03) compared to the 8:00 AM- 11:00 AM and 2:01 PM-5:00 PM cohorts when allocated using all treatment times. No significant differences in response were seen between cohorts when all patients were analysed together or analysed for males only. CONCLUSIONS: Treatment time may affect response in female patients receiving radiotherapy for painful bone metastases. Subsequent chronotherapy studies in radiation should investigate these gender differences.
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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 | 0.006 |
| 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".