Independent External Validation of a Score Predicting Survival After Radiotherapy for Bone Metastases and Expansion to Patients Treated With Single Fraction Radiotherapy
Bibliographic record
Abstract
BACKGROUND: Recently a prognostic score that predicts 12-month survival in patients treated with fractionated radiotherapy for painful bone metastases has been developed. Fractionated radiotherapy might cause unnecessary burden for patients with limited survival, thus estimation of survival is clinically relevant. The purpose of the present study was independent external validation of the new score and, in addition, its application in patients who received single fraction irradiation, a convenient option currently endorsed in several guidelines. METHODS: We conducted a retrospective analysis of 270 patients, including 24% who had received single fraction irradiation. The three-tiered score was assigned as described in the development study, and included age, performance status and primary tumor type. Additional prognostic factors not studied in the development cohort, such as the Glasgow prognostic score (GPS) and presence of liver metastases, were included in this validation study. RESULTS: The three-tiered score was valid in this independent cohort (12-month survival rates were 7%, 30% and 71%, respectively, P = 0.0001). Its performance and validity were also confirmed in the single fraction radiotherapy group. Three additional prognostic factors were significant in the multivariate analysis and may therefore contribute to decision making. CONCLUSIONS: Irrespective of fractionation, the score based on age, performance status and primary tumor type provides a readily available estimate of 12-month survival.
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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 | 0.005 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".