A definition of “uncomplicated bone metastases” based on previous bone metastases radiation trials comparing single-fraction and multi-fraction radiation therapy
Bibliographic record
Abstract
The most recent systematic review of randomized trials in patients with bone metastases has shown equal efficacy of single fraction (SF) and multiple fraction (MF) palliative radiation therapy in pain relief. It is important to determine the patient population to which the evidence applies. This study aims to examine the eligibility criteria of the studies included in the systematic review to define characteristics of "uncomplicated" bone metastases. Inclusion and exclusion criteria of 21 studies included in the systematic review were compared. Common eligibility criteria were documented in hopes of defining the specific features of a common patient population representative of those in the studies. More than half of the studies included patients with cytological or histological evidence of malignancy. Patients with impending and/or existing pathological fracture, spinal cord compression or cauda equina compression were excluded in most studies. Most studies also excluded patients receiving retreatment to the same site. "Uncomplicated" bone metastases can be defined as: presence of painful bone metastases unassociated with impending or existing pathologic fracture or existing spinal cord or cauda equina compression. Therefore, MF and SF have equal efficacy in patients with such bone metastases.
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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 | 0.061 | 0.111 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.015 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".