The Future Is Now—Prospective Study of Radiosurgery for More Than 4 Brain Metastases to Start in 2018!
Bibliographic record
Abstract
Stereotactic radiosurgery (SRS) has replaced whole brain radiotherapy (WBRT) as standard therapy for most patients with four or fewer brain metastases due to improved cognitive outcomes and more favorable health related quality of life (QoL). Whether SRS or WBRT is the optimal radiation modality for patients with five to fifteen brain metastases remains an open question. Efforts are underway to develop prospective evidence to answer this question. One of the planned trials is a Canadian Cancer Trials Group (CCTG)-lead North American intergroup trial. In general cancer treatments must have two basic aims: prolonging and improving QoL. In this vein, the selection of overall survival and QoL metrics as outcomes appear obvious. Potential secondary outcomes are numerous: patient/disease related, treatment related, economic, translational, imaging, and dosimetric. In designing a trial, one must also ponder what is standard WBRT-specifically, whether it should be associated with memantine. With the rapid accrual of an intergroup trial of hippocampal-sparing WBRT, we may find that the standard WBRT regimen changes in the course of planned trials. As up-front radiosurgery is increasingly used for more than 4 brain metastases without high level evidence, we have a window of opportunity to develop high quality evidence which will help guide our future clinical and policy decisions.
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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 | 0.010 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".