Stereotactic ablative radiotherapy for comprehensive treatment of oligometastatic tumors (SABR-COMET): Study protocol for a randomized phase II trial
Bibliographic record
Abstract
BACKGROUND: A recent randomized phase II trial evaluated stereotactic ablative radiotherapy (SABR) in a group of patients with a small burden of oligometastatic disease (mostly with 1-3 metastatic lesions), and found that SABR was associated with a significant improvement in progression-free survival and a trend to an overall survival benefit, supporting progression to phase III randomized trials. METHODS: Two hundred and ninety-seven patients will be randomized in a 1:2 ratio between the control arm (consisting of standard of care [SOC] palliative-intent treatments), and the SABR arm (consisting of SOC treatment + SABR to all sites of known disease). Randomization will be stratified by two factors: histology (prostate, breast, or renal vs. all others), and disease-free interval (defined as time from diagnosis of primary tumor until first detection of the metastases being treated on this trial; divided as ≤2 vs. > 2 years). The primary endpoint is overall survival, and secondary endpoints include progression-free survival, cost effectiveness, time to development of new metastatic lesions, quality of life (QoL), and toxicity. Translational endpoints include assessment of circulating tumor cells, cell-free DNA, and tumor tissue as prognostic and predictive markers, including assessment of immunological predictors of response and long-term survival. DISCUSSION: This study will provide an assessment of the impact of SABR on survival, QoL, and cost effectiveness to determine if long-term survival can be achieved for selected patients with 1-3 oligometastatic lesions. TRIAL REGISTRATION: Clinicaltrials.gov identifier: NCT03862911. Date of registration: March 5, 2019.
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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 | 0.027 | 0.020 |
| Meta-epidemiology (narrow) | 0.006 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.052 | 0.014 |
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".