BMET-02EVALUATION OF DIFFERENT THERAPEUTIC MODALITIES FOR PRIMARY TREATMENT AND SALVAGE THERAPY AND THEIR RELATIVE COST IN PATIENTS WITH BRAIN METASTASES: A SINGLE INSTITUTION REPORT
Bibliographic record
Abstract
BACKGROUND: Indications for whole brain radiotherapy (WBRT), stereotaxic radiosurgery (SRS) and craniotomy are not sufficiently well defined in a context of optimal care that takes into account cost effectiveness of therapy. Previous reports have shown contradictory results with regards to optimal care. Some favor loco-regional control while others preservation of neuro-cognitive function. We decided to review our own experience and trends in treatment with analysis focused not only on survival but as well treatment costs and use of salvage therapy. METHODS: Between January 2010 and 2015, we have treated 387 consecutive patients treated for brain metastasis. Chart review will collect the type of initial treatment as well as the type and the number of salvage treatment. The patients will be identified according to anatomic primary site and histology, age and gender, the date of initial diagnosis, performance status, number of brain metastasis and presence of other systemic metastasis. Local control and survival will be analyzed using the Kaplan Meier method, while age, gender, primary site location and initial method of treatment will be studied with COX univariate and multivariate analysis. Treatment cost for every patient will also be evaluated. RESULTS: Data analysis will be done between June and July 2015 and the results will be presented at the San Antonio SNO meeting.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".