BMET-06. IMPROVED SURVIVAL AND PROGNOSTIC ABILITY IN LUNG CANCER PATIENTS WITH BRAIN METASTASES: AN UPDATE OF THE GRADED PROGNOSTIC ASSESSMENT FOR LUNG CANCER USING MOLECULAR MARKERS (LUNG-molGPA)
Bibliographic record
Abstract
Lung cancer is the leading worldwide cause of cancer and cancer-related mortality. With improving, molecularly-targeted systemic therapies, lung cancer patients are living longer and are at increased risk for brain metastases. Understanding how prognosis varies across this heterogeneous population is essential to individualizing care and designing future clinical trials. Our original Lung-GPA prognostic index was based on four factors (age, Karnofsky Performance Status, extracranial metastases and number of brain metastases) found to be significant for survival and weighted by magnitude, such that patients with the best/worst prognosis would have a Lung GPA score of 4.0/0.0, respectively. The purpose of this study is to update the Lung-GPA, incorporating that gene/molecular alteration data, to create the new Lung-molGPA. A multi-institutional retrospective database (2006-2014) of 2186 patients with NSCLC and newly diagnosed brain metastases was utilized for this analysis. Prognostic factors reaching statistical significance on multivariate analysis were weighted by Hazard Ratio and an updated Lung-molGPA was designed. Significant prognostic factors included the four original factors and two new factors (EGFR and ALK alterations in adenocarcinoma patients). Notably, the overall median survival for the group increased from 7 to 12 months between the two study periods (1985-2005 and 2006-2014). NSCLC-adenocarcinoma patients with Lung-molGPA of 3.5-4.0 exhibited a median survival of nearly 4 years. This best prognosis group (Lung-molGPA 3.5-4.0) would require all of the following: EGFR or ALK alterations, KPS > 90, age < 70, no extracranial metastases and < 5 brain metastases. The updated Lung-molGPA incorporates gene alteration data. Survival and the ability to predict survival duration for NSCLC patients with brain metastases has improved significantly. This free user-friendly tool (BrainMetGPA.com) will facilitate clinical decision-making and appropriate stratification of future clinical trials.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".