BIOMARKER STATUS PREDICTS FOR LOCAL CONTROL (LC) FOLLOWING SPINE STEREOTACTIC BODY RADIOTHERAPY (SBRT) IN NON-SMALL CELL LUNG CANCER (NSCLC) PATIENTS WITH SPINAL METASTASES
Bibliographic record
Abstract
Abstract Report of spine SBRT outcomes in NSCLC patients and impact of death-ligand 1 (PD-L1) status and epidermal growth factor (EGFR) mutation on LC. METHODS: 165 patients and 389 spinal segments were retrospectively reviewed. Primary endpoint was LF and secondary outcomes included overall survival (OS) and vertebral compression fracture (VCF) rates. RESULTS: Median follow-up, OS and age was 13 months (range, 0.5-95 months), 18.4 months (95% CI 11.4-24.6), and 67 years (range, 28.2-89.9) respectively. 52% were female and 76% had adenocarcinoma. 29% had an EGFR mutation, 16% were PD-L1 ≥ 50%, 20% PD-L1 1-49% and 35% PD-L1 <1%. Of 389 segments, 79% were denovo. At baseline, 35% had VCF, 27% epidural disease and 27% paraspinal extension. 61% were treated with 24 or 28 Gy in 2 SBRT fractions. LF cumulative incidence (CI) at 2-years was 25.4% (95% CI 20.9%-30%). EGFR positivity (p<0.0001), PD-L1≥50% (p=0.013) and treatment with IO within 1 month of SBRT (p=0.004) predicted for LC on multivariable analysis (MVA). The 2-year LF rate in EGFR-positive vs. negative patients were 17.7% vs. 28.8%, and in those PD-L1 ≥50% vs PD-L1<50% were 7.8% vs. 38.1%. CI of VCF at 2-years were 8.8% (95% CI 6.1-12.0%). Prior SBRT to the same segment (P<0.0001) and baseline VCF (p<0.0001) were predictors on MVA. CONCLUSION: We identify predictability of EGFR mutation, PD-L1 ≥50% and peri-SBRT IO on LC following spine SBRT in NSCLC.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".