Survival Outcomes of Immune Checkpoint Inhibitors in Conjunction with Cranial Radiation for Older Adults with Non-Small Cell Lung Cancer and Synchronous Brain Metastasis
Bibliographic record
Abstract
Immune checkpoint inhibitors (ICIs) display efficacy in non-small cell lung cancers (NSCLCs) with brain metastases (BMs) and studies suggest potential synergy with cranial radiation (CR). However, population-based evaluations of optimal time between ICI-CR combinations are limited in the US. Using SEER-Medicare database (2010-2019), we analyzed patients aged ≥65 years with NSCLC and BM receiving ICI-CR within 6 months of diagnosis, excluding those receiving targeted therapies. First treatment after diagnosis (ICI or CR) was defined as index treatment; followed by subsequent treatment. Findings were validated using an independent cohort from the TriNetX LIVE™ Platform. Patients were grouped by interval between the end of the index treatment and the start of the subsequent treatment: ≤15 days (n = 117), 16-30 days (n = 42), and >30 days (n = 77). Overall survival (OS) was measured from the start of the subsequent treatment until death, end of insurance coverage, or study end. Kaplan-Meier survival curves and multivariable Cox proportional hazards models estimated differences between groups. Among 236 patients, median OS was 134 days, 92 days, and 209 days, respectively. No significant OS differences were found across intervals. However, a survival benefit emerged approximately 300 days after follow-up when ICI was administered within 15 days of CR. These findings offer insight into treatment sequencing in NSCLC with BM and support further investigation in larger cohorts.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".