RADT-07. RADIOGRAPHIC “NECROSIS" FOLLOWING SINGLE-FRACTION SRS AND IMMUNE CHECKPOINT INHIBITION IS ASSOCIATED WITH IMPROVED SURVIVAL IN PATIENTS WITH BRAIN METASTASES: AN INTERNATIONAL MULTICENTER STUDY
Bibliographic record
Abstract
Abstract OBJECTIVE Immune checkpoint inhibitors (ICI) and stereotactic radiosurgery (SRS) are commonly utilized in the management of brain metastases. Treatment-related imaging changes (TRIC) are a frequently observed clinical manifestation and are commonly classified as radiographic radiation necrosis. However, these findings are not well characterized and may predict for response to SRS and ICI. METHODS The diagnosis-specific graded prognostic assessment was used to guide variable selection. TRIC were determined based upon MRI, PET/CT, or MR spectroscopy and a consensus by local clinical providers was required. RESULTS The analysis included 697 patients with 4,536 brain metastases across 11 institutions in 4 countries. The median follow-up after SRS was 13.6 months. The median age was 66 years, 54.1% of patients were male, and 57.3%, 36.3%, and 6.4% were non-small cell lung cancer, melanoma, and renal cell carcinoma (RCC) histology, respectively. TRIC were observed in 9.8%. On univariable analysis, Karnofsky Performance Status (KPS) (hazard ratio [HR]: 0.98; p < 0.001), presence of TRIC (HR: 0.67; p = 0.03), female sex (HR: 0.67; p < 0.001), and prior resection (HR: 0.60; p = 0.03) were associated with improved OS. On multivariable analysis, KPS (HR: 0.98; p < 0.001) and the presence of TRIC (HR: 0.66; p = 0.03) were associated with improved OS. A V12 Gy ≥ 10 cm3 (Odds Ratio [OR]: 2.78; p < 0.001), prior whole brain radiation therapy (OR: 3.46; p = 0.006), and RCC histology (OR: 3.10; p = 0.01) were associated with an increased probability of developing TRIC. The median OS in patients with and without TRIC was 29.0 and 23.1 months, respectively (log-rank p = 0.03). CONCLUSION TRIC following ICI and SRS are associated with a median OS benefit of approximately 6 months. Further prospective study is warranted to further elucidate the role and etiology of this common clinical scenario.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".