Phase II multicenter trial combining nivolumab and radiosurgery for NSCLC and RCC brain metastases
Bibliographic record
Abstract
Abstract Background Anti-PD-1 has activity in brain metastases (BM). This phase II open labeled non-randomized single arm trial examined the safety and efficacy of combining nivolumab with radiosurgery (SRS) in the treatment of patients with BM from non-small cell lung cancer (NSCLC) and renal cell carcinoma (RCC). Methods This was a multicenter trial (NCT02978404) in which patients diagnosed with NSCLC or RCC, having ≤ 10 cc of un-irradiated BM and no prior immunotherapy were eligible. Nivolumab (240 mg or 480 mg IV) was administered for up to 2 years until progression. SRS (15–21 Gy) to all un-irradiated BM was delivered within 14 days after the first dose of nivolumab. The primary endpoint was intracranial progression free survival (iPFS). Results Twenty-six patients (22 NSCLC and 4 RCC) were enrolled between August 2017 and January 2020. A median of 3 (1–9) BM were treated with SRS. Median follow-up was 16.0 months (0.43–25.9 months). Two patients developed nivolumab and SRS related grade 3 fatigue. One-year iPFS and OS were 45.2% (95% CI 29.3–69.6%) and 61.3% (95% CI 45.1–83.3%), respectively. Overall response (partial or complete) of SRS treated BM was attained in 14 out of the 20 patients with ≥1 evaluable follow-up MRI. Mean FACT-Br total scores were 90.2 at baseline and improved to 146.2 within 2–4 months (P = .0007). Conclusions The adverse event profile and FACT-Br assessments suggested that SRS during nivolumab was well tolerated. Upfront SRS with the initiation of anti-PD-1 prolonged the 1-year iPFS and achieved high intracranial control. This combined approach merits validation randomized studies.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".