MLTI-04. EVOLUTION OF TREATMENT PARADIGMS FOR PATIENTS WITH ≥1 BRAIN METASTASES FROM PRIMARY NON-SMALL-CELL LUNG CANCER – A SYSTEMATIC REVIEW
Bibliographic record
Abstract
Abstract BACKGROUND: Brain metastases (BM) are common in non-small cell lung cancer (NSCLC), with approximately 10% of patients presenting with BM at the time of diagnosis. The aim of this systematic review was to critically evaluate the evolution of management paradigms for BM from NSCLC. METHODS: We searched MEDLINE, EMBASE, Web of Science, ClinicalTrials.gov, and CENTRAL for randomized controlled trials (RCTs) published until October 2018. Comparative RCTs based on ≥ 50 patients were selected. The primary outcomes of interest were overall survival (OS) and progression-free survival (PFS). RESULTS: Among 3188 abstracts, 14 RCTs (2494 patients) met inclusion criteria. Median sample size was 97 (range 59–538). Most trials were open-label, parallel, superiority trials. All included patients aged ≥18 with histologically proven NSCLC and ≥1 BM proven on CT/MRI. The majority of trials (11/14) excluded patients with non-favorable performance status (ECOG, KPS, or WHO scales), prior SRS or WBRT, and/or leptomeningeal metastases. Interventions assessed included WBRT (11/14), SRS (3/14), targeted therapies (e.g. EGFR inhibitors, 5/14), and various chemotherapeutic regimens (12/14). Most trials (12/13) reported no significant difference in OS between interventions. 4/10 trials reported a difference in PFS, two of which only included patients with EGFR-mutant NSCLC; these showed a significant increase in PFS in patients managed with EGFR inhibitors. The other two trials reported longer PFS with sodium glycididazole + WBRT vs. WBRT alone (p=0.038) and temozolomide + SRS vs. SRS alone (p=0.003). The incidence of adverse events was consistent across most treatment groups. CONCLUSIONS: Most trials showed no significant improvement in OS; however, improvement in PFS was seen in several trials, most notably in EGFR-positive patients treated with EGFR inhibitors. Given the long-standing merit of radiation-based therapies for BM management, these data support the need for an in-depth meta-analysis assessing the comparative efficacy of current management paradigms for specific patient populations.
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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 | 0.008 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.010 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".