Non-Small-Cell Lung Cancer Patients Harboring ROS1 Rearrangement: Real World Testing Practices, Characteristics and Treatment Patterns (ROS1REAL Study)
Bibliographic record
Abstract
ROS1 rearrangements are considered rare in non-small-cell lung cancer (NSCLC). This retrospective real-world study aimed to evaluate first-line treatment with crizotinib, a tyrosine kinase inhibitor (TKI) standard of care vs. new generation ROS1 anti-cancer agents. Forty-nine ROS1-expressing NSCLC patients, diagnosed with advanced metastatic disease, were included. Molecular profiling using either FISH/CISH or NGS was performed on tissue samples. Twenty-eight patients were treated with crizotinib, while fourteen patients were administered newer drugs (entrectinib, repotrectinib) and seven patients received platinum-doublet chemotherapy in a first-line setting. Overall response rate and disease control rate for the crizotinib and entrectinb/repotrectinib cohort were 68% and 82% vs. 86% and 93%, respectively. Median progression free survival was 1.6 years (95% CI 1.15-2.215) for the crizotinib treatment vs. 2.35 years for the entrectinib/repotrectinib cohort (95% CI 1.19-3.52). Central nervous system progression was noted in 20% and 25% of the crizotinib and entrectinib/repotrectinib cohorts, respectively. This multi-center study presents real-world treatment patterns of ROS1 NSCLC population, indicating that crizotinib exhibited comparable results to entrectinib/repotrectinib in a first-line setting, although both response rate and survival was numerically longer with treatment with newer agents.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".