Efficacy and safety of crizotinib in the treatment of advanced non-small cell lung cancer with ROS1 gene fusion: a systematic literature review and meta-analysis of real-world evidence
Bibliographic record
Abstract
BackgroundCrizotinib was approved to treat patients with advanced non-small cell lung cancer (aNSCLC) with ROS proto-oncogene 1 (ROS1) gene fusion in 2016. We conducted a systematic literature review to identify real-world evidence (RWE) studies and estimated the efficacy and safety of crizotinib using meta–analyses (MA) for objective response rate (ORR), real-world progression-free survival (PFS), and overall survival (OS).MethodsWe searched MEDLINE®, Embase, and Cochrane CENTRAL from January 2016 to March 2023 using Ovid® for published single-arm or comparative RWE studies evaluating patients (N ≥ 20) receiving crizotinib monotherapy for aNSCLC with ROS1 gene fusion. Pooled estimates for ORR and grade 3/4 adverse events (AEs) were derived using the metafor package in R while pooled estimates for median real-world PFS (rwPFS) and OS were derived using reconstructed individual patient data from published Kaplan-Meier curves. The primary analysis included all studies regardless of crizotinib line of therapy; a subgroup analysis (SA) was conducted using studies evaluating patients receiving first-line crizotinib.ResultsFourteen studies met the eligibility criteria and were considered feasible for MA. For the primary analysis, the pooled ORR (N = 9 studies) was 70.6 % (95 % confidence interval [CI]: 57.0, 81.3), median rwPFS was 14.5 months (N = 11 studies), and OS was 40.2 months (N = 9 studies). In the SA, the pooled ORR (N = 4 studies) was 81.1 % (95 % CI: 76.1,85.2) and the median rwPFS (N = 4 studies) and OS (N = 2 studies) were 18.1 and 60 months, respectively. All MAs were associated with significant heterogeneity (I2 > 25 %). Grade 3/4 AEs occurred in 18.7 % of patients (pooled estimate).ConclusionThe results from this study are consistent with clinical trial data and taken collectively, supports crizotinib as a safe and effective treatment across different lines of therapy in patients with ROS1 aNSCLC in the real-world setting.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.001 |
| Bibliometrics | 0.000 | 0.003 |
| 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) | 0.000 | 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 teacher head, 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".