Brief Report: Real-World Treatment Patterns and Clinical Outcomes for Patients With Advanced ALK-Rearranged NSCLC in British Columbia
Bibliographic record
Abstract
Introduction EML4-ALK rearrangements represent an oncogenic driver alteration in 5% of NSCLC cases. We aim to better understand real-world treatment patterns and outcomes of ALK fusion-positive (ALK+) patients with advanced-stage NSCLC. Methods We performed a retrospective population-based chart review of ALK+ patients with locally advanced or metastatic NSCLC in British Columbia (BC), Canada. Patients diagnosed from January 2014 to May 2023 were identified through the BC Cancer Genetics Laboratory database, and data were collected up to December 2023. Results A total of 216 patients with stage IIIB, IIIC, or IV ALK+ lung NSCLC were identified. Median age was 60 (range: 24–91) years, 151 (68.9%) had never smoked, and 95 (43.9%) were Asian. The median overall survival was 49.4 months with median follow-up time of 55.4 months. Majority of the cohort (n = 198, 91.7%) received palliative systemic therapy, all of which included at least one ALK tyrosine kinase inhibitor (TKI). The most common first-line regimen was alectinib (n = 97, 49.0%) followed by crizotinib (n = 84, 42.4%); only four and one patient received lorlatinib and brigatinib first line, respectively. Alectinib was frequently prescribed overall, with 80.3% of patients receiving it in any treatment line. Time to treatment discontinuation was significantly longer ( p < 0.0001) on first-line alectinib at 22.9 months as compared with 10.9 months for crizotinib. Conclusions Patients with ALK+ advanced NSCLC in BC have durable responses to ALK TKIs. Despite approval of all ALK TKIs for first-line use since 2021, alectinib is largely the favored agent in BC. Further real-world investigations can refine treatment strategies and shape policies around ALK TKIs for patients with ALK+ NSCLC.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".