Trends in Real-World Clinical Outcomes of Patients with Anaplastic Lymphoma Kinase (ALK) Rearranged Non-Small Cell Lung Cancer (NSCLC) Receiving One or More ALK Tyrosine Kinase Inhibitors (TKIs): A Cohort Study in Ontario, Canada
Bibliographic record
Abstract
The treatment landscape for patients with advanced ALK-positive NSCLC has rapidly evolved following the approval of several ALK TKIs in Canada. However, public funding of ALK TKIs is mostly limited to the first line treatment setting. Using linked provincial health administrative databases, we examined real-world outcomes of patients with advanced ALK-positive NSCLC receiving ALK TKIs in Ontario between 1 January 2012 and 31 December 2021. Demographic, clinical characteristics and treatment patterns were summarized using descriptive statistics. Kaplan–Meier analysis was performed to evaluate progression-free survival (PFS) and overall survival (OS) among the treatment groups. A total of 413 patients were identified. Patients were administered alectinib (n = 154), crizotinib (n = 80), or palliative-intent chemotherapy (n = 55) in the first-line treatment. There was a significant difference in first-line PFS between the treatment groups. The median PFS (mPFS) was not reached for alectinib (95% CI, 568 days—not reached), compared to 8.2 months (95% CI, 171–294 days) for crizotinib (HR = 0.34, p < 0.0001) and 2.4 months (95% CI, 65–100 days) for chemotherapy (HR = 0.14, p < 0.0001). There was no significant difference in first-line OS between the treatment groups. In patients who received more than one line of treatment, there was a significant difference in mOS between patients who received two or more lines of ALK TKIs compared to those who received one line of ALK TKI (mOS = 55 months (95% CI, 400–987 days) and 26 months (95% CI, 1448–2644 days), respectively, HR = 4.64, p < 0.0001). This study confirms the effectiveness of ALK TKIs in real-world practice and supports the potential benefit of multiple lines of ALK TKI on overall survival in patients with ALK-positive NSCLC.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".