Real-World Pattern of Treatment and Clinical Outcomes of EGFR-Mutant Non-Small Cell Lung Cancer in a Single Academic Centre in Quebec
Bibliographic record
Abstract
The discovery of EGFR tyrosine kinase inhibitors (TKI) for the treatment of EGFR mutant (EGFRm) metastatic NSCLC is regarded as a landmark in lung cancer. EGFR-TKIs have now become a standard first-line treatment for EGFRm NSCLC. The aim of this retrospective cohort study is to describe real-world patterns of treatment and treatment outcomes in patients with EGFRm metastatic NSCLC who received EGFR-TKI therapy outside of clinical trials. One hundred and seventy EGFRm metastatic NSCLC patients were diagnosed and initiated on first-line TKI therapy between 2004 and 2018 at the Peter Brojde Lung Cancer Centre in Montreal. Following progression of the disease, 137 (80%) patients discontinued first-line treatment. Moreover, 80/137 (58%) patients received second-line treatment, which included: EGFR-TKIs, platinum-based, or single-agent chemotherapy. At the time of progression on first-line treatment, 73 patients were tested for the T790M mutation. Moreover, 30/73 (41%) patients were found to be positive for the T790M mutation; 62/80 patients progressed to second-line treatment and 20/62 were started on third-line treatment. The median duration of treatment was 11.5 (95% CI; 9.62-13.44) months for first-line treatment, and 4.4 (95% CI: 1.47-7.39) months for second-line treatment. Median OS from the time of diagnosis of metastatic disease was 23.5 months (95% CI: 16.9-30.1) and median OS from the initiation of EGFR-TKI was 20.6 months (95% CI: 13.5-27.6). We identified that ECOG PS ≤ 2, presence of exon 19 deletion mutation, and absence of brain metastases were associated with better OS. A significant OS benefit was observed in patients treated with osimertinib in second-line treatment compared to those who never received osimertinib. Overall, our retrospective observational study suggests that treatment outcomes in EGFRm NSCLC in real-world practice, such as OS and PFS, reflect the result of RCTs. However, given the few observational studies on real-world treatment patterns of EGFR-mutant NSCLC, this study is important for understanding the potential impact of EGFR-TKIs on survival outside of clinical trials. Further real-world studies are needed to characterize patient outcomes for emerging therapies, including first-line osimertinib use and combination of osimertinib with chemotherapy and potential future combination of osimertinib and novel anticancer drug, outside of a clinical trial setting.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".