Asian ethnicity and survival outcomes in advanced non-small cell lung cancer (NSCLC) patients receiving systemic therapy: A regional Canadian experience.
Bibliographic record
Abstract
e18081 Background: Recent studies in advanced NSCLC have identified Asian ethnicity as a favorable survival prognosticator, possibly attributed to the use of antiepidermal growth factor receptor (EGFR) agents. We investigate the validity of this finding in a regional, Canadian population in the anti-EGFR era. Methods: East/Southeast Asian-born patients newly diagnosed with advanced stage IIIB or IV NSCLC from 2002 to 2007 were identified via the Alberta Cancer Registry (Alberta, Canada). Retrospective chart reviews were performed to obtain relevant clinical and histological parameters. A control group consisting of Alberta-born, non-Asian patients was randomly selected and matched for age, gender, stage, and treatment type received. Patients incorrectly classified or who received non-palliative intent therapies were excluded. Statistical analyses were performed using SAS v9.1. Results: 197 Asian patients in total were identified. Of the 67 Asian patients and 67 controls receiving systemic therapy, median overall survival (OS) was significantly longer in the Asian group at 15.9 mo (95% CI: 11.5-20.2) vs 9.7 mo (95% CI: 8.4- 10.9) in the control group (HR = 1.84, 95% CI: 1.27-2.68, p = 0.001). Use of an EGFR tyrosine kinase inhibitor (TKI) during any line of treatment was associated with improved OS in both the Asian and control groups (20.8 mo, 95% CI: 10.3-31.3; vs 12.7 mo, 95% CI: 11.6-13.8), as compared with no EGFR TKI use (7.1 mo, 95% CI: 3.3-10.8; vs 9.0 mo, 95% CI: 8.4-9.6, respectively). On multivariate analysis, use of an EGFR TKI was associated with OS advantage in both groups, especially in the Asian group (HR = 3.90, 95% CI: 1.90-8.02, p = 0.0002). Conclusions: This regional, Canadian study demonstrates a survival advantage associated with Asian ethnicity in advanced NSCLC patients receiving systemic therapy in the anti-EGFR era, particularly associated with EGFR TKI use. These findings likely relate to the higher prevalence of EGFR mutations reported in this population. No significant financial relationships to disclose.
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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 | 0.002 |
| Science and technology studies | 0.001 | 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".