Real-World Treatment Patterns and Survival in Stage IV Non-Small-Cell Lung Cancer in Canada
Bibliographic record
Abstract
Background: Almost half of all patients with non-small-cell lung cancer (nsclc) present with stage iv disease. The objective of the present study was to characterize treatment patterns and survival outcomes in patients with advanced nsclc. Methods: We conducted a longitudinal population-level study in patients diagnosed with stage iv nsclc in Ontario between 1 April 2010 and 31 March 2015, with follow-up to 31 March 2017 for overall survival and treatment sequence. Patients were stratified as nonsquamous or squamous histology. A sub-analysis was conducted for patients with nonsquamous histology who received targeted therapies, on the assumption that their tumours were EGFR mutation–positive (EGFRm+). Treatment patterns were determined, and survival was calculated from date of diagnosis to death or censoring. Results: Of 24,729 nsclc cases identified, stage iv disease was diagnosed in 49.2%, histology was nonsquamous in 10,103, and EGFRm+ was assumed in 508. Median patient age ranged from 69 to 72 years for the three cohorts. For patients with nonsquamous histology, palliative radiotherapy was the most frequently used first-line treatment (44.4%), followed by no treatment (26.7%) and chemotherapy (14.9%). In the EGFRm+ cohort, 75.6% received gefitinib as first- or second-line therapy, and almost half (47.4%) the 473 patients with squamous histology treated with first-line chemotherapy received cisplatin or carboplatin with gemcitabine. Median overall survival in the nonsquamous and squamous cohorts was 4.9 and 4.6 months respectively; it was 17.6 months for patients who were EGFRm+. Conclusions: Survival of patients with stage iv nsclc remains poor, with the exception of patients who are EGFRm+. Only 14.9% of patients received first-line chemotherapy; the mainstay of treatment was palliative radiotherapy.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 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".