Trends in treatment patterns and survival outcomes in advanced non-small cell lung cancer: a Canadian population-based real-world analysis
Bibliographic record
Abstract
BACKGROUND: As part of the multi-country I-O Optimise research initiative, this population-based study evaluated real-world treatment patterns and overall survival (OS) in patients treated for advanced non-small cell lung cancer (NSCLC) before and after public reimbursement of immuno-oncology (I-O) therapies in Alberta province, Canada. METHODS: This study used data from the Oncology Outcomes (O2) database, which holds information for ~ 4.5 million residents of Alberta. Eligible patients were adults newly diagnosed with NSCLC between January 2010 and December 2017 and receiving first-line therapy for advanced NSCLC (stage IIIB or IV) either in January 2010-March 2016 (pre-I-O period) or April 2016-June 2019 (post-I-O period). Time periods were based on the first public reimbursement of I-O therapy in Alberta (April 2017), with a built-in 1-year lag time before this date to allow progression to second-line therapy, for which the I-O therapy was indicated. Kaplan-Meier methods were used to estimate OS. RESULTS: Of 2244 analyzed patients, 1501 (66.9%) and 743 (33.1%) received first-line treatment in the pre-I-O and post-I-O periods, respectively. Between the pre-I-O and post-I-O periods, proportions of patients receiving chemotherapy decreased, with parallel increases in proportions receiving I-O therapies in both the first-line (from < 0.5% to 17%) and second-line (from 8% to 47%) settings. Increased use of I-O therapies in the post-I-O period was observed in subgroups with non-squamous (first line, 15%; second line, 39%) and squamous (first line, 25%; second line, 65%) histology. First-line use of tyrosine kinase inhibitors also increased among patients with non-squamous histology (from 26% to 30%). In parallel with these evolving treatment patterns, median OS increased from 10.2 to 12.1 months for all patients (P < 0.001), from 11.8 to 13.7 months for patients with non-squamous histology (P = 0.022) and from 7.8 to 9.4 months for patients with squamous histology (P = 0.215). CONCLUSIONS: Following public reimbursement, there was a rapid and profound adoption of I-O therapies for advanced NSCLC in Alberta, Canada. In addition, OS outcomes were significantly improved for patients treated in the post-I-O versus pre-I-O periods. These data lend support to the emerging body of evidence for the potential real-world benefits of I-O therapies for treatment of patients with advanced 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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 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".