Integrating comprehensive genomic sequencing of non-small cell lung cancer into a public healthcare system
Bibliographic record
Abstract
OBJECTIVES: Standard molecular testing for patients with stage IV non-small cell lung cancer (NSCLC) in the Canadian publicly funded health system includes single gene testing for EGFR, ALK, and ROS-1. Comprehensive genomic profiling (CGP) may broaden treatment options for patients. This study examined the impact of CGP in a publicly funded health system. METHODS: Consenting patients with stage IV NSCLC without known targetable alterations underwent CGP on diagnostic samples. Patients that had progressed on targeted therapy were also eligible. The CGP assay was a hybrid capture next generation sequencing (NGS) panel (Oncomine Comprehensive Assay Version 3, ThermoFisher). The number of actionable alterations, changes in treatment, clinical trial eligibility and costs as a result of CGP were evaluated and patient willingness-to-pay. RESULTS: Of 182 screened patients,134 (74%) had successful CGP testing. Twenty percent had received prior targeted therapy. Incremental actionable alterations were identified in 31% of patients. The most common novel targets identified were mutations in ERBB2 (exon 20 insertions), MET (exon 14 skipping) and KRAS (G12C). At data cut off (31/12/2020), 16% of patients had a change in treatment as a result of CGP. Additional clinical trial options were identified for 75% of patients. The incremental direct laboratory cost for CGP beyond public reimbursement for single gene tests was $747 CAD/case. CONCLUSION: CGP identifies additional actionable targets beyond single gene tests with a direct impact on patient treatment and increased clinical trial eligibility. These benefits highlight the value of CGP in patients with NSCLC in public health systems.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 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) | 0.000 | 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".