Evaluation of Cost-Effectiveness of Adjuvant Osimertinib in Patients with Resected EGFR Mutation-Positive Non-small Cell Lung Cancer
Bibliographic record
Abstract
For many patients with resected epidermal growth factor receptor mutation-positive (EGFRm) non-small cell lung cancer (NSCLC), current standard of care (SoC) is adjuvant chemotherapy; however, disease recurrence remains high. Based on positive results from ADAURA (NCT02511106), adjuvant osimertinib was approved for treatment of resected stage IB‒IIIA EGFRm NSCLC. The aim was to assess the cost-effectiveness of adjuvant osimertinib in patients with resected EGFRm NSCLC. A five-health-state, state-transition model with time dependency was developed to estimate lifetime (38 years) costs and survival of resected EGFRm patients treated with adjuvant osimertinib or placebo (active surveillance), with/without prior adjuvant chemotherapy, using a Canadian Public Healthcare perspective. Transitions between health states were modeled using ADAURA and FLAURA (NCT02296125) data, Canadian life tables, and real-world data (CancerLinQ Discovery ® ). The model used a ‘cure’ assumption: patients remaining disease free for 5 years after treatment completion for resectable disease were deemed ‘cured.’ Health state utility values and healthcare resource usage estimates were derived from Canadian real-world evidence. In the reference case, adjuvant osimertinib treatment led to a mean 3.20 additional quality-adjusted life-years (QALYs; (11.77 vs 8.57) per patient, versus active surveillance. The modeled median percentage of patients alive at 10 years was 62.5% versus 39.3%, respectively. Osimertinib was associated with mean added costs of Canadian dollars (C$)114,513 per patient and a cost/QALY (incremental cost-effectiveness ratio) of C$35,811 versus active surveillance. Model robustness was demonstrated by scenario analyses. In this cost-effectiveness assessment, adjuvant osimertinib was cost-effective compared with active surveillance for patients with completely resected stage IB‒IIIA EGFRm NSCLC after SoC.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".