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 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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".