The Role of Adjuvant Chemotherapy before Osimertinib in Epidermal Growth Factor Receptor Mutant Resected Non-Small Cell Lung Cancer and Communicating It to Patients
Bibliographic record
Abstract
Patients with radically resected stage II and III NSCLC are exposed to a high risk of disease recurrence. Thus, adjuvant cisplatin-based chemotherapy is routinely offered to this patient population, although it results in an absolute increase in 5-year survival rate of only 4%. This modest improvement in survival rate makes it challenging to communicate to our patients about the decision to be treated with adjuvant chemotherapy or not. Nowadays, the decision to administer adjuvant chemotherapy or not in resected NSCLC is almost never completely shared with patients because its role is very difficult to explain. The risk-benefit ratio becomes clearly unfavourable in elderly and unfit patients. Recently, the phase III ADAURA trial demonstrated a clinically significant disease-free survival and overall survival benefit with adjuvant osimertinib (with or without adjuvant chemotherapy) versus a placebo in EGFR-mutated stage IB-IIIA resected NSCLC. In this patient population, the decision to administer chemotherapy or not is much more challenging given the great benefit offered by osimertinib alone. Thus, it is time now to improve our communication tools to explain the role of adjuvant chemotherapy to our patients, especially in the EGFR-mutated population, in order to undertake real shared decision making in a clinical context in which the opportunity to administer toxic chemotherapy is debatable and subjective.
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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 | 0.006 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 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".