Patient-Reported Symptoms and Impact of Treatment With Osimertinib Versus Chemotherapy in Advanced Non–Small-Cell Lung Cancer: The AURA3 Trial
Bibliographic record
Abstract
Purpose Capturing patient-reported outcome data is important for evaluating the overall clinical benefits of new cancer therapeutics. We assessed self-reported symptoms of advanced non-small-cell lung cancer in patients treated with osimertinib or chemotherapy in the AURA3 phase III trial. Patients and Methods Patients completed the European Organisation for Research and Treatment of Cancer 13-item Quality of Life Questionnaire-Lung Cancer Module (EORTC QLQ-LC13) questionnaire on disease-specific symptoms and the EORTC 30-item Core Quality of Life Questionnaire (EORTC QLC-C30) on general cancer symptoms, functioning, global health status/quality of life. We assessed differences between treatments in time to deterioration of individual symptoms and odds of improvement (a deterioration or improvement was defined as a change in score from baseline of ≥ 10). Hazard ratios (HRs) were calculated using a log-rank test stratified by ethnicity; odds ratios (ORs) were assessed using logistic regression adjusted for ethnicity. Results At baseline, the questionnaires were completed by 82% to 88% of patients, and 30% to 70% had individual key symptoms. Time to deterioration was longer with osimertinib than with chemotherapy for cough (HR, 0.74; 95% CI, 0.53 to 1.05), chest pain (HR, 0.52; 95% CI, 0.37 to 0.73), and dyspnea (HR, 0.42; 95% CI, 0.31 to 0.58). The proportion of symptomatic patients with improvement in global health status/quality of life was higher with osimertinib (80 [37%] of 215) than with chemotherapy (23 [22%] of 105; OR, 2.11; 95% CI, 1.24 to 3.67; P = .007). Proportions were also higher for appetite loss (OR, 2.50; 95% CI, 1.31 to 4.84) and fatigue (OR, 1.96; 95% CI, 1.20 to 3.22). Conclusion Time to deterioration of key symptoms was longer with osimertinib than with chemotherapy, and a higher proportion of patients had improvement in global health status/quality of life, demonstrating improved patient outcomes with osimertinib.
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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 | 0.000 | 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".