Patient-reported outcomes in a phase II, North American study of alectinib in patients with ALK-positive, crizotinib-resistant, non-small cell lung cancer
Bibliographic record
Abstract
BACKGROUND: -positive non-small cell lung cancer. We describe patient-reported outcomes (PROs) from the NP28761 study. PATIENTS AND METHODS: PROs and health-related quality of life (HRQoL) benefits were assessed using two self-administered questionnaires (the European Organisation for Research and Treatment of Cancer 30-Item Quality of Life Questionnaire-Core (EORTC QLQ-C30), and the 13-item EORTC QLQ-lung cancer-specific module) at enrolment and every 6 weeks until week 66, disease progression or death. RESULTS: Clinically meaningful mean improvements (≥10 point change from baseline) were observed in 10 domains, including global health status (GHS), role and social functioning, fatigue, pain, dyspnoea, and appetite loss. A clinically meaningful improvement was observed in GHS from the first assessment (6 weeks) until week 60. Alectinib demonstrated a rapid effect, with a median time to symptom improvement, using the composite endpoint of cough, dyspnoea and pain in the chest, of 1.4 months (6.1 weeks) (95% CI 1.4 to 1.6) and a median time to symptom deterioration of 5.1 months (22.1 weeks) (95% CI 2.8 to 6.8). Patients with CNS metastases at baseline experienced comparable HRQoL over the duration of the study as patients without CNS metastases. Exploratory analysis showed that the occurrence of an objective response may be associated with a better HRQoL. CONCLUSIONS: Patients treated with alectinib in this phase II study achieved clinically meaningful improvements in HRQoL and symptoms and had delayed time to symptom deterioration.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".