Survival, quality-adjusted survival, and other clinical end points in older advanced non-small-cell lung cancer patients treated with albumin-bound paclitaxel
Bibliographic record
Abstract
BACKGROUND: This analysis compared the quality-adjusted survival and clinical outcomes of albumin-bound paclitaxel+carboplatin (nab-PC) vs solvent-based paclitaxel+carboplatin (sb-PC) as first-line therapy in advanced non-small-cell lung cancer (NSCLC) in older patients. METHODS: Using age-based subgroup data from a randomised Phase-3 clinical trial, nab-PC and sb-PC were compared with respect to overall response rate (ORR), overall survival (OS), progression-free survival (PFS), quality of life (QoL), safety/toxicity, and quality-adjusted time without symptoms or toxicity (Q-TWiST) with ages ⩾60 and ⩾70 years as cut points. RESULTS: Among patients aged ⩾60 years (N=546), nab-PC (N=265) significantly increased ORR and prolonged OS, despite a non-significant improvement in PFS, vs sb-PC (N=281). Nab-PC improved QoL and was associated with less neuropathy, arthralgia, and myalgia but resulted in more anaemia and thrombocytopenia. Nab-PC yielded significant Q-TWiST benefits (11.1 vs 9.8 months; 95% CI of gain: 0.2-2.6), with a relative Q-TWiST gain of 10.8% (ranging from 6.4% to 15.1% in threshold analysis). In the ⩾70 years age group, nab-PC showed similar, but non-significant, ORR, PFS, and Q-TWiST benefits and significantly improved OS and QoL. CONCLUSION: Nab-PC as first-line therapy in older patients with advanced NSCLC increased ORR, OS, and QoL and resulted in quality-adjusted survival gains compared with standard sb-PC.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".