Safety and efficacy analysis by histology of weekly nab-paclitaxel in combination with carboplatin as first-line therapy in patients (pts) with advanced non-small cell lung cancer (NSCLC).
Bibliographic record
Abstract
7592 Background: Treatment of advanced NSCLC differs by histology, with fewer options and poorer outcomes in pts with squamous histology. In a phase III trial of nab-paclitaxel (nab-P, 130 nm albumin-bound paclitaxel particles) + carboplatin (C) vs solvent-based paclitaxel (sb-P) + C, the primary endpoint of ORR was significantly improved from 25% to 33%, p = 0.005, with a 1-month improvement in OS (p = NS) and improved safety. This analysis evaluated efficacy and safety by histology. Methods: Pts with untreated stage IIIB/IV NSCLC were randomized 1:1 (stratified by age, histology, region, stage, and gender) to C AUC 6 day 1 and either nab-P 100 mg/m2 on days 1, 8, 15 or sb-P 200 mg/m2 day 1 q 21 days. ORR and PFS were determined by blinded centralized review. Results: In squamous pts, nab-P/C produced a significantly higher ORR (41% vs 24%, p < 0.001), similar PFS (5.6 vs 5.7 mo, HR: 0.865) and >1-month improvement in OS (10.7 vs 9.5 mo, HR: 0.890) vs sb-P/C (Table). nab-P/C was as effective as sb-P/C in nonsquamous pts for ORR (26% vs 25%, p = 0.808), PFS (6.9 vs 6.5 mo, HR: 0.933), and OS (13.1 vs 13.0 mo, HR: 0.950). In both squamous and nonsquamous pts, nab-P/C vs sb-P/C produced lower rates of grade 3/4 neuropathy (3% vs 11% and 3% vs 12%, respectively, p < 0.001 both), neutropenia (43% vs 51%, p = NS, and 50% vs 63%, p = 0.008), and higher but manageable rates of anemia (27% vs 4% and 28% vs 9%, p < 0.001 both) and thrombocytopenia (21% vs 7% and 16% vs 11%, p < 0.001 both). Conclusions: In pts with advanced NSCLC, nab-P/C demonstrated a favorable risk-benefit profile as a first-line therapy regardless of histology. Significantly improved ORR and a positive trend in OS were observed in pts with squamous histology. [Table: see text]
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".