Weekly nab-Paclitaxel in Combination With Carboplatin as First-Line Therapy in Patients With Advanced Non–Small-Cell Lung Cancer: Analysis of Safety and Efficacy in Patients With Diabetes
Bibliographic record
Abstract
PURPOSE: To examine outcomes in a phase 3 trial of nab-paclitaxel plus carboplatin (nab-P/C) versus solvent-based paclitaxel plus carboplatin (sb-P/C) in a subset of patients with advanced non-small-cell lung cancer (NSCLC) and diabetes. PATIENTS AND METHODS: on day 1, both with C at an area under the curve of 6 mg·min/mL on day 1 every 3 weeks. Overall response rate (ORR) and progression-free survival (PFS) were determined by blinded, independent, centralized review. P values were based on chi-square test for ORR and log-rank test for overall survival (OS) and PFS. RESULTS: Of the 1052 randomized patients in the phase 3 trial, 61 had diabetes according to prespecified terms (nab-P/C, 31; sb-P/C, 30). ORR for nab-P/C versus sb-P/C in this subset was 52% versus 27% (relative risk ratio, 1.935; P = .046), median PFS was 10.9 versus 4.9 months (hazard ratio, 0.420; P = .016), and median OS was 17.5 versus 11.1 months (hazard ratio, 0.550; P = .057). Treatment differences in PFS remained significant (P ≤ .036) after adjusting for histology, region, stage, race, and age and also remained significant in OS for histology (P = .039). Patients with diabetes experienced lower rates of grade 3 or higher neutropenia and peripheral neuropathy and higher rates of thrombocytopenia and anemia with nab-P/C versus sb-P/C. CONCLUSION: nab-P/C demonstrated improved efficacy and manageable tolerability in patients with advanced NSCLC and diabetes.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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".