Anti-angiogenic therapy in advanced non-small cell lung carcinoma (NSCLC): is there a role in subsequent lines of therapy?
Bibliographic record
Abstract
Early in 2014, Reck and colleagues published the results of the LUME Lung-1 trial in Lancet Oncology (1). This trial evaluated the addition of nintedanib, an oral triple angiokinase inhibitor or placebo, to standard second-line chemotherapy with docetaxel. The trial, conducted largely in European countries, randomized 1,314 patients to docetaxel plus nintedanib 200 mg twice daily, or docetaxel plus placebo. Treatment continued until disease progression, or unacceptable toxicity. Eligible patients had stage IIIB/IV or recurrent non-small cell lung carcinoma (NSCLC) that had progressed after first-line chemotherapy. Patients with contraindications to the use of VEGF-R directed therapy (untreated brain metastases, underlying major bleeding or thrombotic disorders, cavitatory lesions, lesions invading major blood vessels and a history of hemoptysis) were excluded. Prior therapy with bevacizumab was allowed, although fewer than 5% of patients in both arms had previously received bevacizumab. Stratification was based on Eastern Cooperative Oncology Group (ECOG) performance status (0 vs. 1), prior bevacizumab therapy (yes vs. no), squamous versus non squamous histology, and the presence of brain metastases (yes vs. no). The primary outcome was progression free survival (PFS).
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".