Bibliographic record
Abstract
Several agents have been evaluated for the second-line treatment of patients with non-small cell lung cancer. The TAX 317 trial found that patients treated with docetaxel (Taxotere) 75 mg/m2 had significantly longer survival than those treated with best supportive care alone. In addition, symptom control was better for patients who received chemotherapy. The TAX 320 trial found that treatment with docetaxel 75 or 100 mg/m2 resulted in significantly higher response rates than treatment with vinorelbine (Navelbine) or ifosfamide (Mitoxana), and the 1-year survival rate was also significantly better for patients treated with docetaxel 75 mg/m2. A large randomized trial compared pemetrexed (LY-231514 or Alimta) 500 mg/m2 with docetaxel 75 mg/m2. Response and survival rates were similar in the two treatment arms, however, the toxicity profile of pemetrexed was superior to that of docetaxel with significantly less Grade 3/4 neutropenia and febrile neutropenia. Fewer patients in the pemetrexed arm required hospitalization. Topotecan (Hycamtin) 2.3 mg/m2/day orally for 5 days has been compared with docetaxel 75 mg/m2 in a large 800-patient study. The results of this trial are awaited. Gemcitabine (Gemzar) and irinotecan (Campto) have been evaluated both as single agents and in combination with each other and study results do not suggest that either of these drugs is superior to docetaxel or pemetrexed. The vinca alkaloid vinorelbine has proved to be inferior to docetaxel in a randomized trial. The epidermal growth factor receptor inhibitors gefitinib (ZD1839, Iressa) and erlotinib (CP-358774, OSI 774, Tarceva) have been evaluated in Phase II trials in the second- and third-line setting. Both drugs have demonstrated interesting response rates ranging from 10 to almost 20%. The results of placebo-controlled randomized trials of this family of drugs are awaited. In summary, several studies have now found a definite role for the second-line treatment of patients with non-small cell lung cancer.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".