Phase III Trial of Maintenance Gefitinib or Placebo After Concurrent Chemoradiotherapy and Docetaxel Consolidation in Inoperable Stage III Non–Small-Cell Lung Cancer: SWOG S0023
Bibliographic record
Abstract
PURPOSE: Early clinical studies with gefitinib showed promising efficacy and mild toxicity in patients with advanced non-small-cell lung cancer (NSCLC). Thus, gefitinib was an ideal agent to evaluate in a maintenance setting in stage III disease. PATIENTS AND METHODS: Untreated patients with stage III NSCLC, a performance score of 0 to 1, and adequate organ function were eligible. All patients received cisplatin 50 mg/m(2) on days 1 and 8 plus etoposide 50 mg/m(2) on days 1 to 5, every 28 days for two cycles with concurrent thoracic radiation (1.8- to 2-Gy fractions per day; total dose, 61 Gy) followed by three cycles of docetaxel 75 mg/m(2). Patients whose disease did not progress were randomly assigned to gefitinib 250 mg/d or placebo until disease progression, intolerable toxicity, or the end of 5 years. The planned sample size was 672 patients to confer power of 0.89 to detect a 33% increase over the expected median survival time of 21 months (one-sided P = .025, log-rank test). Random assignment was stratified by stage, histology, and measurable versus nonmeasurable disease. RESULTS: Enrollment began in July 2001. An unplanned interim analysis conducted in April 2005 rejected the alternative hypothesis of improved survival at the P = .0015 level for 243 randomly assigned patients. The study closed, and preliminary results were reported. Now, with a median follow-up time of 27 months, median survival time was 23 months for gefitinib (n = 118) and 35 months for placebo (n = 125; two-sided P = .013). The toxic death rate was 2% with gefitinib compared with 0% for placebo. CONCLUSION: In this unselected population, gefitinib did not improve survival. Decreased survival was a result of tumor progression and not gefitinib toxicity.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".