A Phase II Study of the Central European Society of Anticancer-Drug Research (CESAR) Group: Results of an Open-Label Study of Gemcitabine plus Cisplatin with or without Concomitant or Sequential Gefitinib in Patients with Advanced or Metastatic Transitional Cell Carcinoma of the Urothelium
Bibliographic record
Abstract
INTRODUCTION: This phase II trial evaluated the efficacy and safety of the epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor, gefitinib, in combination with first-line chemotherapy in advanced urothelial cancer. METHODS: Chemotherapy-naïve patients with advanced or metastatic urothelial carcinoma were randomized 1:1:1 to receive six cycles of chemotherapy (gemcitabine 1,250 mg/m2 on days 1 and 8, and cisplatin 70 mg/m2 on day 1 of every cycle) concomitantly with gefitinib 250 mg/day (arm A); or with sequential gefitinib (arm B); or alone (arm C). The primary endpoint was the time to progression (TTP). RESULTS: A total of 105 patients received study treatment. Median TTP for arms A, B, and C were 6.1, 6.3, and 7.8 months, respectively. There were no significant differences between treatment arms for any outcomes measured. The most common adverse events were nausea and vomiting. CONCLUSION: Gefitinib in combination with chemotherapy did not improve efficacy in advanced urothelial 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 | 0.005 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| 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".