Phase II study of erlotinib (OSI-774) in patients with metastatic colorectal cancer
Bibliographic record
Abstract
Erlotinib (Tarceva, OSI-774), a potent epidermal growth factor receptor tyrosine kinase inhibitor (EGFR), was evaluated in a phase II study to assess its activity in patients with metastatic colorectal cancer. In all, 38 patients with metastatic colorectal cancer were treated with erlotinib at a continuous daily oral dose of 150 mg. Radiological evaluation was carried out every 8 weeks and tumour biopsies were performed before treatment and on day 8. Of 31 evaluable patients, 19 (61%) had progressive disease and 12 (39%) had stable disease (s.d.). The median time to progression for those patients having s.d. was 123 days (range 108-329 days). The most common adverse events were rash in 34 patients and diarrhoea in 23 patients. Correlative studies were conducted to investigate the effect of erlotinib on downstream signalling. Tumour tissue correlations were based on usable tissue from eight match paired tumour samples pre- and on therapy, and showed a statistically significant decrease in the median intensity of both pEGFR (P=0.008) and phospho-extracellular signal-regulated kinase (ERK) (P=0.008) a week after commencement of treatment. No other statistically significant change in tumour markers was observed. Erlotinib was well tolerated with the most common toxicities being rash and diarrhoea. More than one-third of evaluable patients had s.d. for a minimum of 8 weeks. Correlative studies showed a reduction in phosphorylated EGFR and ERK in tumour tissue post-treatment.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".