Erlotinib in the treatment of advanced pancreatic cancer
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Single agent gemcitabine has been the mainstay of therapy for advanced pancreatic cancer over the past decade. Multiple trials of newer chemotherapeutic agents both alone and in combination have yielded disappointing results, spurring the ongoing search for new agents and combinations in this aggressive malignancy. Inhibitors of the epidermal growth factor receptor (EGFR) have shown promising activity in multiple solid tumors types, and preclinical data support a role for EGFR inhibition in pancreatic cancer. A recent phase III study by the National Cancer Institute of Canada Clinical Trials Group (NCIC-CTG) demonstrated a significant survival benefit with the addition of the EGFR tyrosine kinase inhibitor, erlotinib, to gemcitabine chemotherapy for the first-line treatment of patients with advanced pancreatic cancer, becoming the first phase III study to demonstrate a survival benefit of combination therapy as well as targeted therapy in this disease. This article reviews the evidence supporting EGFR inhibition and the use of erlotinib in advanced pancreatic cancer as well as future implications of targeted therapy in this challenging malignancy.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it