Is EGFR expression altered following postoperative chemotherapy for colorectal adenocarcinoma?
Bibliographic record
Abstract
BACKGROUND: There is immunohistochemical evidence to suggest that expression of epidermal growth factor receptor (EGFR) in primary colorectal adenocarcinoma predicts its expression in recurrent disease. This study investigates whether postoperative chemotherapy affects the degree of concordance between EGFR statuses of the two tumors. METHODS: Thirty-three patients were identified from the files of Sunnybrook Health Sciences Center from July 1994 to June 2005. All patients had resection of their primary tumors and their distant recurrences. Eighteen patients received postoperative chemotherapy, 3 of which also received postoperative radiation therapy. Representative primary and recurrent tumor sections were stained using mouse anti-EGFR antibodies and only membranous staining of malignant cells was recorded. Results were reported as negative (no staining), 1+ (positivity in <50% of cells) or 2+ (positivity in >50% of cells). RESULTS: EGFR immunostaining in the 15 patients, who received no postoperative chemotherapy, was decreased in 3 recurrences, remained the same in 10 and increased in 2. In the group of 18 patients who received postoperative chemotherapy, EGFR immunostaining was decreased in 6 recurrences, remained the same in 9 and increased in 3 (p = 0.6598). In patients who received postoperative chemotherapy, the odds ratio for a recurrence to show lower levels of EGFR immunostaining compared to its originally resected primary was 4.75 (CI = 0.94-26.73). CONCLUSION: These preliminary data suggest that recurrences following postoperative chemotherapy are likely to have lower levels of EGFR expression compared to cases who receive no chemotherapy. Although the difference of immunostaining profiles between the two groups was not statistically significant, this observation might impact the management of these patients by targeted biologic therapies and its practical implications need further validation in larger series.
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How this classification was reachedexpand
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) | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".