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Record W2141025284 · doi:10.1309/hv7v1mjxv8y8989w

Expression of Epidermal Growth Factor Receptor in Primary Colorectal Adenocarcinoma Predicts Expression in Recurrent Disease

2006· article· en· W2141025284 on OpenAlexaff
Mahmoud A. Khalifa, Corwyn Rowsell, Rebecca A. Gladdy, Yoo-Joung Ko, Sherif S. Hanna, Andy Smith, Calvin Law

Bibliographic record

VenueAmerican Journal of Clinical Pathology · 2006
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Treatments and Studies
Canadian institutionsSunnybrook Health Science Centre
Fundersnot available
KeywordsImmunostainingMedicineStainingPathologyAdenocarcinomaEpidermal growth factor receptorImmunohistochemistryPrimary tumorOdds ratioColorectal cancerOncologyInternal medicineCancerMetastasis

Abstract

fetched live from OpenAlex

We tested the usefulness of epidermal growth factor receptor (EGFR) immunostaining in primary colorectal adenocarcinoma as a predictor for EGFR status of tumor recurrences in 33 primary tumors and distant recurrences (July 1994 to June 2005). 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). Of 33 cases, 19 (58%) showed the same extent of immunopositivity in primary and recurrent tumors. Bivariate logistic regression analysis of primary tumors with 2+ vs those with negative or 1+ staining showed that the primary tumor status had a major predictive relationship with that of recurrence (odds ratio, of 45.99; confidence limit, 4.0-524.9; P = .0021). The difference between the median time to recurrence of primary tumors with the various degrees of staining was not statistically significant. Our reporting method provides a useful correlation between the staining profiles of primary colorectal adenocarcinoma and recurrent disease. It is exceptionally reliable in predicting immunopositivity of a recurrence when more than 50% of cells of the primary tumor are immunoreactive.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.566

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.028
GPT teacher head0.343
Teacher spread0.315 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations17
Published2006
Admission routes1
Has abstractyes

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