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Record W2030813163 · doi:10.1097/pgp.0b013e3182230d00

Pathologic Scoring of PTEN Immunohistochemistry in Endometrial Carcinoma is Highly Reproducible

2011· article· en· W2030813163 on OpenAlexaff
Karuna Garg, Russell R. Broaddus, Robert A. Soslow, Diana L. Urbauer, Douglas A. Levine, Bojana Djordjevic

Bibliographic record

VenueInternational Journal of Gynecological Pathology · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPI3K/AKT/mTOR signaling in cancer
Canadian institutionsUniversity of OttawaOttawa Hospital
FundersNational Cancer Institute
KeywordsPTENImmunohistochemistryConcordanceCarcinomaPathologyMedicineEndometrial cancerStainStainingCancerBiologyPI3K/AKT/mTOR pathwayInternal medicine

Abstract

fetched live from OpenAlex

Endometrial carcinomas show frequent PTEN-PI3K pathway abnormalities, and there are currently multiple trials focused on PI3K pathway inhibitors in patients with endometrial carcinoma. PTEN immunohistochemistry may help to select patients with potential for response to targeted therapy, making it important to develop and validate this stain in formalin-fixed, paraffin-embedded tissue. Immunohistochemistry for PTEN was performed and scored independently on 118 cases of endometrial carcinomas from 2 cancer centers using monoclonal DAKO 6H2.1 antibody. Cases were scored as positive, negative, or heterogeneous; reproducibility of PTEN staining and interpretation was assessed. Overall interobserver agreement was good (weighted κ=0.80), with 82% concordance, similar for nonendometrioid (81%) and endometrioid carcinomas (85%). Twenty-one of 118 cases showed discrepant results (17%) that resulted from differences in interpretation and not staining. Our study shows that evaluation of PTEN loss by immunohistochemistry is highly reproducible with the application of standard immunohistochemical techniques and simple scoring criteria.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.604

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.038
GPT teacher head0.298
Teacher spread0.260 · 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 designBench or experimental
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

Citations81
Published2011
Admission routes1
Has abstractyes

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