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Record W2014726838 · doi:10.1097/pas.0b013e31827f576a

Poor Interobserver Reproducibility in the Diagnosis of High-grade Endometrial Carcinoma

2013· article· en· W2014726838 on OpenAlexaffabout
C. Blake Gilks, Esther Oliva, Robert A. Soslow

Bibliographic record

VenueThe American Journal of Surgical Pathology · 2013
Typearticle
Languageen
FieldMedicine
TopicEndometrial and Cervical Cancer Treatments
Canadian institutionsUniversity of British ColumbiaVancouver General Hospital
Fundersnot available
KeywordsCarcinosarcomaMedicineCarcinomaSerous fluidSerous carcinomaClear cell carcinomaPTENOncologyInternal medicineClear cellNot Otherwise SpecifiedPathologyCancerBiology

Abstract

fetched live from OpenAlex

Patients with high-grade subtypes of endometrial carcinoma (grade 3 endometrioid, serous, clear cell, or carcinosarcoma) have a relatively poor prognosis. The specific subtype may be used to guide patient management, but there is little information on the reproducibility of subtype diagnosis in cases of high-grade endometrial carcinoma. Fifty-six cases diagnosed as a high-grade subtype of endometrial carcinoma were identified from the pathology archives of Vancouver General Hospital. All slides for each case were reviewed independently by 3 pathologists, who diagnosed the specific tumor subtype(s) and assigned the percentage of each subtype for mixed tumors. Agreement between observers was categorized as follows: major disagreement: (A) no consensus for low-grade endometrioid versus high-grade carcinoma (any subtype), or (B) no consensus with respect to the predominant high-grade subtype present; minor disagreement: consensus was reached about the cell type of the predominant component of a mixed tumor, but there was disagreement about the subtype of the minor component. A tissue microarray was constructed from these cases and immunostained for p16, ER, PR, PTEN, and p53. In 35 of 56 (62.5%) cases, there was agreement between all 3 reviewers regarding the subtype diagnosis of the exclusive (in pure tumors) or predominant (in mixed tumors) high-grade component. Of these cases, there was a minor disagreement (ie, disagreement about the minor high-grade component subtype in a mixed tumor) in 4 cases (4/56, 7.1%). In 20 of 56 (35.8%) cases there was a major disagreement; in 17 (30.4%) of these cases there was no consensus about the major subtype diagnosis, whereas in 3 (5.4%) cases there was disagreement about whether a component of high-grade endometrial carcinoma was present. In the final case, all 3 reviewers diagnosed the case as low-grade endometrioid carcinoma, disagreeing with the original diagnosis of high-grade carcinoma. The most frequent areas of disagreement were serous versus clear cell (7 cases) and serous versus grade 3 endometrioid (6 cases). Immunostaining results using the 5-marker immunopanel were then used to adjudicate in the 6 cases in which there was disagreement between reviewers with respect to serous versus endometrioid carcinoma, and these supported a diagnosis of serous carcinoma in 4 of 6 cases and endometrioid carcinoma in 2 of 6 cases. Pairwise comparison between the reviewers for the 20 cases classified as showing major disagreement was as follows: reviewer 1 and reviewer 2 agreed in 5/20 cases, reviewer 1 and reviewer 3 agreed in 7/20 cases, and reviewer 2 and reviewer 3 agreed in 8/20 cases, indicating that disagreements were not because of a single reviewer holding outlier opinions. Diagnostic consensus among 3 reviewers about the exclusive or major subtype of high-grade endometrial carcinoma was reached in only 35/56 (62.5%) cases, and in 4 of these cases there was disagreement about the minor component present. This poor reproducibility did not reflect systematic bias on the part of any 1 reviewer. There is a need for molecular tools to aid in the accurate and reproducible diagnosis of high-grade endometrial carcinoma subtype.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.109
metaresearch head score (Gemma)0.211
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Reproducibility · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.891
Threshold uncertainty score0.578

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1090.211
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.002
Science and technology studies0.0020.002
Scholarly communication0.0030.001
Open science0.0020.003
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.044
GPT teacher head0.308
Teacher spread0.264 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designObservational
DomainReproducibility
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

Citations412
Published2013
Admission routes2
Has abstractyes

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