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Record W2038858587 · doi:10.2350/07-06-0303.1

Pathologist Interobserver Variability of Histologic Features in Childhood Brain Tumors: Results from the CCG-945 Study

2008· article· en· W2038858587 on OpenAlex
Floyd H. Gilles, C. Jane Tavaré, Edna B. Laurence, Peter C. Burger, Allan J. Yates, Ian F. Pollack, Jonathan L. Finlay

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePediatric and Developmental Pathology · 2008
Typearticle
Languageen
FieldMedicine
TopicRadiomics and Machine Learning in Medical Imaging
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsPathologyMedicine

Abstract

fetched live from OpenAlex

In the Children's Cancer Group-945 trial, study design allowed estimation of overall interpathologist observational agreement for 6 histologic features frequently used in brain tumor diagnoses. We evaluated agreement between pairs of 5 experienced neuropathologists, who had knowledge of the general diagnoses prior to slide readings. We performed this study in an attempt to further improve pathologist interinstitutional agreement. The features mitosis, necrosis, and giant cells had "fair" overall kappa estimates of reproducibility of around 0.5, while endothelial proliferation had only a "poor" overall kappa of 0.35. The Rogot reproducibility index averaged 0.5 for pleomorphism and hyperchromia. The upper bounds for the 10 pair summary agreement estimates were at best 0.65 ("good") for all 6 features. These relatively low-reproducibility estimates for the very small number of histologic features being assessed in tumors institutionally diagnosed as high-grade gliomas indicate that neuropathologists either used different operational definitions or interpreted them differently. We found that we could rank the histologic features from best to worst agreement among study pathologists as necrosis, giant cells, mitosis, endothelial proliferation, hyperchromic nuclei, and pleomorphic cells. We suggest that neuropathologists involved in multi-institutional studies of putative therapies not discard these traditional histologic features, but rather develop standardized operational definitions and measure their variability before beginning the studies. Only after such histologic feature variability studies are conducted will we have the data to identify specific histologic features of value to clinicians and researchers. Agreement and strict adherence to improved nonsubjective diagnostic criteria would improve histologic feature reliability and, consequently, their usefulness in studies.

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 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)0.004
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 score0.009
Threshold uncertainty score0.487

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
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 science0.0000.000
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 head0.014
GPT teacher head0.256
Teacher spread0.241 · 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