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A report on the review of archived osteosarcoma and EWING sarcoma specimens at the Biopathology Center, BONE Sarcoma Committee, Children’s Oncology Group.

2022· article· en· W4286294211 on OpenAlexaff
Sonja Chen, Archana Shenoy, Alyaa Al‐Ibraheemi, Jonathan Bush, Jessica L. Davis, Patrick J. Grohar, Odion Binitie, Mark Krailo, Damon R. Reed, Katherine A. Janeway

Bibliographic record

VenueJournal of Clinical Oncology · 2022
Typearticle
Languageen
FieldMedicine
TopicSarcoma Diagnosis and Treatment
Canadian institutionsB.C. Women's Hospital & Health Centre
Fundersnot available
KeywordsMedicineSarcomaBiorepositoryOsteosarcomaMedical physicsQuality assurancePathologyBioinformaticsBiobank

Abstract

fetched live from OpenAlex

11524 Background: The Children’s Oncology Group (COG) Biorepository at the Biopathology Center (BPC), Nationwide Children’s Hospital, Columbus, OH contains archived tumor specimens submitted for COG study protocols. The BPC repository is utilized for numerous biology study aims with the goal of improved understanding of tumor pathophysiology, and impacts future clinical trials design and patient care. BPC pathologists perform quality assurance (QA) reviews of archival material before biospecimens are released for study. Since QA reviews are not routinely included in the submission process into the BPC, the quality and utility of tissue is often unclear. Therefore, a pathology quality assurance review was conducted to explore the utility of future testing on banked formalin fixed paraffin embedded (FFPE) Ewing Sarcoma and Osteosarcoma specimens. Methods: The BPC staff retrieved archival tumor cases for review between 06/2020 and 1/2022. One hematoxylin and eosin-stained slide per FFPE tissue block was digitally scanned for whole slide image (WSI) analysis and uploaded with a de-identified pathology report on a virtual slide-viewing platform. Five board certified pediatric pathologists with sarcoma expertise (AA, JB, SC, AS, JD) designed a digital QA review form and performed reviews. The QA review data collection form included diagnosis, volume of viable tumor, decalcification techniques, ancillary molecular/cytogenetic studies and a comment box to include additional noteworthy information. Results: During the study period, of the 1379 digitally prepared cases, 486 case reviews were completed, totaling 1192 digital slides reviewed. Of the reviewed cases, 465 (95%) were concordant with the diagnosis and had variable volumes of viable tumor (scant to adequate), while 33 (7%) of cases had no viable tumor (extensive necrosis or no tumor on the slide) and 21 (4%) had an alternative diagnosis (e.g. tumor submitted as osteosarcoma, re-classified as a chondromyxoid fibroma). Of the reviewed concordant cases, 271 (58%) were consistent with OS, 187 (40%) were consistent with ES and 7 (2%) were consistent non-ES round cell sarcomas (e.g. BCOR or CIC- rearranged sarcomas). Conclusions: Over ninety percent of reviewed specimens passed QA review, whereas the remaining failed due to diagnostic discordance or lack of viable tumor. Among cases with diagnostic concordance, variable volumes of tumor were present, including cases with scant viable tumors. Although QA reviews are time consuming, these results suggest QA reviews at tissue submission could potentially improve tissue quality available and timeliness of sample delivery for research. In addition, it would provide an opportunity for follow-up with sites to request submission of higher quality specimens and mitigate storage of tissue without potential for future use.

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)0.012
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.026
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0110.005
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.009

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 head0.092
GPT teacher head0.411
Teacher spread0.319 · 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.

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

Citations2
Published2022
Admission routes1
Has abstractyes

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