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Record W2061343866 · doi:10.1002/path.1453

MSI‐low, a real phenomenon which varies in frequency among cancer types

2003· article· en· W2061343866 on OpenAlexaff
Sarah Halford, Elinor J. Sawyer, Maryou Lambros, Patricia Gorman, Nicola MacDonald, Ian Talbot, William D. Foulkes, Cheryl Gillett, Diana M. Barnes, Lars A. Akslen, Kwok Lee, Ian Jacobs, Andrew M. Hanby, Trivadi S. Ganesan, Helga B. Salvesen, Walter F. Bodmer, Ian Tomlinson, Rebecca Roylance

Bibliographic record

VenueThe Journal of Pathology · 2003
Typearticle
Languageen
FieldMedicine
TopicGenetic factors in colorectal cancer
Canadian institutionsMcGill University
FundersCancer Research UKUniversity of Chicago
KeywordsMicrosatellite instabilityColorectal cancerMedicineOncologyInternal medicineBreast cancerOvarian carcinomasOvarian cancerCancerPathologyBiologyMicrosatelliteOvarian carcinomaGene

Abstract

fetched live from OpenAlex

This study assessed whether low-level microsatellite instability (MSI-L) is a phenomenon specific to colorectal cancers or is also present in other tumour types. Breast (grade III ductal and lobular), endometrial and ovarian carcinomas, as well as colorectal cancers, were analysed for MSI-L using eight microsatellite markers. The markers were selected from a panel that had previously been shown to be sensitive for the detection of MSI-L in colorectal cancers. It was found that MSI-L was present in 30 of 87 (35%) colorectal cancers, 2 of 59 (3%) grade III breast carcinomas, 1 of 35 (3%) lobular breast cancers, 16 of 50 (32%) endometrial cancers, and 9 of 34 (26%) ovarian cancers. These results suggest that MSI-L is a very rare occurrence in breast carcinomas, but does occur as a real phenomenon in colorectal, endometrial, and ovarian carcinomas, which are all part of the hereditary non-polyposis colon cancer (HNPCC) syndrome. PCR artefact was also found to masquerade as MSI-L; criteria for the assessment of MSI-L are suggested to eliminate this problem.

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)0.000
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 score0.169
Threshold uncertainty score0.675

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.017
GPT teacher head0.287
Teacher spread0.270 · 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

Citations56
Published2003
Admission routes1
Has abstractyes

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