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Record W2128793721 · doi:10.1093/jnci/djh034

Revised Bethesda Guidelines for Hereditary Nonpolyposis Colorectal Cancer (Lynch Syndrome) and Microsatellite Instability

2004· article· en· W2128793721 on OpenAlexaff
Asad Umar, C. Richard Boland, Jonathan P. Terdiman, Sapna Syngal, Albert de la Chapelle, Josef Rüschoff, Richard Fishel, Noralene M. Lindor, Lawrence J. Burgart, Richard C. Hamelin, Stanley R. Hamilton, Robert A. Hiatt, Jeremy R. Jass, Annika Lindblom, Henry T. Lynch, Païvi Peltomäki, Scott D. Ramsey, Miguel A. Rodrı́guez-Bigas, Hans F. A. Vasen, Ernest T. Hawk, J. Carl Barrett, Andrew N. Freedman, Sudhir Srivastava

Bibliographic record

VenueJNCI Journal of the National Cancer Institute · 2004
Typearticle
Languageen
FieldMedicine
TopicGenetic factors in colorectal cancer
Canadian institutionsMcGill University
FundersNational Cancer Institute
KeywordsMicrosatellite instabilityLynch syndromeMedicineColorectal cancerCancerGenetic testingDNA mismatch repairOncologyGynecologyInternal medicineMicrosatelliteGeneticsBiology

Abstract

fetched live from OpenAlex

Hereditary nonpolyposis colorectal cancer (HNPCC), also known as Lynch syndrome, is a common autosomal dominant syndrome characterized by early age at onset, neoplastic lesions, and microsatellite instability (MSI). Because cancers with MSI account for approximately 15% of all colorectal cancers and because of the need for a better understanding of the clinical and histologic manifestations of HNPCC, the National Cancer Institute hosted an international workshop on HNPCC in 1996, which led to the development of the Bethesda Guidelines for the identification of individuals with HNPCC who should be tested for MSI. To consider revision and improvement of the Bethesda Guidelines, another HNPCC workshop was held at the National Cancer Institute in Bethesda, MD, in 2002. In this commentary, we summarize the Workshop presentations on HNPCC and MSI testing; present the issues relating to the performance, sensitivity, and specificity of the Bethesda Guidelines; outline the revised Bethesda Guidelines for identifying individuals at risk for HNPCC; and recommend criteria for MSI testing.

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)0.019
metaresearch head score (Gemma)0.070
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.032
Threshold uncertainty score0.098

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.070
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0070.005
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0050.002
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.0070.006

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 head0.094
GPT teacher head0.384
Teacher spread0.290 · 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 designNot applicable
Domainnot available
GenreMethods

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

Citations3,183
Published2004
Admission routes1
Has abstractyes

Explore more

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