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Record W2161989604 · doi:10.1001/jama.293.16.1979

Lower Cancer Incidence in Amsterdam-I Criteria Families Without Mismatch Repair Deficiency

2005· article· en· W2161989604 on OpenAlexaff
Noralane M. Lindor, Kari G. Rabe, Gloria M. Petersen, Robert W. Haile, Graham Casey, John A. Baron, Steve Gallinger, Bharati Bapat, Melyssa Aronson, John L. Hopper, Jeremy R. Jass, Loı̈c Le Marchand, John Grove, John D. Potter, Polly A. Newcomb, Jonathan P. Terdiman, Peggy Conrad, G. Möslein, Richard M. Goldberg, Argyrios Ziogas, Hoda Anton‐Culver, Mariza de Andrade, Kim Siegmund, Stephen N. Thibodeau, Daniela Seminara

Bibliographic record

VenueJAMA · 2005
Typearticle
Languageen
FieldMedicine
TopicGenetic factors in colorectal cancer
Canadian institutionsMcGill UniversityUniversity of Toronto
FundersNational Cancer Institute
KeywordsMedicineIncidence (geometry)Lynch syndromeColorectal cancerCancerEpidemiologyPopulationDNA mismatch repairInternal medicineConfidence intervalOncologyGynecology

Abstract

fetched live from OpenAlex

CONTEXT: Approximately 60% of families that meet the Amsterdam-I criteria (AC-I) for hereditary nonpolyposis colorectal cancer (HNPCC) have a hereditary abnormality in a DNA mismatch repair (MMR) gene. Cancer incidence in AC-I families with MMR gene mutations is reported to be very high, but cancer incidence for individuals in AC-I families with no evidence of an MMR defect is unknown. OBJECTIVE: To determine if cancer risks in AC-I families with no apparent deficiency in DNA MMR are different from cancer risks in AC-I families with DNA MMR abnormalities. DESIGN, SETTING, AND PARTICIPANTS: Identification (1997-2001) of 161 AC-I pedigrees from multiple population- and clinic-based sources in North America and Germany, with families grouped into those with (group A) or without (group B) MMR deficiency by tumor testing. A total of 3422 relatives were included in the analyses. MAIN OUTCOME MEASURES: Cancer incidence in groups A and B (excluding the 3 affected members used to define each pedigree as AC-I) and computed age- and sex-adjusted standardized incidence ratios (SIRs) using Surveillance, Epidemiology, and End Results data. RESULTS: Group A families from both population- and clinic-based series showed increased incidence of the HNPCC-related cancers. Group B families showed increased incidence only for colorectal cancer (SIR, 2.3; 95% confidence interval, 1.7-3.0) and to a lesser extent than group A (SIR, 6.1; 95% confidence interval, 5.2-7.2) (P<.001). CONCLUSIONS: Families who fulfill AC-I criteria but who have no evidence of a DNA MMR defect do not share the same cancer incidence as families with HNPCC-Lynch syndrome (ie, hereditary MMR deficiency). Relatives in such families have a lower incidence of colorectal cancer than those in families with HNPCC-Lynch syndrome, and incidence may not be increased for other cancers. These families should not be described or counseled as having HNPCC-Lynch syndrome. To facilitate distinguishing these entities, the designation of "familial colorectal cancer type X" is suggested to describe this type of familial aggregation of colorectal cancer.

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)0.001
metaresearch head score (Gemma)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.019
GPT teacher head0.316
Teacher spread0.297 · 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

Citations546
Published2005
Admission routes1
Has abstractyes

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