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Abstract A016: Cascade Failure in Lynch Syndrome Diagnosis: A Single-Institution Analysis

2025· article· en· W4417203801 on OpenAlexaboutno aff
Gideon T. Dosunmu, Fabienne Ehivet, Hasiya Yusuf, Kim-Anh Nguyen, Mosunmoluwa Oyenuga, Oluwadunni E. Emiloju, Lindsay M. Hannan, Patrick S. Sullivan, Christine Stanislaw, Olatunji B. Alese

Bibliographic record

VenueClinical Cancer Research · 2025
Typearticle
Languageen
FieldMedicine
TopicGenetic factors in colorectal cancer
Canadian institutionsnot available
Fundersnot available
KeywordsLynch syndromeMLH1GermlineDNA mismatch repairGenetic testingGermline mutationMicrosatellite instability

Abstract

fetched live from OpenAlex

Abstract Early-onset colorectal cancer (EOCRC) and endometrial cancer (EC) are defining malignancies for Lynch syndrome (LS). Universal tumor screening with mismatch repair (MMR) immunohistochemistry (IHC) is now standard practice in these malignancies. Despite this, many patients still fail to complete genetic testing after abnormal MMR results. We reviewed deidentified data from 772 patients with CRC (n=565) and EC (n=207) from the Emory Lynch Syndrome Screening Network (LSSN) database (2013 to 2023). We evaluated age specific cascade performance and COVID-19 era changes. All patients underwent IHC for MLH1, MSH2, MSH6, and PMS2, with reflex BRAF V600E and MLH1 methylation testing performed as indicated. Outcomes included deficient MMR (dMMR) rates, germline testing referral, germline testing completion, and pathogenic variant detection by age (<50 vs ≥50 years) and COVID era (pre-2020 vs ≥2020). Among 119 EOCRC cases, IHC completion was 99% (99/100) with dMMR identified in 15% (15/99). For early-onset EC (n=19), IHC completion was 100% with dMMR in 21% (4/19). For CRC, dMMR rates increased from 12% (59/482) pre-COVID to 51% (41/80) post-COVID. This is likely due to case selection bias post COVID rather than true biologic shifts. EOCRC patients with dMMR had better cascade completion compared to older patients. Referral rates for germline testing were 73% (11/15) in EOCRC vs 17% (14/83) in older patients and germline testing 53% (8/15) in EOCRC vs 11% (9/83) in older patients. Pathogenic variants were detected in 63% (5/8) of tested EOCRC patients vs 44.4% (4/9) of older patients. Post COVID, CRC referrals increased to 36.6% vs 20.3% pre-COVID, but testing completion was largely unchanged (22% vs 17%). Among early-onset EC patients with dMMR, 75% (3/4) completed testing with no pathogenic variants identified. In contrast, older EC patients had 20% (15/74) referral rate and 8% (6/74) completed germline testing with no pathogenic findings. Overall, 84.4% (151 of 179) of dMMR patients across groups never completed germline testing. This is a major implementation gap given the high pathogenic yield among those tested. Systematic interventions are urgently needed to address cascade failures and ensure universal genetic evaluation for all dMMR patients. Citation Format: Gideon T. Dosunmu, Fabienne Ehivet, LePaige R. Godfrey, Hasiya E. Yusuf, Kim Nguyen, Mosunmoluwa Oyenuga, Oluwadunni E. Emiloju, Lindsay Hannan, Patrick S. Sullivan, Christine Stanislaw, Olatunji Alese. Cascade Failure in Lynch Syndrome Diagnosis: A Single-Institution Analysis [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: The Rise in Early-Onset Cancers—Knowledge Gaps and Research Opportunities; 2025 Dec 10-13; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2025;31(23_Suppl):Abstract nr A016.

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)0.002
metaresearch head score (Gemma)0.008
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 score0.007
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.185
GPT teacher head0.520
Teacher spread0.335 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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