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Record W2164212079 · doi:10.1093/jnci/djr153

DNA Mismatch Repair Status and Colon Cancer Recurrence and Survival in Clinical Trials of 5-Fluorouracil-Based Adjuvant Therapy

2011· article· en· W2164212079 on OpenAlexaff
Frank A. Sinicrope, Nathan R. Foster, Stephen N. Thibodeau, Silvia Marsoni, G Monges, Roberto Labianca, Greg Yothers, Carmen J. Allegra, Malcolm J. Moore, Steven Gallinger, Daniel J. Sargent

Bibliographic record

VenueJNCI Journal of the National Cancer Institute · 2011
Typearticle
Languageen
FieldMedicine
TopicGenetic factors in colorectal cancer
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health Network
FundersNational Cancer Institute
KeywordsMedicineInternal medicineMicrosatellite instabilityColorectal cancerOncologyHazard ratioAdjuvant therapyProportional hazards modelDNA mismatch repairPopulationFluorouracilUnivariate analysisCancerConfidence intervalMultivariate analysisBiology

Abstract

fetched live from OpenAlex

BACKGROUND: Approximately 15% of colorectal cancers develop because of defective function of the DNA mismatch repair (MMR) system. We determined the association of MMR status with colon cancer recurrence and examined the impact of 5-fluorouracil (FU)-based adjuvant therapy on recurrence variables. METHODS: We included stage II and III colon carcinoma patients (n = 2141) who were treated in randomized trials of 5-FU-based adjuvant therapy. Tumors were analyzed for microsatellite instability by polymerase chain reaction and/or for MMR protein expression by immunohistochemistry to determine deficient MMR (dMMR) or proficient MMR (pMMR) status. Associations of MMR status and/or 5-FU-based treatment with clinicopathologic and recurrence covariates were determined using χ(2) or Fisher Exact or Wilcoxon rank-sum tests. Time to recurrence (TTR), disease-free survival (DFS), and overall survival (OS) were analyzed using univariate and multivariable Cox models, with the latter adjusted for covariates. Tumors showing dMMR were categorized by presumed germline vs sporadic origin and were assessed for their prognostic and predictive impact. All statistical tests were two-sided. RESULTS: In this study population, dMMR was detected in 344 of 2141 (16.1%) tumors. Compared with pMMR tumors, dMMR was associated with reduced 5-year recurrence rates (33% vs 22%; P < .001), delayed TTR (P < .001), and fewer distant recurrences (22% vs 12%; P < .001). In multivariable models, dMMR was independently associated with delayed TTR (hazard ratio = 0.72, 95% confidence interval = 0.56 to 0.91, P = .005) and improved DFS (P = .035) and OS (P = .031). In stage III cancers, 5-FU-based treatment vs surgery alone or no 5-FU was associated with reduced distant recurrence for dMMR tumors (11% vs 29%; P = .011) and reduced recurrence to all sites for pMMR tumors (P < .001). The dMMR tumors with suspected germline mutations were associated with improved DFS after 5-FU-based treatment compared with sporadic tumors where no benefit was observed (P = .006). CONCLUSIONS: Patients with dMMR colon cancers have reduced rates of tumor recurrence, delayed TTR, and improved survival rates, compared with pMMR colon cancers. Distant recurrences were reduced by 5-FU-based adjuvant treatment in dMMR stage III tumors, and a subset analysis suggested that any treatment benefit was restricted to suspected germline vs sporadic tumors.

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)0.014
metaresearch head score (Gemma)0.029
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 score0.014
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.029
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
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 head0.314
GPT teacher head0.462
Teacher spread0.148 · 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

Citations529
Published2011
Admission routes1
Has abstractyes

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