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Multifocal extramural venous invasion detected with an elastin stain as a predictor of cancer-specific outcomes in stage I-III resected colorectal cancer (CRC).

2021· article· en· W3124012519 on OpenAlexaff
David P. Cyr, Richard Kirsch, Amanpreet Brar, Sameer Shivji, Mantaj S. Brar, Robert Gryfe, Helen MacRae, Erin Kennedy, James R. Connor, Carol J. Swallow, Ayşegül Akder

Bibliographic record

VenueJournal of Clinical Oncology · 2021
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Surgical Treatments
Canadian institutionsPrincess Margaret Cancer CentreSinai Health SystemBrampton Civic HospitalMount Sinai HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicineNomogramStage (stratigraphy)Proportional hazards modelHazard ratioStainColorectal cancerPathologyLog-rank testT-stageCancerOncologyRadiologyInternal medicineStainingConfidence interval

Abstract

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114 Background: ExtraMural Venous Invasion (EMVI) is considered an indicator of poor prognosis in patients who have undergone resection of primary CRC, but its use has not been widely adopted in staging systems or nomograms. Staining for elastin may facilitate the accurate detection of EMVI and minimize interobserver variability, as well as enable the assessment of specific features of EMVI including focality and size. We examined the prognostic potential of EMVI detected by elastin staining at a tertiary center that performs a high volume of CRC resections. Methods: This is a single-institution, observational study of consecutive patients who underwent resection of primary CRC between 01/2011 and 12/2016 (n=556). All pathology specimens were re-assessed by expert reviewers who were blinded to patient outcomes. Venous invasion was detected using an elastin trichrome stain and classified as IntraMural or ExtraMural. The number of VI foci, as well as the maximum foci width and length, were also determined. Disease-specific and recurrence-free survival (DSS, RFS) were estimated using the Kaplan-Meier method and group differences were assessed using the log-rank test. Cox proportional-hazard models were used to calculate hazard ratios (HR) and 95% CI. For the present analysis, patients with stage IV (n=86) CRC were excluded. Results: The cohort for analysis included 470 patients (264M, 206F; TNM 8th edition Stage I/II n=291; Stage III n=179) with a median follow-up time of 63 months (0.1-114). EMVI was detected in 33% of all cases (20% in Stage I/II vs. 55% in Stage III; p<0.0001). For the entire cohort, DSS and RFS at 5 years were 86% and 76%, respectively. The presence of EMVI was associated with significantly worse DSS and RFS at 5-years (73% and 54%) compared to patients with no VI (92% and 85%) or IMVI alone (93% and 89%; p<0.0001). The majority of EMVI was multifocal (69%) vs. unifocal (31%). Interestingly, multifocal EMVI was prognostic for worse 5-year DSS (65%), whereas unifocal EMVI was similar to the absence of EMVI (91% and 92%, respectively; p<0.0001). A Cox-proportional hazards model showed worsening DSS with increasing number of detected EMVI foci (1 focus: HR 1.1, 2-4 foci: HR 3.3, >4 foci: HR 7.9; p<0.0001). A similar trend was observed for RFS. Neither the maximum width or length of EMVI foci were prognostic of DSS or RFS. Conclusions: To our knowledge, the prognostic role of EMVI focality in CRC has not been previously explored. In this cohort of Stage I - III CRC patients, multifocal EMVI as assessed by elastin staining was a powerful predictor of cancer-specific death and recurrence-free survival. Elastin staining, which improves the accuracy and objectivity of EMVI detection, may allow validation of EMVI as an independent prognostic variable that should be incorporated into staging systems and nomograms.

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)0.002
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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
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)0.0010.000

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 head0.113
GPT teacher head0.459
Teacher spread0.346 · 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".

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Citations1
Published2021
Admission routes1
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