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Record W3160068387 · doi:10.1002/jso.26522

Prognostic importance of lymph node count and ratio in rectal cancer after neoadjuvant chemoradiotherapy: Results from a cross‐sectional study

2021· article· en· W3160068387 on OpenAlexfundno aff
Robin Detering, Vincent Meyer, Wernard A. A. Borstlap, Regina G. H. Beets‐Tan, Corrie A.M. Marijnen, Roel Hompes, Pieter J. Tanis, Henderik L. van Westreenen

Bibliographic record

VenueJournal of Surgical Oncology · 2021
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Surgical Treatments
Canadian institutionsnot available
FundersAllerganKWF KankerbestrijdingAllerGen
KeywordsMedicineTotal mesorectal excisionColorectal cancerLymph nodeInternal medicineChemoradiotherapyOncologyNeoadjuvant therapyStage (stratigraphy)Overall survivalCancerGastroenterologyBreast cancer

Abstract

fetched live from OpenAlex

BACKGROUND: The aim of this study was to determine the prognostic value of lymph node count (LNC) and lymph node ratio (LNR) in rectal cancer after neoadjuvant chemoradiotherapy (CRT). METHODS: Patients who underwent neoadjuvant CRT and total mesorectal excision (TME) for Stage I-III rectal cancer were selected from a cross-sectional study including 71 Dutch centres. Primary outcome parameters were disease-free survival (DFS) and overall survival (OS). Prognostic significance of LNC and LNR (cut-off values 0.15, 0.20, 0.30) was tested for different (sub)groups. RESULTS: From 2095 registered patients, 458 were included, of which 240 patients with LNC < 12 and 218 patients with LNC ≥ 12. LNC was not significantly associated with DFS (p = 0.35) and OS (p = 0.59). In univariable analysis, LNR was significantly associated with DFS and OS in the whole cohort and LNC subgroups, but not in multivariable analysis. CONCLUSIONS: LNC was not associated with long-term oncological outcome in rectal cancer patients treated with CRT, nor was LNR when corrected for N-stage. However, LNR might be used to identify subgroups of node-positive patients with a favourable outcome.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.018
Threshold uncertainty score0.590

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.027
GPT teacher head0.351
Teacher spread0.325 · 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 teacher head, 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

Citations8
Published2021
Admission routes1
Has abstractyes

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