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Record W2401884997 · doi:10.1007/s00345-016-1848-9

Promising role of preoperative neutrophil-to-lymphocyte ratio in patients treated with radical nephroureterectomy

2016· article· en· W2401884997 on OpenAlexaff
Mihai Dorin Vartolomei, Romain Mathiéu, Vitaly Margulis, José A. Karam, Morgan Rouprêt, Ilaria Lucca, Aurélie Mbeutcha, Christian Seitz, Pierre I. Karakiewicz, Harun Fajković, Christopher G. Wood, Alon Z. Weizer, Jay D. Raman, Nathalie Rioux‐Leclercq, Andrea Haitel, Karim Bensalah, Michael Rink, Alberto Briganti, Évanguelos Xylinas, Shahrokh F. Shariat

Bibliographic record

VenueWorld Journal of Urology · 2016
Typearticle
Languageen
FieldMedicine
TopicInflammatory Biomarkers in Disease Prognosis
Canadian institutionsUniversité de MontréalMcGill University Health Centre
FundersMedizinische Universität WienEuropean Association of UrologyUniversität Wien
KeywordsMedicineNeutrophil to lymphocyte ratioLymphovascular invasionInternal medicineProportional hazards modelLymphadenectomyOncologyRetrospective cohort studyNephrologyCohortCancerPathologicalT-stageUrologyMetastasisLymphocyte

Abstract

fetched live from OpenAlex

OBJECTIVE: Several retrospective studies with small cohorts reported neutrophil-to-lymphocyte ratio (NLR) as a prognostic marker in upper tract urothelial carcinoma (UTUC) following radical nephroureterectomy (RNU). We aimed at validating the predictive and prognostic role of NLR in a large multi-institutional cohort. METHODS: Preoperative NLR was assessed in a multi-institutional cohort of 2477 patients with UTUC treated with RNU. Altered NLR was defined by a ratio >2.7. Logistic regression analyses were performed to assess the association between NLR and lymph node metastasis, muscle-invasive and non-organ-confined disease. The association of altered NLR with recurrence-free survival (RFS) and cancer-specific survival (CSS) was evaluated using Cox proportional hazards regression models. RESULTS: Altered NLR was observed in 1428 (62.8 %) patients and associated with more advanced pathological tumor stage, lymph node metastasis, lymphovascular invasion, tumor necrosis and sessile tumor architecture. In a preoperative model that included age, gender, tumor location and architecture, NLR was an independent predictive factor for the presence of lymph node metastasis, muscle-invasive and non-organ-confined disease (p < 0.001). Within a median follow-up of 40 months (IQR 20-76 months), 548 (24.1 %) patients experienced disease recurrence and 453 patients (19.9 %) died from their cancer. Compared to patients with normal NLR, those with altered NLR had worse RFS (0.003) and CSS (p = 0.002). In multivariable analyses that adjusted for the effects of standard clinicopathologic features, altered NLR did not retain an independent value. In the subgroup of patients treated with lymphadenectomy in addition to RNU, NLR was independently associated with CSS (p = 0.03). CONCLUSION: In UTUC, preoperative NLR is associated with adverse clinicopathologic features and independently predicts features of biologically and clinically aggressive UTUC such as lymph node metastasis, muscle-invasive or non-organ-confined status. NLR may help better risk stratify patients with regard to lymphadenectomy and conservative therapy.

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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.006
GPT teacher head0.228
Teacher spread0.222 · 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

Citations69
Published2016
Admission routes1
Has abstractyes

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