Evidence map›Paper›PMID 41445740›Full record

ArticleFrontiers in immunology2025

Organ-specific role of neutrophil extracellular traps in shaping the postoperative thrombo-inflammatory niche in pancreatic ductal adenocarcinoma: a multi-model machine learning and mechanistic study.

Songping Cui, Di Wang, Shaocheng Lyu, Jincan Huang, Ren Lang, Jing Wang

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Article in Frontiers in immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Songping Cui *Department of Thoracic Surgery, Beijing Institute of Respiratory Medicine and Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China.
Di Wang *Department of Liver Transplantation, First Central Hospital of Tianjin Medical University, Tianjin, China.
Shaocheng Lyu *Department of Hepatobiliary and Pancreaticosplenic Surgery, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.
Jincan HuangDepartment of Hepatobiliary and Pancreaticosplenic Surgery, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.
Ren LangDepartment of Hepatobiliary and Pancreaticosplenic Surgery, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.
Jing WangDepartment of Thoracic Surgery, Beijing Institute of Respiratory Medicine and Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Neutrophil extracellular traps (NETs) play a crucial role in thrombosis formation and tumor progression. However, the association between NETs and portal vein thrombosis (PVT) is not well understood. Methods: We retrospectively and prospectively developed and validated a predictive model for postoperative PVT following radical surgery for pancreatic ductal adenocarcinoma (PDAC) from Jan. 2011 to Dec. 2022 and Jan. 2023 to Dec. 2023. 30 clinicopathological variables, including the novel biomarker NETs, were evaluated. 11 ML algorithms were compared based on several evaluation indexes including AUC. SHapley Additive exPlanations (SHAP) analysis was utilized for feature ranking and interpretability. Results: In the retrospective study, a total of 306 patients were included, among which 70 (22.9%) developed PVT. In the prospective study, a total of 64 patients were enrolled and the incidence of PVT was 25%. eXtreme gradient boosting (XGBoost) demonstrated superior discriminative performance among 11 evaluated ML-models. After feature reduction based on ranked feature importance, a final interpretable XGBoost model comprising 7 variables was established. This model accurately predicted postoperative PVT in both training (AUC = 0.906) and validation (AUC = 0.823) cohorts, and has been translated into a convenient tool to facilitate its utility in clinical settings. Conclusion: In patients with PDAC, higher NETs levels are correlated with an increased risk of developing PVT and are indicative of poor prognosis. Assessment of Cit-H3 and D-dimer levels may aid clinicians in predicting PVT.

Indexed as

Carcinoma, Pancreatic DuctalExtracellular TrapsMachine LearningPancreatic NeoplasmsPostoperative ComplicationsVenous ThrombosisAgedFemaleHumansMaleMiddle AgedNeutrophilsPortal VeinProspective StudiesRetrospective Studiesexplainable artificial intelligenceneutrophil extracellular trapspancreatic ductal adenocarcinomaportal vein thrombosisprognosis

Identifiers

PMID41445740
PMCPMC12722873

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.