Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Advertisement

Scientific Reports
  • View all journals
  • Search
  • My Account Login
  • Content Explore content
  • About the journal
  • Publish with us
  • Sign up for alerts
  • RSS feed
  1. nature
  2. scientific reports
  3. articles
  4. article
XGBoost and SHAP based lymph node ratio thresholds for predicting overall survival in stage I to IIIA NSCLC
Download PDF
Download PDF
  • Article
  • Open access
  • Published: 24 April 2026

XGBoost and SHAP based lymph node ratio thresholds for predicting overall survival in stage I to IIIA NSCLC

  • Yuanyuan Xiao1,2,
  • Xiaotao Xu3,
  • Wei Chen4,
  • Shancheng He1,2,
  • Baochang Xie1,2,
  • Wenqi Zhao1,2 &
  • …
  • Yuhui Xu5 

Scientific Reports (2026) Cite this article

  • 667 Accesses

  • 1 Altmetric

  • Metrics details

We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Subjects

  • Cancer
  • Oncology
  • Risk factors

Abstract

The lymph node ratio (LNR) may emerge as a more reliable prognostic indicator for non-small cell lung cancer (NSCLC). This study utilized data collected between 2010 and 2019 from the Surveillance, Epidemiology, and End Results (SEER) 17 registry research database. The cohort comprised patients diagnosed with stage I-IIIA non-small cell lung cancer (NSCLC) who had undergone surgical resection and had at least one lymph node examined. Overall survival was predicted using XGBoost, a robust tree-based ensemble algorithm, based on LNR, and prognostic LNR thresholds were determined using SHAP (SHapley Additive exPlanations) to interpret the model. Smooth-fit curves were also employed to determine the cutoff values for the lymph node ratio (LNR) in relation to mortality. Trend tests and Cox proportional hazards regression models were applied to evaluate the association between LNR and overall survival (OS). This investigation encompassed a total of 61,990 patients who met the criteria for inclusion. The cohort was stratified into three categories based on smooth-fitting curves and SHAP dependence plot: low (<0.1), medium (0.1≤,<0.4), and high (≥ 0.4) LNR groups. Kaplan-Meier curves illustrated that patients in the low LNR group exhibited superior overall survival compared to those in the medium and high LNR groups (P < 0.001). This trend was evident in all subgroup analyses. The Kaplan-Meier curves stratified by LNR groups demonstrate superior discriminatory power compared to those stratified by N-stage grouping. In the population of patients with NSCLC, an elevated LNR is linked to diminished OS. This relationship holds true across all stratified cohorts. Evaluation of LNR serves as a dependable prognostic marker for OS in patients with stage I-IIIA NSCLC undergoing radical surgery.

Similar content being viewed by others

Prognostic model for log odds of negative lymph node in locally advanced rectal cancer via interpretable machine learning

Article Open access 07 March 2025

Identification of a visualized web-based nomogram for overall survival prediction in patients with limited stage small cell lung cancer

Article Open access 11 September 2023

Evaluation of LNR and modified N stage systems for prognostic stratification of metastatic lymph nodes in stage III colorectal Cancer

Article Open access 21 April 2025

Acknowledgements

We hereby thank the participants for their time and energy in the data collection phase of SEER project.

Author information

Authors and Affiliations

  1. Department of Critical Care Medicine, Ganzhou Fifth People’s Hospital, Ganzhou, China

    Yuanyuan Xiao, Shancheng He, Baochang Xie & Wenqi Zhao

  2. Ganzhou Respiratory Disease Control Institute, Ganzhou, China

    Yuanyuan Xiao, Shancheng He, Baochang Xie & Wenqi Zhao

  3. Ganxian District Traditional Chinese Medicine Hospital, Ganzhou, China

    Xiaotao Xu

  4. Department of critical care medicine, Jiangxi Changzheng Hospital, Nanchang, Jiangxi, China

    Wei Chen

  5. Department of Pulmonary and Critial Care Medicine, Ganzhou People’s Hospital, Ganzhou, China

    Yuhui Xu

Authors
  1. Yuanyuan Xiao
    View author publications

    Search author on:PubMed Google Scholar

  2. Xiaotao Xu
    View author publications

    Search author on:PubMed Google Scholar

  3. Wei Chen
    View author publications

    Search author on:PubMed Google Scholar

  4. Shancheng He
    View author publications

    Search author on:PubMed Google Scholar

  5. Baochang Xie
    View author publications

    Search author on:PubMed Google Scholar

  6. Wenqi Zhao
    View author publications

    Search author on:PubMed Google Scholar

  7. Yuhui Xu
    View author publications

    Search author on:PubMed Google Scholar

Corresponding author

Correspondence to Yuhui Xu.

Ethics declarations

Competing interests

The authors declare no competing interests.

Ethics declarations

Review and approval by an ethics committee was not needed for this study because difficulties in identifying patients in SEER database.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary Material 1 (download TIF )

Supplementary Material 2 (download DOCX )

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Xiao, Y., Xu, X., Chen, W. et al. XGBoost and SHAP based lymph node ratio thresholds for predicting overall survival in stage I to IIIA NSCLC. Sci Rep (2026). https://doi.org/10.1038/s41598-026-47993-7

Download citation

  • Received: 14 October 2025

  • Accepted: 06 April 2026

  • Published: 24 April 2026

  • DOI: https://doi.org/10.1038/s41598-026-47993-7

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Keywords

  • LNR
  • Prediction
  • SEER
  • NSCLC
  • Survival Analysis
Download PDF

Advertisement

Explore content

  • Research articles
  • News & Comment
  • Collections
  • Subjects
  • Follow us on Facebook
  • Follow us on X
  • Sign up for alerts
  • RSS feed

About the journal

  • About Scientific Reports
  • Contact
  • Journal policies
  • Guide to referees
  • Calls for Papers
  • Editor's Choice
  • Journal highlights
  • Open Access Fees and Funding

Publish with us

  • For authors
  • Language editing services
  • Open access funding
  • Submit manuscript

Search

Advanced search

Quick links

  • Explore articles by subject
  • Find a job
  • Guide to authors
  • Editorial policies

Scientific Reports (Sci Rep)

ISSN 2045-2322 (online)

nature.com footer links

About Nature Portfolio

  • About us
  • Press releases
  • Press office
  • Contact us

Discover content

  • Journals A-Z
  • Articles by subject
  • protocols.io
  • Nature Index

Publishing policies

  • Nature portfolio policies
  • Open access

Author & Researcher services

  • Reprints & permissions
  • Research data
  • Language editing
  • Scientific editing
  • Nature Masterclasses
  • Research Solutions

Libraries & institutions

  • Librarian service & tools
  • Librarian portal
  • Open research
  • Recommend to library

Advertising & partnerships

  • Advertising
  • Partnerships & Services
  • Media kits
  • Branded content

Professional development

  • Nature Awards
  • Nature Careers
  • Nature Conferences

Regional websites

  • Nature Africa
  • Nature China
  • Nature India
  • Nature Japan
  • Nature Middle East
  • Privacy Policy
  • Use of cookies
  • Legal notice
  • Accessibility statement
  • Terms & Conditions
  • Your US state privacy rights
Springer Nature

© 2026 Springer Nature Limited

Nature Briefing: Cancer

Sign up for the Nature Briefing: Cancer newsletter — what matters in cancer research, free to your inbox weekly.

Get what matters in cancer research, free to your inbox weekly. Sign up for Nature Briefing: Cancer