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ORIGINAL RESEARCH article

Front. Oncol.
Sec. Thoracic Oncology
Volume 15 - 2025 | doi: 10.3389/fonc.2025.1436771

Development and validation of a predictive model for lymph node metastases in peripheral non-small cell lung cancer with a tumor diameter ≤ 2.0 cm and a consolidation-totumor ratio > 0.5

Provisionally accepted
Dongyu Li Dongyu Li 1,2Shaolei Li Shaolei Li 3,4Hongbing Zhang Hongbing Zhang 2Chunqiu Xia Chunqiu Xia 2Xiaoyong Nan Xiaoyong Nan 1HONGYU LIU HONGYU LIU 5Jun Chen Jun Chen 2,5*
  • 1 Yuncheng Central Hospital, Shanxi Medical University, Yuncheng, Shanxi, China
  • 2 Department of Lung Cancer Surgery, Tianjin Medical University General Hospital, Tianjin, China
  • 3 Beijing Cancer Hospital, Peking University, Beijing, Beijing Municipality, China
  • 4 Key Laboratory of Carcinogenesis and Translational Research, Beijing Cancer Hospital, Peking University, Beijing, Beijing Municipality, China
  • 5 Tianjin Lung Cancer Institute, Tianjin Key Laboratory of Lung Cancer Metastasis and Tumor Microenvironment, Tianjin Medical University General Hospital, Tianjin, China

The final, formatted version of the article will be published soon.

    Background: Precisely predicting lymph node metastasis (LNM) status is critical for the treatment of early non-small-cell lung cancer (NSCLC). In this study, we developed a LNM prediction tool for peripheral NSCLC with a tumor diameter ≤ 2.0 cm and consolidation-to-tumor ratio (CTR) > 0.5 to identify patients where segmentectomy could be applied.: Clinical characteristics were retrospectively collected from 435 patients with NSCLC. Logistic regression analysis of the clinical characteristics of this development cohort was used to estimate independent LNM predictors. A prediction model was then developed and externally validated using a validation cohort at another institution. Results: Four independent predictors (tumor size, CTR, pleural indentation, and carcinoembryonic antigen (CEA) values) were identified and entered into the model. The model showed good calibration (Hosmer-Lemeshow (HL) P value = 0.680) with an area under the receiver operating characteristic curve (AUC) = 0.890 (95% confidence interval (CI): 0.808-0.972) in the validation cohort. Conclusions: We developed and validated a novel and effective model that predicted the probability of LNM for individual patients with peripheral NSCLC who had a tumor diameter ≤ 2.0 cm and CTR > 0.5. This model could help clinicians make individualized clinical decisions.

    Keywords: lung cancer, non-small-cell lung cancer, Lymph node metastases, Preoperative workup, Prediction model

    Received: 29 May 2024; Accepted: 07 Jan 2025.

    Copyright: © 2025 Li, Li, Zhang, Xia, Nan, LIU and Chen. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Jun Chen, Department of Lung Cancer Surgery, Tianjin Medical University General Hospital, Tianjin, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.