Skip to main content

ORIGINAL RESEARCH article

Front. Oncol.
Sec. Thoracic Oncology
Volume 14 - 2024 | doi: 10.3389/fonc.2024.1477450

Development and Validation of a Nomogram for Predicting Histologic Subtypes of Subpleural Non-Small Cell Lung Cancer Using Ultrasound Parameters and Clinical Data

Provisionally accepted
Feng Mao Feng Mao 1,2Mengjun Shen Mengjun Shen 1Yi Zhang Yi Zhang 1Hongwei Chen Hongwei Chen 1Yang Cong Yang Cong 1Huiming Zhu Huiming Zhu 1Chunhong Tang Chunhong Tang 1Shengmin Zhang Shengmin Zhang 2*Yin Wang Yin Wang 1*
  • 1 Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, Shanghai Municipality, China
  • 2 The First Affiliated Hospital of Ningbo University, Ningbo, Zhejiang Province, China

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

    Aims: To develop and validate an individualized nomogram for differentiating the histologic subtypes (adenocarcinoma and squamous cell carcinoma) of subpleural non-small cell lung cancer (NSCLC) based on ultrasound parameters and clinical data. Methods: This study was conducted retrospectively between March 2018 and December 2019. Patients were randomly assigned to a development cohort (DC, n=179) and a validation cohort (VC, n=77). A total of 7 clinical parameters and 16 ultrasound parameters were collected. Least absolute shrinkage and selection operator regression analysis was employed to identify the most significant predictors utilizing a 10-fold cross-validation. The multivariate logistic regression model was applied to investigate the relevant factors. An individualized nomogram was then developed. Receiver operating characteristic (ROC) curve, calibration plot and decision curve analysis (DCA) were applied for model validation in both DC and VC.Results: Following the final regression analysis, gender, serum carcinoembryonic antigen, lesion size and perfusion defect in contrast-enhanced ultrasound were entered into the nomogram. The model showed moderate predictive ability, with an area under the ROC curve of 0.867 for DC and 0.838 for VC. The calibration curves of the model showed good agreement between actual and predicted probabilities. The ROC and DCA curves demonstrated that the nomogram exhibited a good predictive performance.We developed a nomogram that can predict the histologic subtypes of subpleural NSCLC. Both internal and external validation revealed optimal discrimination and calibration, indicating that the nomogram may have clinical utility. This model has the potential to assist clinicians in making treatment recommendations.

    Keywords: Non-small cell lung cancer, Subpleural pulmonary lesion, nomogram, ultrasound, contrast-enhanced ultrasound

    Received: 07 Aug 2024; Accepted: 16 Oct 2024.

    Copyright: © 2024 Mao, Shen, Zhang, Chen, Cong, Zhu, Tang, Zhang and Wang. 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:
    Shengmin Zhang, The First Affiliated Hospital of Ningbo University, Ningbo, Zhejiang Province, China
    Yin Wang, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, 200433, Shanghai Municipality, 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.