ORIGINAL RESEARCH article
Front. Oncol.
Sec. Gynecological Oncology
Volume 15 - 2025 | doi: 10.3389/fonc.2025.1562347
Predicting Lymphovascular Space Invasion in Early-Stage Cervical Squamous Cell Carcinoma Using Heart Rate Variability
Provisionally accepted
- 1Department of Clinical Medicine, Bengbu Medical College, Bengbu, Anhui Province, China
- 2Bengbu Medical College, Bengbu, Anhui Province, China
Select one of your emails
You have multiple emails registered with Frontiers:
Notify me on publication
Please enter your email address:
If you already have an account, please login
You don't have a Frontiers account ? You can register here
Background Accurate preoperative assessment of lymphovascular space invasion (LVSI) in patients with early-stage cervical squamous cell carcinoma (ECSCC) is clinically significant for guiding treatment decisions and predicting prognosis. However, current LVSI assessment of ECSCC mainly relies on the invasive method of pathological biopsy, which needs to be further improved in terms of convenience. The main objective of this study is to verify the value of preoperative heart rate variability (HRV) parameters in predicting ECSCC LVSI. Methods A total of 79 patients with ECSCC confirmed by postoperative pathology were enrolled in this study at the Department of Gynecologic Oncology of the First Affiliated Hospital of Bengbu Medical University. Patients were classified as LVSI-positive (LVSI+) or LVSI-negative (LVSI-) based on pathological examination. Preoperative 5-minute electrocardiogram (ECG) data were collected from all patients, and their HRV parameters were analysed, including 7 time-domain parameters, 5 frequency-domain parameters, and 2 nonlinear parameters. Ten HRV features were selected through univariate analysis, and a logistic model was constructed using age, body mass index, menopausal status, and mean heart rate to predict LVSI status. The model performance was evaluated by the area under the receiver operating characteristic curve (AUC), accuracy, precision, sensitivity, and specificity. Results The constructed model showed good predictive performance, with an AUC of 0.845 (95% CI: 0.761 - 0.930), sensitivity of 0.871, specificity of 0.750, precision of 0.690, and accuracy of 0.747. Conclusions The Logistic model constructed based on HRV features has a relatively good diagnostic performance in predicting the LVSI status of ECSCC, but further research is still needed through larger datasets, more features, and the combination of machine learning models.
Keywords: cervical cancer, Cervical squamous cell carcinoma, Heart rate variability, Lymphovascular space invasion, Autonomic Nervous System
Received: 20 Jan 2025; Accepted: 30 Jun 2025.
Copyright: © 2025 Fang, Liu, Song, Zhang, Shi, Liu and Zhang. 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:
Jian Liu, Bengbu Medical College, Bengbu, 233030, Anhui Province, China
Sai Zhang, Bengbu Medical College, Bengbu, 233030, Anhui Province, 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.