Xu YH, Lu P, Gao MC, Wang R, Li YY, Guo RQ, Zhang WS, Song JX. Nomogram based on multimodal magnetic resonance combined with B7-H3mRNA for preoperative lymph node prediction in esophagus cancer. World J Clin Oncol 2024; 15(3): 419-433 [PMID: 38576593 DOI: 10.5306/wjco.v15.i3.419]
Corresponding Author of This Article
Jian-Xiang Song, MD, PhD, Chief Doctor, Chief Physician, Dean, Doctor, Surgeon, Department of Thoracic Surgery, Yancheng Third People's Hospital, The Affiliated Hospital 6 of Nantong University, No. 2 Xindu West Road, Yandu Street, Yandu District, Yancheng 224000, Jiangsu Province, China. jxsongycsy@163.com
Research Domain of This Article
Oncology
Article-Type of This Article
Prospective Study
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Xu YH, Lu P, Gao MC, Wang R, Li YY, Guo RQ, Zhang WS, Song JX. Nomogram based on multimodal magnetic resonance combined with B7-H3mRNA for preoperative lymph node prediction in esophagus cancer. World J Clin Oncol 2024; 15(3): 419-433 [PMID: 38576593 DOI: 10.5306/wjco.v15.i3.419]
Yan-Han Xu, Ming-Cheng Gao, Rui Wang, Yang-Yang Li, Rong-Qi Guo, Wei-Song Zhang, School of Clinical Sciences, Graduate School of Nantong University, Yancheng 226019, Jiangsu Province, China
Yan-Han Xu, Ming-Cheng Gao, Rui Wang, Yang-Yang Li, Rong-Qi Guo, Wei-Song Zhang, Jian-Xiang Song, Department of Thoracic Surgery, Yancheng Third People's Hospital, The Affiliated Hospital 6 of Nantong University, Yancheng 224000, Jiangsu Province, China
Peng Lu, Department of Imaging, Yancheng Third People's Hospital, The Affiliated Hospital 6 of Nantong University, Yancheng 224000, Jiangsu Province, China
Author contributions: Xu YH performed the majority of the writing, prepared the figures and tables; Xu YH, Lu P and Gao MC performed data accusation and writing; Wang R, Li YY, Guo RQ, and Zhang WS helped proofread the abbreviations and terminology in the manuscript; Song JX provided the input in writing the paper; Xu YH and Lu P designed the outline and coordinated the writing of the paper.
Supported byThe Yancheng Key Research and Development Program (Social Development), No. YCBE202324.
Institutional review board statement: The study was reviewed and approved by the Ethics Committee of Yancheng Third People's Hospital Institutional Review Board, Approval No. 2022-10.
Informed consent statement: Considering that the relevant examinations in this study do not pose significant physical or harm to the patients' interests, the requirement for obtaining informed consent from the patients has been waived by the committee.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Data sharing statement: Technical appendix, statistical code, and dataset available from the corresponding author at jxsongycsy@163.com.
Corresponding author: Jian-Xiang Song, MD, PhD, Chief Doctor, Chief Physician, Dean, Doctor, Surgeon, Department of Thoracic Surgery, Yancheng Third People's Hospital, The Affiliated Hospital 6 of Nantong University, No. 2 Xindu West Road, Yandu Street, Yandu District, Yancheng 224000, Jiangsu Province, China. jxsongycsy@163.com
Received: November 19, 2023 Peer-review started: November 19, 2023 First decision: January 9, 2024 Revised: January 15, 2024 Accepted: February 6, 2024 Article in press: February 6, 2024 Published online: March 24, 2024 Processing time: 124 Days and 0 Hours
Abstract
BACKGROUND
Accurate preoperative prediction of lymph node metastasis (LNM) in esophageal cancer (EC) patients is of crucial clinical significance for treatment planning and prognosis.
AIM
To develop a clinical radiomics nomogram that can predict the preoperative lymph node (LN) status in EC patients.
METHODS
A total of 32 EC patients confirmed by clinical pathology (who underwent surgical treatment) were included. Real-time fluorescent quantitative reverse transcription-polymerase chain reaction was used to detect the expression of B7-H3 mRNA in EC tissue obtained during preoperative gastroscopy, and its correlation with LNM was analyzed. Radiomics features were extracted from multi-modal magnetic resonance imaging of EC using Pyradiomics in Python. Feature extraction, data dimensionality reduction, and feature selection were performed using XGBoost model and leave-one-out cross-validation. Multivariable logistic regression analysis was used to establish the prediction model, which included radiomics features, LN status from computed tomography (CT) reports, and B7-H3 mRNA expression, represented by a radiomics nomogram. Receiver operating characteristic area under the curve (AUC) and decision curve analysis (DCA) were used to evaluate the predictive performance and clinical application value of the model.
RESULTS
The relative expression of B7-H3 mRNA in EC patients with LNM was higher than in those without metastasis, and the difference was statistically significant (P < 0.05). The AUC value in the receiver operating characteristic (ROC) curve was 0.718 (95%CI: 0.528-0.907), with a sensitivity of 0.733 and specificity of 0.706, indicating good diagnostic performance. The individualized clinical prediction nomogram included radiomics features, LN status from CT reports, and B7-H3 mRNA expression. The ROC curve demonstrated good diagnostic value, with an AUC value of 0.765 (95%CI: 0.598-0.931), sensitivity of 0.800, and specificity of 0.706. DCA indicated the practical value of the radiomics nomogram in clinical practice.
CONCLUSION
This study developed a radiomics nomogram that includes radiomics features, LN status from CT reports, and B7-H3 mRNA expression, enabling convenient preoperative individualized prediction of LNM in EC patients.
Core Tip: Accurate tumor-node-metastasis staging plays a critical role in devising treatment strategies for esophageal cancer (EC), particularly in assessing lymph node (LN) metastasis. Nevertheless, existing techniques for diagnosing LN in EC are currently constrained by limited accuracy. In light of this, our study endeavors to construct a clinical column chart that can enhance the assessment of LN status, furnishing a valuable point of reference for the diagnosis and treatment of EC.
