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A Risk-Scoring Model for Predicting Lymph Node Metastasis in Early Gastric Cancer Patients: a Retrospective Study and External Validation

Journal of Gastrointestinal Surgery volume 22, pages 1508–1515 (2018)Cite this article

Abstract

Background

The possibility of lymph node metastasis (LNM) is critical to the assessment of the indication for endoscopic submucosal dissection. Thus, the aim of this study is to identify the risk factors for LNM and construct a risk-scoring model for patients with early gastric cancer to guide treatment.

Methods

A retrospective examination of reports and studies carried out January 2000 and December 2014 was conducted. A risk-scoring model for predicting LNM was developed based on the data thus collected. In addition, the model is subject to verification and validation by three institutions.

Results

Of the 1029 patients, 228 patients (22%) had LNM. Multivariate analysis showed that female, depressed type, undifferentiated type, submucosa, tumor size, and lymphovascular invasion were significantly associated with LNM. An 11-point risk-scoring model was used to predict LNM risk. An area under the receiver operating characteristic (AUROC) of the risk-scoring model was plotted using the development set and the AUROC of the model [0.76 (95% CI 0.73–0.80)] to predict LNM risk. After internal and external validation, the AUROC curve for predicting LNM was 0.77 (95% CI 0.68–0.86), 0.82 (95% CI 0.72–0.91), and 0.82 (95% CI 0.70–0.94), respectively.

Conclusions

A risk-scoring model for predicting LNM was developed and validated. It could help with personalized care for patients with EGC.

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Author information

Affiliations

  1. Department of General Surgery, Zhejiang University School of Medicine Sir Run Run Shaw Hospital, No.3, East Qingchun Road, Hangzhou, 310016, Zhejiang, China

    Lihu Gu, Xinlong Li, Hepan Zhu, Xin Zhong, Junhai Pan & XianFa Wang

  2. Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China

    Manman Chen & Liya Kong

  3. Zhejiang University School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China

    Parikshit Asutosh Khadaroo

  4. Zhuji People’s Hospital, Shaoxing, Zhejiang, China

    Xueqiang Ma

Authors
  1. Lihu Gu
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  2. Manman Chen
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  3. Parikshit Asutosh Khadaroo
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  4. Xueqiang Ma
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  5. Liya Kong
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  6. Xinlong Li
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  7. Hepan Zhu
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  8. Xin Zhong
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  9. Junhai Pan
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  10. XianFa Wang
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Contributions

All authors helped to perform the research. Lihu Gu, Manman Chen, and Parikshit Asutosh Khadaroo manuscript writing; Xueqiang Ma and Liya Kong performing procedures and data analysis; Xinlong Li, Hepan Zhu, Xin Zhong, and Junhai Pan contribution to writing the manuscript; Xianfa Wang contribution to drafting conception and design.

Corresponding author

Correspondence to XianFa Wang.

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This article does not contain any studies with human or animal subjects performed by any of the authors.

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The authors declare that they have no conflict of interest.

Electronic Supplementary Material

Fig. S1
figure 2

Receiver operating characteristic curve of the risk-scoring model for the prediction of lymph node metastasis in early gastric cancer in the validation sets. A Validation set 1: Sir Run Run Shaw Hospital (area under the receiver operating characteristic (AUROC), 0.77 (95% CI: 0.68–0.86)). B Validation set 2: Hangzhou First People’s Hospital (AUROC, 0.82 (95% CI: 0.72–0.91)). C Validation set 3: Zhuji People’s Hospital (AUROC, 0.82 (95% CI: 0.70–0.94)) (GIF 220 kb)

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Table S1

Risk scores and percentage of positive lymph node metastasis in development and validation sets (DOCX 19 kb)

Table S2

The measurement results of Youden’s Index and corrected Youden’s Index in each score (DOCX 16 kb)

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Gu, L., Chen, M., Khadaroo, P.A. et al. A Risk-Scoring Model for Predicting Lymph Node Metastasis in Early Gastric Cancer Patients: a Retrospective Study and External Validation. J Gastrointest Surg 22, 1508–1515 (2018). https://doi.org/10.1007/s11605-018-3816-8

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  • DOI: https://doi.org/10.1007/s11605-018-3816-8

Keywords

  • Early gastric cancer
  • Lymph node metastasis
  • Risk-scoring model
  • Endoscopic submucosal dissection