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Univariate Analysis and Principal Component Analysis of Preoperative Blood Indicators in Patients with Esophageal Squamous Cell Carcinoma

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Bio-inspired Computing: Theories and Applications (BIC-TA 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1160))

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Abstract

Esophageal Squamous Cell Carcinoma (ESCC) was one of the most common malignant tumors in the world, and it was in the middle and late stage. Surgery is the first choice for the treatment of ESCC, but the survival rate of patients is still very low. In this paper, it used the blood indicators of patients with ESCC to do univariate analysis, and we found out the influencing factors of survival rate of ESCC. Univariate Cox regression was used to analyze blood indexes and factors affecting survival or death of patients were screened out. Spearman and Pearson correlation analysis could determine whether screening factors were related to survival. Principal component analysis (PCA) was used to test whether screening factors contributed significantly to the survival or death of patients. The survival curve and progression-free survival curve of 5 factors were drawn after obtaining the threshold value by ROC.

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Acknowledgements

This work was supported in part by the National Key R and D Program of China for International S and T Cooperation Projects (2017YFE0103900), in part by the Joint Funds of the National Natural Science Foundation of China (U1804262), in part by the State Key Program of National Natural Science of China under Grant 61632002, in part by the National Natural Science of China under Grant 61603348, Grant 61775198, Grant 61603347, and Grant 61572446, in part by the Foundation of Young Key Teachers from University of Henan Province (2018GGJS092), and in part by the Youth Talent Lifting Project of Henan Province 2018HYTP016 and Henan Province University Science and Technology Innovation Talent Support Plan under Grant 20HASTIT027.

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Authors and Affiliations

  1. Henan Key Lab of Information-Based Electrical Appliances, Zhengzhou University of Light Industry, Zhengzhou, 450002, China

    Enhao Liang, Junwei Sun & Yanfeng Wang

  2. School of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou, 450002, China

    Enhao Liang, Junwei Sun & Yanfeng Wang

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  1. Enhao Liang
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  2. Junwei Sun
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  3. Yanfeng Wang
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Correspondence to Yanfeng Wang .

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Editors and Affiliations

  1. Huazhong University of Science and Technology, Wuhan, China

    Linqiang Pan

  2. Zhengzhou University, Zhengzhou, China

    Jing Liang

  3. Zhongyuan University of Technology, Zhengzhou, China

    Boyang Qu

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Liang, E., Sun, J., Wang, Y. (2020). Univariate Analysis and Principal Component Analysis of Preoperative Blood Indicators in Patients with Esophageal Squamous Cell Carcinoma. In: Pan, L., Liang, J., Qu, B. (eds) Bio-inspired Computing: Theories and Applications. BIC-TA 2019. Communications in Computer and Information Science, vol 1160. Springer, Singapore. https://doi.org/10.1007/978-981-15-3415-7_39

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  • DOI: https://doi.org/10.1007/978-981-15-3415-7_39

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-3414-0

  • Online ISBN: 978-981-15-3415-7

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