Skip to main content
SpringerLink
Log in

Predictive Values of Preoperative Index Analysis in Patients with Esophageal Squamous Cell Carcinoma

  • Conference paper
  • First Online:
Bio-inspired Computing: Theories and Applications (BIC-TA 2019)

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

  • 855 Accesses

Abstract

The prognostic nutritional index (PNI) has been widely used to predict survival outcomes of patients with various malignant tumors. The purpose of this study is to assess the prognostic value of PNI and analyze the effects of preoperative clinical indicators in patients with esophageal squamous cell carcinoma (ESCC). The optimal threshold of PNI is determined by ROC curve analysis, and the correlation between PNI and clinical indicators is evaluated by Chi square test and Fisher’s exact test. The results showed that PNI has been significantly correlated with gender, BMI, T stage, Eosinophil count, Erythrocyte count, Hemoglobin concentration, TP, Albumin and Globulin. PNI is positively related to LMR, NLR and PLR by Spearman’s rank correlation coefficient. Univariate Cox regression model declared that PFS has been vitally correlated with T stage, N stage, TNM stage, EC and PT. Further, multivariate Cox regression model analyses showed that PFS has been significantly correlated with N stage and PT. ROC curve analysis expressed that the combination of N stage and EC has better accuracy and validity in predicting the severity of the patient. The present study determines that N stages, EC and PT are valuable factors in predicting patient’s survival outcomes, as well as independent indicators for poor prognosis.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Mao, J., et al.: Predictive value of pretreatment MRI texture analysis in patients with primary nasopharyngeal carcinoma. Eur. Radiol. 29, 4105–4113 (2019)

    Google Scholar 

  2. Samiei, H., et al.: Dysregulation of helper T lymphocytes in esophageal squamous cell carcinoma (ESCC) patients is highly associated with aberrant production of miR-21. Immunol. Res. 67, 212–222 (2019)

    Google Scholar 

  3. Péron, J., et al.: Assessing long-term survival benefits of immune checkpoint inhibitors using the net survival benefit. JNCI: J. Natl. Cancer Inst. 111, 1186–1191 (2019)

    Google Scholar 

  4. Song, S.E., et al.: Intravoxel incoherent motion diffusion-weighted MRI of invasive breast cancer: correlation with prognostic factors and kinetic features acquired with computer-aided diagnosis. J. Magn. Reson. Imaging 49(1), 118–130 (2019)

    Article  Google Scholar 

  5. Fan, Y., Du, Y., Sun, W., Wang, H.: Including positive lymph node count in the AJCC N staging may be a better predictor of the prognosis of NSCLC patients, especially stage III patients: a large population-based study. Int. J. Clin. Oncol. 24, 1359–1366 (2019)

    Google Scholar 

  6. Choi, Y.H., et al.: A high monocyte-to-lymphocyte ratio predicts poor prognosis in patients with advanced gallbladder cancer receiving chemotherapy. Cancer Epidemiol. Prevent. Biomarkers 28(6), 1045–1051 (2019)

    Google Scholar 

  7. Peng, J., Zhang, R., Zhao, Y., Wu, X., Chen, G., Wan, D., Lu, Z., Pan, Z.: Prognostic value of preoperative prognostic nutritional index and its associations with systemic inflammatory response markers in patients with stage III colon cancer. Chinese J. Cancer 36(1), 96 (2017)

    Article  Google Scholar 

  8. Han, L.H., Jia, Y.B., Song, Q.X., Wang, J.B., Wang, N.N., Cheng, Y.F.: Prognostic significance of preoperative lymphocyte-monocyte ratio in patients with resectable esophageal squamous cell carcinoma. Asian Pac. J. Cancer Prev. 16(6), 2245–2250 (2015)

    Article  Google Scholar 

  9. Fawcett, T.: An introduction to ROC analysis. Pattern Recogn. Lett. 27(8), 861–874 (2006)

    Article  MathSciNet  Google Scholar 

  10. Chapman, B.C., et al.: Perioperative and survival outcomes following neoadjuvant FOLFIRINOX versus gemcitabine abraxane in patients with pancreatic adenocarcinoma. JOP: J. Pancreas 19(2), 75 (2018)

    Google Scholar 

  11. Polen-De, C., Loreen, A., Billingsley, C., Jackson, A., Herzog, T.: Independent radiologic review in ovarian cancer research. Gynecol. Oncol. 153(3), e10 (2019)

    Article  Google Scholar 

  12. McSorley, L., et al.: 64p timing of treatment with concurrent chemoradiotherapy (CRT) and impact on progression free survival (PFS) in limited stage small cell lung cancer (LSSCLC). Ann. Oncol. 30(Suppl.\_2), mdz071-004 (2019)

    Google Scholar 

  13. Hodi, F.S., et al.: Immune-modified response evaluation criteria in solid tumors (imRECIST): refining guidelines to assess the clinical benefit of cancer immunotherapy. J. Clin. Oncol. 36(9), 850–858 (2018)

    Article  Google Scholar 

  14. Jiao, Y., Li, Y., Lu, Z., Liu, Y.: High trophinin-associated protein expression is an independent predictor of poor survival in liver cancer. Dig. Dis. Sci. 64(1), 137–143 (2019)

    Article  Google Scholar 

  15. Ma, J., et al.: Neutrophil-to-lymphocyte ratio (NLR) as a predictor for recurrence in patients with stage III melanoma. Sci. Rep. 8(1), 4044 (2018)

    Article  Google Scholar 

  16. Lobon-Iglesias, M., et al.: Diffuse intrinsic pontine gliomas (DIPG) at recurrence: is there a window to test new therapies in some patients? J. Neurooncol. 137(1), 111–118 (2018)

    Article  Google Scholar 

  17. Chen, G., Cox, R.W., Glen, D.R., Rajendra, J.K., Reynolds, R.C., Taylor, P.A.: A tail of two sides: artificially doubled false positive rates in neuroimaging due to the sidedness choice with t-tests. Hum. Brain Mapp. 40(3), 1037–1043 (2019)

    Article  Google Scholar 

  18. Eklund, A., Knutsson, H., Nichols, T.E.: Reply to chen et al.: parametric methods for cluster inference perform worse for two-sided t-tests. Hum. Brain Mapp. 40(5), 1689–1691 (2019)

    Google Scholar 

  19. Yan, Y., et al.: Patterns of life lost to cancers with high risk of death in China. Int. J. Environ. Res. Public Health 16(12), 2175 (2019)

    Article  Google Scholar 

  20. Ma, W., Jiang, B.: Health impacts due to major climate and weather extremes. In: Lin, H., Ma, W., Liu, Q. (eds.) Ambient Temperature and Health in China, pp. 59–73. Springer, Heidelberg (2019). https://doi.org/10.1007/978-981-13-2583-0_4

    Chapter  Google Scholar 

  21. Zafarzadeh, A., Rahimzadeh, H., Mahvi, A.H.: Health risk assessment of heavy metals in vegetables in an endemic esophageal cancer region in Iran. Health Scope (2018, in press)

    Google Scholar 

  22. Li, Z., et al.: Occurrence and potential human health risks of semi-volatile organic compounds in drinking water from cities along the Chinese coastland of the Yellow Sea. Chemosphere 206, 655–662 (2018)

    Article  Google Scholar 

  23. Zheng, X., et al.: Margin diagnosis for endoscopic submucosal dissection of early gastric cancer using multiphoton microscopy. Surg. Endosc. 34, 408–416 (2019)

    Google Scholar 

  24. Du, H., Xiong, M., Liao, H., Luo, Y., Shi, H., Xie, C.: Chylothorax and constrictive pericarditis in a woman due to generalized lymphatic anomaly: a case report. J. Cardiothorac. Surg. 13(1), 59 (2018)

    Article  Google Scholar 

  25. de Blasio, F., Di Gregorio, A., de Blasio, F., Bianco, A., Bellofiore, B., Scalfi, L.: Malnutrition and sarcopenia assessment in patients with chronic obstructive pulmonary disease according to international diagnostic criteria, and evaluation of raw bia variables. Respir. Med. 134, 1–5 (2018)

    Article  Google Scholar 

  26. Hung, A.J., Chen, J., Gill, I.S.: Automated performance metrics and machine learning algorithms to measure surgeon performance and anticipate clinical outcomes in robotic surgery. JAMA Surg. 153(8), 770–771 (2018)

    Article  Google Scholar 

  27. Semple, C., Lannon, D., Qudairat, E., McCaughan, E., McCormac, R.: Development and evaluation of a holistic surgical head and neck cancer post-treatment follow-up clinic using touchscreen technology—Feasibility study. Eur. J. Cancer Care 27(2), e12809 (2018)

    Article  Google Scholar 

  28. Sun, J., Zhao, X., Fang, J., Wang, Y.: Autonomous memristor chaotic systems of infinite chaotic attractors and circuitry realization. Nonlinear Dyn. 94(4), 2879–2887 (2018). https://doi.org/10.1007/s11071-018-4531-4

    Article  Google Scholar 

  29. Gupta, A., et al.: Feasibility of wearable physical activity monitors in patients with cancer. JCO Clin. Cancer Inform. 2, 1–10 (2018)

    Article  Google Scholar 

  30. Lynce, F., et al.: Characteristics and outcomes of breast cancer patients enrolled in the national cancer institute cancer therapy evaluation program sponsored phase I clinical trials. Breast Cancer Res. Treat. 168(1), 35–41 (2018)

    Article  Google Scholar 

Download references

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.

Author information

Authors and Affiliations

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

    Zhenzhen Zhang, Qinfei Yang & Yingcong Wang

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

    Zhenzhen Zhang, Qinfei Yang & Yingcong Wang

Authors
  1. Zhenzhen Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Qinfei Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yingcong Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yingcong Wang .

Editor information

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

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Zhang, Z., Yang, Q., Wang, Y. (2020). Predictive Values of Preoperative Index Analysis 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_38

Download citation

  • DOI: https://doi.org/10.1007/978-981-15-3415-7_38

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-3414-0

  • Online ISBN: 978-981-15-3415-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation