Computer-aided diagnosis of lung malignity using multidimensional analysis of tumour marker data

Authors

  • Viera Mrázová Department of Chemistry, University of SS. Cyril and Methodius, J. Herdu 2, Trnava, SK-917 01, Slovak Republic
  • Ján Mocák Department of Chemistry, University of SS. Cyril and Methodius, J. Herdu 2, Trnava, SK-917 01, Slovak Republic
  • Elena Varmusová Institute for Tuberculosis and Respiratory Diseases, Department of Clinical Chemistry, Kvetnica, Poprad, SK-058 87 Slovak Republic
  • Denisa Kavková Institute for Tuberculosis and Respiratory Diseases, Department of Clinical Chemistry, Kvetnica, Poprad, SK-058 87 Slovak Republic

DOI:

https://doi.org/10.36547/nbc.1309

Keywords:

lung malignity, multidimensional analysis, tumour marker

Abstract

The aim of this work is assessing diagnostic performance of lung tumour markers. Three clinical laboratory tests were used for indicating lung malignancy in order to verify or predict the patient’s diagnosis. The data set of 182 patients was examined and two main groups of the patient samples were created – 86 with diagnosed malignancy (confirmed by histology) and 96 with diagnosed benign tumours or tuberculosis. The following tumour markers were analyzed: carcinoembryonic antigen and cytokeratin 19 fragment, which were sampled in the pleural exudates, and the same tumour markers in serum. In addition, the patient’s age and the gender of the corresponding individual were used as further variables in the original data matrix. Three laboratory tests were used for indicating lung malignancy in order to verify or predict the patient’s diagnosis not only by using the results of the chosen individual laboratory test but also applying multivariate statistical approach, which jointly utilizes all performed tests in the form of their optimal linear combination.

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Published

2021-12-04

How to Cite

Mrázová, V., Mocák, J., Varmusová, E., & Kavková, D. (2021). Computer-aided diagnosis of lung malignity using multidimensional analysis of tumour marker data. Nova Biotechnologica Et Chimica, 8(1), 65–70. https://doi.org/10.36547/nbc.1309

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Section

Research Articles