Acta Biomedica Scientifica (Aug 2021)

Diagnostic and prognostic significance of some inflammatory serum proteins in patients with precancerous diseases and cervical cancer

  • E. V. Kayukova,
  • V. A. Mudrov,
  • L. F. Sholokhov

DOI
https://doi.org/10.29413/ABS.2021-6.3.13
Journal volume & issue
Vol. 6, no. 3
pp. 126 – 133

Abstract

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Background: The high social significance of cervical cancer, the shortcomings of the performed cervical screening is prerequisites for research in the field of mproving the diagnosis of this disease. We hypothesized that the systemic level of some inflammatory proteins could be used as a diagnostic criterion for cervical cancer.The aim of the study was to study the level of some vascular-inflammatory markers in the blood serum in patients with precancerous diseases and cervical cancer in order to improve their diagnosis and also to identify markers for predicting an unfavorable outcome in patients with cervical cancer.Materials and methods. A non-randomized prospective controlled study was carried out, the participants of which were patients with the diagnosis of cervical cancer (n = 49) and cervical intraepithelial neoplasia of the III degree (n = 13). The control group included 15 relatively healthy women. The following spectrum of inflammatory proteins was determined in blood serum by flow cytometry using the Human Vascular Inflammation Panel 1: myoglobin, calprotectin, lipocalin A, matrix metal peroxidase 2, osteopontin, myeloperoxidase, serum amyloid A, protein 4, which binds insulin-like growth factor cell-cell adhesion 1, vascular cell adhesion molecule, matrix metalloperoxidase 9, cystatin C. Statistical analysis was carried out by calculating the Mann-Whitney test with Bonferroni’s correction. The model was created using binary logistic regression to diagnose cervical cancer.Results. In the intergroup comparison of the protein`s spectrum in the blood serum, no significant differences were obtained. However, using the binary logistic regression method, an equation was drawn up to calculate the diagnostic coefficient of cervical cancer, which allows diagnosing cervical cancer with an accuracy of 82%, and in terms of information content is not inferior to cytological diagnostics. The developed coefficient can be used to predict an unfavorable outcome of cervical cancer after 1 year from the moment of diagnosis. Conclusion. The developed diagnostic coefficient makes it possible to diagnose cervical cancer with high accuracy and can be used to predict cervical cancer.

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