1. The recurrences of cervical cancer: Possibilities of molecular prediction
- Author
-
L. A. Ashrafyan, T. E. Belokrinitskaya, L. F. Sholokhov, E. V. Kayukova, and V. A. Mudrov
- Subjects
cervical cancer ,immune cycle proteins ,recurrence prediction ,Science - Abstract
The incidence of recurrence of cervical cancer ranges from 10 to 40 %. The 5-year survival rate for patients with recurrent cervical cancer is about 5–15 % against the background of current drug therapy. Clinical and morphological characteristics of the tumor process are known, which are used as markers of an unfavorable prognosis for the development of cervical cancer recurrence. The search for molecular prognostic markers of the course of cervical cancer continues.The aim. To determine the level of immune cycle proteins in patients with cervical cancer 0–IV stages, depending on the occurrence of a relapse of the disease.Materials and research methods. A retrospective analysis of previously obtained results of a study on the local level of immune cycle proteins in patients with cervical cancer was performed. Three years after follow-up, 2 groups were formed: group 1 – patients treated for cervical cancer without signs of disease progression (n = 83); group 2 – patients with cervical cancer with local or systemic recurrence (n = 18). Used statistical methods: non-parametric methods of statistics using the Kruskal – Wallis test; ROC-analysis for significant values in order to calculate threshold values; determination of the quality of the identified predictive markers by calculating the sensitivity, specificity, accuracy.Results. Local initial threshold values have a predictive value for predicting the occurrence of cervical cancer recurrence: B7.2 < 10.7 pg/ml (Se = 0.87; Sp = 0.73; Ac = 0.76; AUC = 0.78), PD-L1 ≤ 5.1 pg/ml (Se = 0.87; Sp = 0.68; Ac = 0.71; AUC = 0.76), sCD27 ≥ 32.0 pg/ml (Se = 0.75; Sp = 0.78; Ac = 0.78; AUC = 0.75).Conclusion. Determination of local levels of B7.2, PD-L1, sCD27 in patients with cervical cancer before treatment can be used to predict the development of disease recurrence during 3 years of follow-up.
- Published
- 2022
- Full Text
- View/download PDF