FIELD: medicine; oncological gynecology.
SUBSTANCE: invention can be used for the diagnosis of high-grade serous ovarian cancer using the lipid profile of blood serum obtained by high-performance liquid chromatography with mass spectrometric detection. The first step is to calculate the response variable y based on lipids SM d16:1/14:0, PC 12:0_18:1, PC 18:2_20:3'1:
where
is the area of peaks of lipid markers SM d16:1/14:0 on the chromatogram of a patient’s blood sample, a.u.;
is the area of peaks of lipid markers PC 12:0_18:1 on the chromatogram of a patient’s blood sample, a.u.;
is the area of peaks of lipid markers PC 18:2_20:3 on the chromatogram of a patient’s blood sample, a.u. At a value of 0.7≤ y' 1≤ 1 it is concluded that the patient belongs to the group of patients with ovarian cancer. If the value is 0 < y'1 < 0.7, the patient belongs to the control group. At the second step, based on the lipids PC P-16:0/18:1 and PC P-16:0/18:2, the response variable y is calculated'2:
where
is the area of peaks of lipid markers PC P-16:0/18:1 on the chromatogram of a patient’s blood sample, a.u.;
is the area of peaks of lipid markers PC P-16:0/18:2 on the chromatogram of a patient’s blood sample, a.u. At a value of 0.6≤ at'2 < 1 it is concluded that there is presence of serous ovarian cancer of stages III–IV. If the value is 0 < y'2 < 0.6, there is the presence of serous ovarian cancer of stages I–II.
EFFECT: method provides the ability to increase the diagnostic accuracy of detecting high-grade epithelial serous ovarian cancer in the early stages (stages I–II) by determining the lipid profile of blood serum using high-performance liquid chromatography with mass spectrometric detection, allowing the identification of possible marker molecules characteristic of pathological conditions in the early stages of the oncological process; sequential application of two models based on the method of logistic regression to calculate a response variable that allows identifying patients with early stages of serous ovarian cancer.
1 cl, 8 dwg, 4 ex
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Authors
Dates
2023-11-14—Published
2022-12-09—Filed