Possible predictors of recurrence risk of deep endometriosis

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Abstract

Objective: To evaluate individual risk factors for recurrence of deep endometriosis (DE) on the basis of the obtained clinical, anamnestic and molecular biological data and to develop a formula for the individual recurrence risk of DE.

Materials and methods: This was a study of the clinical and anamnestic data of 200 patients with DE who underwent surgical treatment at the Department of General Surgery of the National Medical Research Centre for Obstetrics, Gynecology and Perinatology, Moscow during the period from 2020 to 2021. Group I consisted of 80 patients with recurrent DE, and group II included 120 patients with newly diagnosed DE. All patients underwent surgical treatment followed by immunohistochemical (IHC) assessment. The most significant risk factors for the recurrence of DE were selected using binary logistic regression, and the computer model of a possible recurrence of DE was developed.

Results: The detailed study of clinical, anamnestic and IHC data of the patients revealed five risk factors for recurrence of DE, namely: the age of the patients at the time of surgery, the duration of the disease, EphA1 expression in the ectopic endometrium, protein to the VEGF receptor in the eutopic and ectopic endometrium. A mathematical model with a sensitivity of 97.3% and a specificity of 85.7% was developed on the basis of the identified risk factors; the accuracy of the mathematical model was 93.1%. The duration of the recurrence interval averaged 48 (24;72) months. The recurrence interval was significantly longer in patients with a more radical extent of surgery (3 (2;11.5) years versus 1 (1;3) years, respectively (p<0.05)). The recurrence interval was almost three times less in patients after bowel shaving compared to women after intestinal resection (2 (1;3) years versus 3 (2;11.5) years, respectively, p=0.001)). The excision of all visible endometrioid foci reduces the risk of recurrence of endometriosis.

Conclusion: The mathematical model with high sensitivity and specificity was developed on the basis of the obtained data using binary logistic regression. In order to determine the possible risks of endometriosis recurrence, it is necessary to validate the presented model which can be useful in the work of obstetrician-gynecologists.

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About the authors

Daria N. Senina

Academician V.I. Kulakov National Medical Research Centre for Obstetrics, Gynecology and Perinatology, Ministry of Health of Russia; I.M. Sechenov First Moscow State Medical University, Ministry of Health of Russia (Sechenov University)

Author for correspondence.
Email: seninadasha1995@gmail.com

graduate student of the Surgical Department

Russian Federation, 117997, Moscow, Ac. Oparin str., 4; 119992, Moscow, Trubetskaya str., 8-2

Vladimir D. Chuprynin

Academician V.I. Kulakov National Medical Research Centre for Obstetrics, Gynecology and Perinatology, Ministry of Health of Russia

Email: v_chuprynin@oparina4.ru

PhD, Head of the Surgical Department

Russian Federation, 117997, Moscow, Ac. Oparin str., 4

Alexandra V. Asaturova

Academician V.I. Kulakov National Medical Research Centre for Obstetrics, Gynecology and Perinatology, Ministry of Health of Russia

Email: a.asaturova@gmail.com

Dr. Med. Sci., Head of the 1st Pathology Department

Russian Federation, 117997, Moscow, Oparin str., 4

Vyacheslav V. Chursin

Academician V.I. Kulakov National Medical Research Centre for Obstetrics, Gynecology and Perinatology, Ministry of Health of Russia

Email: v_chursin@oparina4.ru

doctor at the surgical department

Russian Federation, 117997, Moscow, Ac. Oparin str., 4

Natalya A. Buralkina

Academician V.I. Kulakov National Medical Research Centre for Obstetrics, Gynecology and Perinatology, Ministry of Health of Russia

Email: natalyaburalkina@yandex.ru

Dr. Med. Sci., Senior Researcher at Surgical Department

Russian Federation, 117997, Moscow, Ac. Oparin str., 4

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