| Autor: |
P. Yu. Grishko, A. V. Mishchenko, O. V. Ivko, D. V. Samsonov, A. M. Karachun |
| Jazyk: |
ruština |
| Rok vydání: |
2020 |
| Předmět: |
|
| Zdroj: |
Тазовая хирургия и онкология, Vol 10, Iss 1, Pp 20-27 (2020) |
| Druh dokumentu: |
article |
| ISSN: |
2686-9594 |
| DOI: |
10.17650/2686-9594-2020-10-1-20-27 |
| Popis: |
Objective: to determine the predicting factors for the effectiveness of neoadjuvant treatment in colorectal cancer based on the analysis of overall and relapse-free survival, as well as the possibility of multiparametric magnetic resonance imaging (MRI) in stratifying patients into groups with favorable and unfavorable clinical course.Materials and methods. 112 patients who received preoperative chemoradiotherapy (n = 85) and chemoradiotherapy supplemented with neoadjuvant polychemotherapy (n = 27) followed by surgery were enrolled in retrospective study. To determine the most significant predicting factors and criteria for evaluating the effectiveness of treatment that affect overall and relapse-free survival, Kaplan–Meier estimator and Cox regression were used.Results. The relapse-free survival was significantly affected by the presence or absence of extramural venous invasion according to MRI (mrEMVI) (p = 0.0001), circumferential resection margin status according to pathomorphological data (pCRM) (p = 0.031), change in volume of tumor (mrVolumetric analysis) (p = 0.015), tumor regression grade according to MRI (mrTRG) (p = 0.017) and pathomorphological data (pTRG) (p = 0.038). Independent predictors of overall survival were: extramural venous invasion according to MRI (mrEMVI) (p = 0.0001), posttreatment N staging (p = 0.047) and tumor regression grade according to MRI (mrTRG) (p = 0.059). Based on the most significant MR criteria, a mathematical model was developed to predict the risk of relapse after neoadjuvant treatment.Conclusions. MRI allows stratifying patients into groups with a favorable and unfavorable prognosis at the preoperative stage and optimizing the management of patients after surgery taking into account pathomorphological data. |
| Databáze: |
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| Externí odkaz: |
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