Predicting optimal surgeon volume in patients with early gastric cancer

Abstract

Introduction. The incidence of gastric cancer remains high, despite the increase in the share of stage I–II cancers — 37.1% in 2019. Surgical treatment remains relevant even in patients with “early” forms of gastric cancer (EGC). Therefore, the reliable means for determining the surgeon volume in such patients are to be urgently developed.Aim. To estimate the probability of building a stable predictive model for patients with EGC in order to choose the proper surgical intervention.Materials and methods. Th e research involved the data obtained from “Database of patients with gastric cancer, reflecting statistics of patients with a particular variant of surgical intervention, treated at Yaroslavl Regional Clinical Oncological Hospital during the period from 2009 to 2019”. All patients (n = 266) received different volume of surgery: intraluminal surgery (n = 128), wedge gastric resection (n = 36), classical gastrectomy or subtotal gastric resection (n = 102). According to the volume of intervention, the patients were ratified into several study groups. Statistical analysis involved case records of three groups of patients and was conducted using MedCalc Statistical Soft ware version 20.022 and Statistica 12.5.Results. Ten factors were identified to form a patient model corresponding to each method of surgical treatment. Th e fairness of the division of patients into groups was checked by ROC-analysis in order to determine sensitivity and specificity of the set of criteria for the division. Th e following characteristics of the mathematical model were obtained by means of ROC analysis: concordance coefficient = 88.24%, AUC = 0.893; index J = 0.811; Se = 87.92; Sp = 89.04; +LR = 3.27; -LR = 1.31.Conclusion. Introduction of this approach into clinical practice decreased the rate of gastrectomies and gastric resections by 15% for the last three years.