Predicting optimal surgeon volume in patients with early gastric cancer

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.

1. Collection of medical statistics. Yaroslavl; 2018 (In Russ).

2. Dylenok A.A. Th e state of diagnosis of “early” stomach cancer in the Yaroslavl region. Science of Russia: aims and targets. 2021;1:39 (In Russ). DOI: 10.18411/sr-10-04-2021-10

3. Mikhaleva L.M., Birukov A.E., Polyanko N.I. Precancerous lesions and early gastric cancer: modern clinical-morphological data. Clinical Medicine. 2017;95(10):881–7 (In Russ.). DOI: 10.18821/0023-2149-2017-95-10-881-887

4. Chaika A.V., Khomyakov V.M., Ryabov A.B. Functional effects of operations for malignant gastric neoplasms: prevention, diagnosis and treatment of post-gastrectomy disorders. Russian Journal of Gastroenterology, Hepatology, Coloproctology. 2018;28(3):4–17 (In Russ.). DOI: 10.22416/1382-4376-2018-28-3-4-17

5. Rybachkov V.V., Vasin A.B., Malashenko V.N., Dubrovina D.E. Surgical tactics at the reflux esophagitis in patients with total gastrectomy. Modern Problems of Science and Education. 2015;1(1):1336 (In Russ.).

6. Wang J.-D., Zhu S.-Y., Lu Y.-J. Anti-reflux anastomosis following esophagectomy for adenocarcinoma of the esophagogastric junction: impact of duodenogastroesophageal reflux and expression of cyclooxygenase 2 in the remnant esophagus. Eur Rev Med Pharmacol Sci. 2016;20:476–85. PMID: 26914122

7. Berg P., McCallum R. Dumping syndrome: a review of the current concepts of pathophysiology, diagnosis, and treatment. Dig Dis Sci. 2016;61:11. DOI: 10.1007/s10620-015-3839-x

8. Uriu Y., Kuriyama A., Ueno A., Ikegami T. Afferent loop syndrome of 10 years’ onset aft er gastrectomy. Asian J Surg. 2019;42(10):935–7. DOI: 10.1016/j.asjsur.2019.06.008

9. Gambardella V., Cervantes A. Precision medicine in the adjuvant treatment of gastric cancer. Th e Lancet Oncology. 2018;19(5):583–4. DOI: 10.1016/s1470-2045(18)30131-1

10. Ko W.J., Kim Y.M., Yoo I.K., Cho J.Y. Clinical outcomes of minimally invasive treatment for early gastric cancer in patients beyond the indications of endoscopic submucosal dissection. Surg Endosc. 2018;32(9):3798–805. DOI: 10.1007/s00464-018-6105-4

11. Pectasides E., Stachler M.D., Derks S., Liu Y., Maron S., Islam M., et al. Genomic heterogeneity as a barrier to precision medicine in gastroesophageal adenocarcinoma. Cancer Discov. 2018;8(1):37–48. DOI: 10.1158/2159-8290.CD-17-0395

12. Mingchi L., Lifeng L. Clinical utility of miniprobe endoscopic ultrasonography for prediction of invasion depth of early gastric cancer: A meta-analysis of diagnostic test from PRISMA guideline. Medicine. 2019; 98(6):e14430. DOI: 10.1097/MD.0000000000014430

13. Sitarz R., Skierucha M., Mielko J., Off erhaus G.J.A., Maciejewski R., Polkowski W.P. Gastric cancer: epidemiology, prevention, classification, and treatment. Cancer Manag Res. 2018;10:239–48. DOI: 10.2147/CMAR.S149619

14. Zheng H., Zhu W., Niu Z., Li H., Zheng Y., Liu Z., et al. A novel nutrition-based nomogram to predict prognosis aft er curative resection of gastric cancer. Front Nutr. 2021;8:664620. DOI: 10.3389/fnut.2021.664620

15. Ma M., Wang J., Hu Y., Weng M., Liu X., Wang Y. Prognostic value of inflammatory biomarkers in gastric cancer patients and the construction of a predictive model. Dig Surg. 2019;36(5):433–42. DOI: 10.1159/000493432