Consideration of clinicopathologic features improves patient stratification for multimodal treatment of gastric cancer

In Cho, In Gyu Kwon, Ali Guner, Taeil Son, Hyoung Il Kim, Dae Ryong Kang, Sung Hoon Noh, Joon Seok Lim, Woo Jin Hyung

Research output: Contribution to journalArticle

Abstract

Preoperative staging of gastric cancer with computed tomography alone exhibits poor diagnostic accuracy, which may lead to improper treatment decisions. We developed novel patient stratification criteria to select appropriate treatments for gastric cancer patients based on preoperative staging and clinicopathologic features. A total of 5352 consecutive patients who underwent gastrectomy for gastric cancer were evaluated. Preoperative stages were determined according to depth of invasion and nodal involvement on computed tomography. Logistic regression analysis was used to identify clinicopathological factors associated with the likelihood of proper patient stratification. The diagnostic accuracies of computed tomography scans for depth of invasion and nodal involvement were 67.1% and 74.1%, respectively. Among clinicopathologic factors, differentiated tumor histology, tumors smaller than 5 cm, and gross appearance of early gastric cancer on endoscopy were shown to be related to a more advanced stage of disease on preoperative computed tomography imaging than actual pathological stage. Additional consideration of undifferentiated histology, tumors larger than 5 cm, and grossly advanced gastric cancer on endoscopy increased the probability of selecting appropriate treatment from 75.5% to 94.4%. The addition of histology, tumor size, and endoscopic findings to preoperative staging improves patient stratification for more appropriate treatment of gastric cancer.

Original languageEnglish
Pages (from-to)79594-79603
Number of pages10
JournalOncotarget
Volume8
Issue number45
DOIs
Publication statusPublished - 2017 Jan 1

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Combined Modality Therapy
Stomach Neoplasms
Tomography
Histology
Endoscopy
Neoplasms
Therapeutics
Gastrectomy
Logistic Models
Regression Analysis

All Science Journal Classification (ASJC) codes

  • Oncology

Cite this

Cho, In ; Kwon, In Gyu ; Guner, Ali ; Son, Taeil ; Kim, Hyoung Il ; Kang, Dae Ryong ; Noh, Sung Hoon ; Lim, Joon Seok ; Hyung, Woo Jin. / Consideration of clinicopathologic features improves patient stratification for multimodal treatment of gastric cancer. In: Oncotarget. 2017 ; Vol. 8, No. 45. pp. 79594-79603.
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Consideration of clinicopathologic features improves patient stratification for multimodal treatment of gastric cancer. / Cho, In; Kwon, In Gyu; Guner, Ali; Son, Taeil; Kim, Hyoung Il; Kang, Dae Ryong; Noh, Sung Hoon; Lim, Joon Seok; Hyung, Woo Jin.

In: Oncotarget, Vol. 8, No. 45, 01.01.2017, p. 79594-79603.

Research output: Contribution to journalArticle

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