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Tumor Depth Prediction of Gastric Cancer With a T4 Score

  • Kiyoaki Taniguchi
  • , Masaho Ota
  • , Takuji Yamada
  • , Akiko Serizawa
  • , Sho Kotake
  • , Shunichi Ito
  • , Kazuomi Suzuki
  • , Masalazu Yamamoto

研究成果: ジャーナルへの寄稿学術論文査読

抄録

Background/Aim: Peritoneal metastases are often found at surgery of pT4 gastric cancers, preventing R0 resection. In the event of successful R0 resection, distant metastases still occur in a sizeable proportion of patients. Estimation of the depth of invasion has a relatively low accuracy (57%-86%) compared with pathological findings. This study sought to develop a clinical score to distinguish between pathological stage T4 (pT4) and pT1-3 gastric cancer. Patients and Methods: Reviewing the data of 2,771 patients who had undergone gastrectomy at our hospital from January 1996-December 2016, we assessed demographic factors plus tumor markers, diameter, location, histology, and macroscopic type according to the fifth edition (2019) of the WHO classification. Significant factors on multivariate analysis were used to develop a pT4 gastric cancer depth prediction score (T4 score). Results: Multivariate analysis revealed that the clinical factors associated with pT4 disease were CA19-9 elevation, tumor diameter ≥50 mm, poorly cohesive type adenocarcinoma, mucinous adenocarcinoma, and WHO macroscopic types 2-4. The T4 score was obtained by weighing these factors according to the β-coefficient. The optimum cutoff value of the T4 score was 4 points. A total of 79.4% of cases with a T4 score ≥4 points were stage pT4. A total of 93.9% of cases with a T4 score <4 points were stage pT1-3, with 91.1% sensitivity, 85.3% specificity, 79.4% positive predictive value, and 93.9% negative predictive value. Conclusion: T4 scoring can differentiate pT4 gastric cancer from pT1-3 gastric cancer.

本文言語英語
ページ(範囲)641-647
ページ数7
ジャーナルCancer Diagnosis and Prognosis
2
6
DOI
出版ステータス出版済み - 2022
外部発表はい

UN SDG

この成果は、次の持続可能な開発目標に貢献しています

  1. SDG 3 - すべての人に健康と福祉を
    SDG 3 すべての人に健康と福祉を

All Science Journal Classification (ASJC) codes

  • 腫瘍学
  • 癌研究

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