Recursive partition analysis of peritoneal and systemic recurrence in patients with gastric cancer who underwent D2 gastrectomy: Implications for neoadjuvant therapy consideration

Jee Suk Chang, Kyung Hwan Kim, Ki Chang Keum, Sung Hoon Noh, Joon Seok Lim, Hyo Song Kim, Sun Young Rha, Yong Chan Lee, Woo Jin Hyung, Woong Sub Koom

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)

Abstract

Background and Objectives: To classify patients with nonmetastatic advanced gastric cancer who underwent D2-gastrectomy into prognostic groups based on peritoneal and systemic recurrence risks. Methods: Between 2004 and 2007, 1,090 patients with T3–4 or N+ gastric cancer were identified from our registry. Recurrence rates were estimated using a competing-risk analysis. Different prognostic groups were defined using recursive partitioning analysis (RPA). Results: Median follow-up was 7 years. In the RPA-model for peritoneal recurrence risk, the initial node was split by T stage, indicating that differences between patients with T1–3 and T4 cancer were the greatest. The 5-year peritoneal recurrence rates for patients with T4 (n = 627) and T1–3 (n = 463) disease were 34.3% and 9.1%, respectively. N stage and neural invasion had an additive impact on high-risk patients. The RPA model for systemic relapse incorporated N stage alone and gave two terminal nodes: N0–2 (n = 721) and N3 (n = 369). The 5-year cumulative incidences were 7.7% and 24.5%, respectively. Conclusions: We proposed risk stratification models of peritoneal and systemic recurrence in patients undergoing D2-gastrectomy. This classification could be used for stratification protocols in future studies evaluating adjuvant therapies such as preoperative chemoradiotherapy. J. Surg. Oncol. 2016;114:859–864.

Original languageEnglish
Pages (from-to)859-864
Number of pages6
JournalJournal of surgical oncology
Volume114
Issue number7
DOIs
Publication statusPublished - 2016 Dec 1

Bibliographical note

Publisher Copyright:
© 2016 Wiley Periodicals, Inc.

All Science Journal Classification (ASJC) codes

  • Surgery
  • Oncology

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