Cancer Medicine (Jun 2023)

Identification of optimal primary tumor resection candidates for metastatic gastric cancer: Nomograms based on propensity score matching

  • Zhehong Li,
  • Honghong Zheng,
  • Ziming Zhao,
  • Guanyang Chen,
  • Zheng Wang,
  • Buhe Amin,
  • Nengwei Zhang

DOI
https://doi.org/10.1002/cam4.5983
Journal volume & issue
Vol. 12, no. 12
pp. 13063 – 13075

Abstract

Read online

Abstract Background This study sought to develop and validate nomograms for screening patients with metastatic gastric cancer (mGC) who are candidates for primary tumor resection (PTR) and evaluating the prognosis of mGC patients after PTR. Methods From 2010 to 2016, we screened mGC patients with complete data from the Surveillance, Epidemiology, and End Results (SEER) database. Depending on whether or not PTR was performed, we categorized patients into surgery and non‐surgery groups. A 1:1 propensity score matching (PSM) analysis was used to balance the characteristics of the two groups. The endpoints were overall survival (OS) and cancer‐specific survival (CSS). Two predictive nomograms were developed using logistic regression to assess the likelihood of benefit. Two additional prognostic nomograms were developed to assess prognosis in mGC patients after PTR by Cox regression. Finally, nomograms were evaluated using a variety of methodologies. Results Our study included 3594 mGC patients who met the criteria. PTR was associated with improved OS and CSS time (median OS time after PSM: 15 vs. 7 months, P < 0.05; median CSS time after PSM: 17 vs. 7 months, P < 0.05). The OS‐related predictive nomogram, including age, histologic type, grade, T stage, and chemotherapy, was developed. Moreover, the CSS‐related predictive nomogram, including age, histologic type, grade, and chemotherapy, was developed. Sex, histologic type, grade, T stage, N stage, and chemotherapy were found to be correlated with OS. Furthermore, the CSS correlated with histologic type, grade, T stage, N stage, and chemotherapy. Both predictive and prognostic nomograms were found to be valuable and reliable after different types of validation. Conclusion Predictive nomograms were developed and validated for identifying the optimal PTR mGC candidates. Prognostic nomograms were developed and validated for assessing the prognosis of mGC patients after PTR.

Keywords