Cancer Control (Sep 2023)

Development and Validation of Tumor Marker Indices in Advanced Gastric Cancer Patients

  • Jiaqi Zhang,
  • Xin Yin,
  • Hao Wang,
  • Tianyi Fang,
  • Jialiang Gao,
  • Ziyu Zhu,
  • Chunfeng Li,
  • Yufei Wang,
  • Xibo Wang,
  • Zhanfei Lu,
  • Junpeng Wu,
  • Yimin Wang,
  • Yao Zhang,
  • Yingwei Xue

DOI
https://doi.org/10.1177/10732748231202466
Journal volume & issue
Vol. 30

Abstract

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Background Tumor markers (TMs) are important for the prognosis of gastric cancer (GC). However, the prognostic importance of the tumor marker index (TMI) based on GC-specific TMs for advanced gastric cancer (AGC) still needs to be further explored. Methods We retrospectively examined patients who underwent radical gastric cancer surgery between February 2014 and June 2016 at the Department of Gastroenterological Surgery, Affiliated Cancer Hospital, Harbin Medical University. The patients were divided into training and validation groups. TMI was determined as the geometric mean of the standard cancer antigen 19-9 (CA19-9) and carcinoembryonic antigen (CEA) levels. Patient overall survival was assessed using the Kaplan–Meier method. Independent prognosis-associated risk factors were identified using Cox hazard regression models. A nomogram model incorporating TMI and clinicopathological factors was developed, and its performance was evaluated using a decision curve analysis, concordance index, and calibration plots. Results In the TMI training cohort, the cutoff value was set at .439, categorizing patients into TMI-High and TMI-Low groups. The 5-year survival rate in the TMI-Low group significantly surpassed that in the TMI-High group (78.2% vs 58.1% and 49.7 vs 41.6, P < .001). TMI emerged as an independent prognostic factor. The nomogram accurately predicted patient prognosis by using TMI and clinicopathological characteristics. Validation of the TMI in the independent cohort yielded satisfactory results. Conclusion The TMI constructed based on specific TMs associated with gastric cancer can offer a precise prognostic prediction for patients.