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Prediction of Survival Outcomes Based on Preoperative Clinical Parameters in Gastric Cancer

  • Gastrointestinal Oncology
  • Published:
Annals of Surgical Oncology Aims and scope Submit manuscript

Abstract

Background

Few current preoperative risk assessment tools provide essential, optimized treatment for gastric cancer. The purpose of this study was to develop and validate a nomogram that uses preoperative data to predict survival and risk assessments.

Methods

A survival prediction model was constructed using data from a developmental cohort of 1251 patients with stage I to III gastric cancer who underwent curative resection between January 2005 and December 2008 at Ajou University Hospital, Korea. The model was internally validated for discrimination and calibrated using bootstrap resampling. To externally validate the model, data from a validation cohort of 2012 patients with stage I to III gastric cancer who underwent surgery at multiple centers in Korea between January 2001 and June 2006 were analyzed. Analyses included the model’s discrimination index (C-index), calibration plots, and decision curve that predict overall survival.

Results

Eight independent predictors, including age, sex, clinical tumor size, macroscopic features, body mass index, histology, clinical stages, and tumor location, were considered for developing the nomogram. The discrimination index was 0.816 (adjusted C-index) in the developmental cohort and 0.781 (adjusted C-index) in the external validation cohort. Additionally, in both the developmental and validation datasets, age and tumor size were significantly correlated with each other and were independent indicators for survival (P < 0.05).

Conclusions

We developed a new nomogram by using the most common and significant preoperative parameters that can help to identify high-risk patients before treatment and help clinicians to make appropriate decisions for patients with stage I to III gastric cancer.

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Acknowledgments

The authors thank Professor Keun-Won Ryu and Professor Bang-Wool Eom (Gastric Cancer Branch, National Cancer Center, Goyang, Gyeonggi-do, Korea) for critical comments and generous aid to our study. Moreover, this work would not have been possible without the generous and unconditional use of data from the following eight institutions: Gastric Cancer Branch, National Cancer Center, Goyang, Gyeonggi-do, Korea. Department of Surgery, Seoul National University College of Medicine, Seoul, Korea. Department of Surgery, Dong-A University College of Medicine, Busan, Korea. Department of Surgery, Soonchunhyang University Bucheon Hospital, Bucheon, Gyeonggi-do, Korea. Department of Surgery, Chonbuk National University Medical School, Jeonju, Jeollabuk-do, Korea. Department of Surgery, Keimyung University School of Medicine, Daegu, Korea. Department of Surgery, Bundang Jesaeng Hospital, Seongnam, Gyeonggi-do, Korea. Department of Surgery, Yonsei University College of Medicine, Seoul, Korea.

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Authors and Affiliations

Authors

Contributions

Study conception and design: Ho-Jung Shin, Sang-Uk Han; data collection: Ho-Jung Shin, Hoon Hur, Bang-Wool Eom; analysis and interpretation of results: Ho-Jung Shin, Yong-Ok Choi; drafting the manuscript: Ho-Jung Shin, Yong-Ok Choi; critical revision of the article: Sang-Yong Son, Hoon Hur, Bang-Wool Eom, Sang-Uk Han; all authors discussed the results and contributed to the final manuscript.

Corresponding author

Correspondence to Sang-Uk Han MD.

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All authors declare that no support from any organization has been received for the submitted work; there are no financial relationships with any organizations that might have an interest in the submitted work. There are no other relationships or activities that could have influenced the submitted work.

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Supplementary Information

Supplementary material 1 (PDF 347 kb)

Supplement 1. Hazard ratio plots of the pretreatment variables

Supplement 2. Descriptive results of net benefit(NB) differences in development cohort

Supplement 3. Descriptive results of net benefit(NB) differences in validation cohort

Supplement 4. Potential prognostic factors in ages under 60

Supplement 5. Potential prognostic factors in ages over 70

Supplement 6. Optimized cut-off of normogram points calculated with maximum selected ranking statistics

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Shin, HJ., Choi, YO., Roh, Ck. et al. Prediction of Survival Outcomes Based on Preoperative Clinical Parameters in Gastric Cancer. Ann Surg Oncol 28, 7027–7037 (2021). https://doi.org/10.1245/s10434-021-09754-w

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  • DOI: https://doi.org/10.1245/s10434-021-09754-w

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