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Construction of a risk prediction model for gastric cancer based on random forest
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Qingqing WANG1, Wenbo WU1, Shaoping WAN1, Linglin ZHANG2, Yuting LI3, Lilou RONG1
Chinese Nursing Research | 2026, 40(7) : 1070 - 1080
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Chinese Nursing Research | 2026, 40(7): 1070-1080
• Original Articles •
Construction of a risk prediction model for gastric cancer based on random forest
Full
Qingqing WANG1, Wenbo WU1, Shaoping WAN1, Linglin ZHANG2, Yuting LI3, Lilou RONG1
Affiliations
  • 1Sichuan Cancer Hospital, Sichuan Cancer Institute, Sichuan Cancer Center, University of Electronic Science and Technology of China, Sichuan 610041 China
  • 2Renshou County Center for Disease Control and Prevention
  • 3Sichuan Provincial Mental Health Center(Mianyang Third People's Hospital)
Published: 2026-04-10 doi: 10.12102/j.issn.1009-6493.2026.07.002
Outline
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Objective

To construct a risk prediction model for gastric cancer in Sichuan province and to identify its predictive factors.

Methods

A total of 378 patients diagnosed with gastric cancer in four medical institutions in Sichuan province from July 2021 to August 2022 were selected as the case group.A total of 378 healthy individuals undergoing physical examinations during the same period were selected as the control group.The random forest method was used to construct a risk prediction model for gastric cancer.The performance of the model was evaluated by using accuracy,sensitivity,specificity,area under the ROC curve(AUC),calibration curve,and decision curve analysis(DCA).

Results

Educational level,occupation,white meat intake,processed meat intake,coarse grain intake,pickled and sun dried food intake,dietary taste,dietary coldness and heat,eating speed,breakfast status,smoking status,alcohol consumption,tea drinking status,history of superficial gastritis,atrophic gastritis,gastric ulcer,hypertension,hyperlipidemia,family history of cancer,and personality were independent influencing factors for gastric cancer.The top three influencing factors in terms of importance score were occupation,education level,and smoking status.The accuracy of the prediction model was 99.8%.The sensitivity was 100.0%.The specificity was 99.6%.The AUC was 0.999(95%CI 0.998-1.000).The calibration curve of the prediction model indicated good consistency between the model and the actual observation results.The DCA curve suggested that the model has good clinical efficacy in predicting gastric cancer.

Conclusions

The risk prediction model for gastric cancer of Sichuan province constructed based on the random forest method in this study has good predictive performance and is helpful for early identification of high-risk population for gastric cancer.

gastric cancer  /  random forest  /  risk prediction model  /  influencing factors
王青青, 武文博, 万绍平, 张铃林, 李玉婷, 容丽楼. 基于随机森林构建胃癌风险预测模型. 护理研究, 2026 , 40 (7) : 1070 -1080 . DOI: 10.12102/j.issn.1009-6493.2026.07.002
Qingqing WANG, Wenbo WU, Shaoping WAN, Linglin ZHANG, Yuting LI, Lilou RONG. Construction of a risk prediction model for gastric cancer based on random forest[J]. Chinese Nursing Research, 2026 , 40 (7) : 1070 -1080 . DOI: 10.12102/j.issn.1009-6493.2026.07.002
Year 2026 volume 40 Issue 7
40
18
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Article Info
doi: 10.12102/j.issn.1009-6493.2026.07.002
  • Receive Date:2025-01-23
  • Online Date:2026-10-28
  • Published:2026-04-10
Article Data
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History
  • Received:2025-01-23
  • Revised:2026-01-07
Affiliations
    1Sichuan Cancer Hospital, Sichuan Cancer Institute, Sichuan Cancer Center, University of Electronic Science and Technology of China, Sichuan 610041 China
    2Renshou County Center for Disease Control and Prevention
    3Sichuan Provincial Mental Health Center(Mianyang Third People's Hospital)

Corresponding:

WU Wenbo, E-mail:
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表12种不同金属材料的力学参数
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Family
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Number of
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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