Literature DB >> 29685636

Prediction of Conditional Probability of Survival After Surgery for Gastric Cancer: A Study Based on Eastern and Western Large Data Sets.

Qing Zhong1, Qi-Yue Chen1, Ping Li2, Jian-Wei Xie2, Jia-Bin Wang2, Jian-Xian Lin2, Jun Lu2, Long-Long Cao1, Mi Lin1, Ru-Hong Tu1, Chao-Hui Zheng3, Chang-Ming Huang4.   

Abstract

BACKGROUND: The dynamic prognosis of patients who have undergone curative surgery for gastric cancer has yet to be reported. Our objective was to devise an accurate tool for predicting the conditional probability of survival for these patients.
METHODS: We analyzed 11,551 gastric cancer patients from the Surveillance, Epidemiology, and End Results database. Two-thirds of the patients were selected randomly for the development set and one-third for the validation set. Two nomograms were constructed to predict the conditional probability of overall survival and the conditional probability of disease-specific survival, using conditional survival methods. We then applied these nomograms to the 4,001 patients in the database from Fujian Medical University Union Hospital, Fuzhou, China, one of the most active Chinese institutes.
RESULTS: The 5-year conditional probability of overall survival of the patients was 41.6% immediately after resection and increased to 52.8%, 68.2%, and 80.4% at 1, 2, and 3 years after gastrectomy. The 5-year conditional probability of disease-specific survival "increased" from 48.9% at the time of gastrectomy to 59.8%, 74.7%, and 85.5% for patients surviving 1, 2, and 3 years, respectively. Sex; race; age; depth of tumor invasion; lymph node metastasis; and tumor size, site, and grade were associated with overall survival and disease-specific survival (P <.05). Within the Surveillance, Epidemiology, and End Results validation set, the accuracy of the conditional probability of overall survival nomogram was 0.77, 0.81, 0.82, and 0.82 at 1, 3, 5, and 10 years after gastrectomy, respectively. Within the other validation set from the Fujian Medical University Union Hospital (n = 4,001), the accuracy of the conditional probability of overall survival nomogram was 0.76, 0.79, 0.77, and 0.77 at 1, 3, 5, and 10 years, respectively. The accuracy of the conditional probability of disease-specific survival model was also favorable. The calibration curve demonstrated good agreement between the predicted and observed survival rates.
CONCLUSION: Based on the large Eastern and Western data sets, we developed and validated the first conditional nomogram for prediction of conditional probability of survival for patients with gastric cancer to allow consideration of the duration of survivorship.
Copyright © 2018 Elsevier Inc. All rights reserved.

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Year:  2018        PMID: 29685636     DOI: 10.1016/j.surg.2018.02.011

Source DB:  PubMed          Journal:  Surgery        ISSN: 0039-6060            Impact factor:   3.982


  6 in total

1.  Prognosis of Young Survivors of Gastric Cancer in China and the U.S.: Determining Long-Term Outcomes Based on Conditional Survival.

Authors:  Qi-Yue Chen; Qing Zhong; Wei Wang; Shi Chen; Ping Li; Jian-Wei Xie; Jia-Bing Wang; Jian-Xian Lin; Jun Lu; Long-Long Cao; Mi Lin; Ru-Hong Tu; Ze-Ning Huang; Ju-Li Lin; Hua-Long Zheng; Zhi-Yu Liu; Chao-Hui Zheng; Jun-Sheng Peng; Zhi-Wei Zhou; Chang-Ming Huang
Journal:  Oncologist       Date:  2018-11-23

2.  Conditional survival after neoadjuvant chemoradiotherapy and surgery for oesophageal cancer.

Authors:  E R C Hagens; M L Feenstra; W J Eshuis; M C C M Hulshof; H W M van Laarhoven; M I van Berge Henegouwen; S S Gisbertz
Journal:  Br J Surg       Date:  2020-02-03       Impact factor: 6.939

3.  Conditional Survival After Resection for Pancreatic Cancer: A Population-Based Study and Prediction Model.

Authors:  Anouk E J Latenstein; Stijn van Roessel; Lydia G M van der Geest; Bert A Bonsing; Cornelis H C Dejong; Bas Groot Koerkamp; Ignace H J T de Hingh; Marjolein Y V Homs; Joost M Klaase; Valery Lemmens; I Quintus Molenaar; Ewout W Steyerberg; Martijn W J Stommel; Olivier R Busch; Casper H J van Eijck; Hanneke W M van Laarhoven; Johanna W Wilmink; Marc G Besselink
Journal:  Ann Surg Oncol       Date:  2020-02-12       Impact factor: 5.344

4.  A Nomogram for Predicting Cancer-Specific Survival of Patients with Gastrointestinal Stromal Tumors.

Authors:  Mengmeng Liu; Chao Song; Ping Zhang; Yuan Fang; Xu Han; Jianang Li; Weixin Wu; Genwen Chen; Jianyong Sun
Journal:  Med Sci Monit       Date:  2020-05-25

5.  A Modified ypTNM Staging System-Development and External Validation of a Nomogram Predicting the Overall Survival of Gastric Cancer Patients Received Neoadjuvant Chemotherapy.

Authors:  Ziyu Li; Qiyan Xiao; Yinkui Wang; Wei Wang; Shuangxi Li; Fei Shan; Zhiwei Zhou; Jiafu Ji
Journal:  Cancer Manag Res       Date:  2020-03-19       Impact factor: 3.989

6.  Nomogram for predicting the survival of gastric adenocarcinoma patients who receive surgery and chemotherapy.

Authors:  Chao-Yang Wang; Jin Yang; Hao Zi; Zhong-Li Zheng; Bing-Hui Li; Yang Wang; Zheng Ge; Guang-Xu Jian; Jun Lyu; Xiao-Dong Li; Xue-Qun Ren
Journal:  BMC Cancer       Date:  2020-01-06       Impact factor: 4.430

  6 in total

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