Literature DB >> 29881929

Development and External Validation of a Simplified Nomogram Predicting Individual Survival After R0 Resection for Gastric Cancer: An International, Multicenter Study.

Zhi-Fang Zheng1,2, Jun Lu1,2, Wei Wang3, Jacopo Desiderio4, Ping Li1,2, Jian-Wei Xie1,2, Jia-Bin Wang1,2, Jian-Xian Lin1,2, Amilcare Parisi4, Zhi-Wei Zhou3, Chang-Ming Huang5,6, Chao-Hui Zheng1,2.   

Abstract

BACKGROUND: Previous studies have developed three nomograms for the individual prediction of overall survival after gastric cancer surgery. In this study, the performance of these nomograms was evaluated and compared with that of a simplified nomogram in a multinational cohort of patients.
METHODS: Clinical data from patients who underwent resection (R0) with curative intent for GC at three specialized centers (two from China and one from Italy) and data from the Surveillance, Epidemiology, and End Results database were retrospectively analyzed.
RESULTS: The study analyzed 9810 patients, and the simplified nomogram was developed based on the following factors present in all models: age, sex, depth of invasion, and number of metastatic lymph nodes. In the decision curve analyses, the simplified nomogram demonstrated similar net benefit gains relative to previous models. The discriminative ability of the simplified nomogram was similar to those of the three existing nomograms, and calibration of the simplified nomogram resulted in a predicted survival similar to the actual survival. The predictive ability of the simplified nomogram was superior to that of the American Joint Committee on Cancer (AJCC) stage using Eastern and Western validation data (p < 0.01). Additionally, the simplified nomogram predicted the probabilities within each AJCC stage to illustrate the heterogeneity of risk within each stage.
CONCLUSION: The novel simplified nomogram simplifies the assessment of individual survival after R0 resection for GC without sacrificing predictive ability. It also has potential for use with other databases and for clinical applications.

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Year:  2018        PMID: 29881929     DOI: 10.1245/s10434-018-6551-1

Source DB:  PubMed          Journal:  Ann Surg Oncol        ISSN: 1068-9265            Impact factor:   5.344


  11 in total

1.  Validation of the Memorial Sloan Kettering Gastric Cancer Post-Resection Survival Nomogram: Does It Stand the Test of Time?

Authors:  Masaya Nakauchi; Colin M Court; Laura H Tang; Mithat Gönen; Yelena Y Janjigian; Steven B Maron; Daniela Molena; Daniel G Coit; Murray F Brennan; Vivian E Strong
Journal:  J Am Coll Surg       Date:  2022-04-28       Impact factor: 6.532

2.  Development and Validation of a Prognostic Nomogram for Gastric Signet Ring Cell Carcinoma: A Multicenter Population-Based Study.

Authors:  Shuairan Zhang; Yang Liu; Zihan Jiao; Zenan Li; Jin Wang; Ce Li; Xiujuan Qu; Ling Xu
Journal:  Front Oncol       Date:  2021-03-05       Impact factor: 6.244

3.  The predictive value of the preoperative C-reactive protein-albumin ratio for early recurrence and chemotherapy benefit in patients with gastric cancer after radical gastrectomy: using randomized phase III trial data.

Authors:  Bin-Bin Xu; Jun Lu; Zhi-Fang Zheng; Jian-Wei Xie; Jia-Bin Wang; Jian-Xian Lin; Qi-Yue Chen; Long-Long Cao; Mi Lin; Ru-Hong Tu; Ze-Ning Huang; Ju-Li Lin; Chao-Hui Zheng; Chang-Ming Huang; Ping Li
Journal:  Gastric Cancer       Date:  2019-02-09       Impact factor: 7.701

4.  Clinicopathological Characteristics and Prognosis of cT1N0M1 Gastric Cancer: A Population-Based Study.

Authors:  Jianbo Han; Junhao Tu; Chaoyang Tang; Xiang Ma; Chi Huang
Journal:  Dis Markers       Date:  2019-05-02       Impact factor: 3.434

5.  Nomograms for predicting overall survival and cancer-specific survival in young patients with pancreatic cancer in the US based on the SEER database.

Authors:  Min Shi; Biao Zhou; Shu-Ping Yang
Journal:  PeerJ       Date:  2020-04-14       Impact factor: 2.984

6.  Development and validation of an artificial neural network prognostic model after gastrectomy for gastric carcinoma: An international multicenter cohort study.

Authors:  Ziyu Li; Xiaolong Wu; Xiangyu Gao; Fei Shan; Xiangji Ying; Yan Zhang; Jiafu Ji
Journal:  Cancer Med       Date:  2020-07-15       Impact factor: 4.452

7.  Prognostic nomogram for predicting long-term cancer-specific survival in patients with lung carcinoid tumors.

Authors:  Yanqi He; Feng Zhao; Qingbing Han; Yiwu Zhou; Shuang Zhao
Journal:  BMC Cancer       Date:  2021-02-08       Impact factor: 4.430

8.  A nomogram for predicting cancer-specific survival in patients with osteosarcoma as secondary malignancy.

Authors:  Yanqi He; Han Liu; Shuai Wang; Jianjun Zhang
Journal:  Sci Rep       Date:  2020-07-30       Impact factor: 4.379

9.  Development and External Validation of a Nomogram for Predicting Overall Survival in Stomach Cancer: A Population-Based Study.

Authors:  Haonan Ji; Huita Wu; Yu Du; Li Xiao; Yiqin Zhang; Qiuhua Zhang; Xin Wang; Wenfeng Wang
Journal:  J Healthc Eng       Date:  2021-09-24       Impact factor: 2.682

10.  A nomogram to predict overall survival and disease-free survival after curative-intent gastrectomy for gastric cancer.

Authors:  Alice Sabrina Tonello; Giulia Capelli; Quoc Riccardo Bao; Alberto Marchet; Fabio Farinati; Timothy M Pawlik; Dario Gregori; Salvatore Pucciarelli; Gaya Spolverato
Journal:  Updates Surg       Date:  2021-06-14
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