Literature DB >> 25697470

Nomograms for predicting the prognosis of stage IV colorectal cancer after curative resection: a multicenter retrospective study.

K Kawai1, S Ishihara2, H Yamaguchi2, E Sunami2, J Kitayama2, H Miyata3, K Sugihara4, T Watanabe2.   

Abstract

PURPOSE: Although stage IV colorectal cancer (CRC) encompasses a wide variety of clinical conditions with diverse prognoses, no statistical model for predicting the postoperative prognosis of stage IV CRC has been established. Thus, we here aimed to construct a predictive model for disease-free survival (DFS) and overall survival (OS) after curative surgery for stage IV CRC using nomograms.
METHODS: The study included 1133 stage IV CRC patients who underwent curative surgical resection in 19 institutions. Patients were divided into derivation (n = 586) and validation (n = 547) groups. Nomograms to predict the 1- and 3-year DFS rates and the 3- and 5-year OS rates were constructed using the derivation set. Calibration plots were constructed, and concordance indices (c-indices) were calculated. The predictive utility of the nomogram was validated in the validation set.
RESULTS: The postoperative carcinoembryonic antigen (CEA) level, depth of tumor invasion (T factor), lymph node metastasis (N factor), and number of metastatic organs were adopted as variables for the DFS-predicting nomogram, whereas the postoperative CEA level, T factor, N factor, and peritoneal dissemination were adopted for the nomogram to predict OS. The nomograms showed moderate calibration, with c-indices of 0.629 and 0.640 in the derivation set and 0.604 and 0.637 in the validation set for DFS and OS, respectively.
CONCLUSIONS: The nomograms developed were capable of estimating the probability of DFS and OS on the basis of only 4 variables, and may represent useful tools for postoperative surveillance of stage IV CRC patients in routine practice.
Copyright © 2015 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Colorectal cancer; Curative resection; Nomogram; Prognosis; Stage IV

Mesh:

Substances:

Year:  2015        PMID: 25697470     DOI: 10.1016/j.ejso.2015.01.026

Source DB:  PubMed          Journal:  Eur J Surg Oncol        ISSN: 0748-7983            Impact factor:   4.424


  15 in total

1.  Predicting Overall Survival in Patients with Metastatic Rectal Cancer: a Machine Learning Approach.

Authors:  Beiqun Zhao; Rodney A Gabriel; Florin Vaida; Nicole E Lopez; Samuel Eisenstein; Bryan M Clary
Journal:  J Gastrointest Surg       Date:  2019-08-29       Impact factor: 3.452

Review 2.  Personalizing prognosis in colorectal cancer: A systematic review of the quality and nature of clinical prognostic tools for survival outcomes.

Authors:  Alyson L Mahar; Carolyn Compton; Susan Halabi; Kenneth R Hess; Martin R Weiser; Patti A Groome
Journal:  J Surg Oncol       Date:  2017-08-02       Impact factor: 3.454

3.  Nomograms for colorectal cancer: A systematic review.

Authors:  Kazushige Kawai; Eiji Sunami; Hironori Yamaguchi; Soichiro Ishihara; Shinsuke Kazama; Hiroaki Nozawa; Keisuke Hata; Tomomichi Kiyomatsu; Junichiro Tanaka; Toshiaki Tanaka; Takeshi Nishikawa; Joji Kitayama; Toshiaki Watanabe
Journal:  World J Gastroenterol       Date:  2015-11-07       Impact factor: 5.742

4.  Using machine learning to construct nomograms for patients with metastatic colon cancer.

Authors:  B Zhao; R A Gabriel; F Vaida; S Eisenstein; G T Schnickel; J K Sicklick; B M Clary
Journal:  Colorectal Dis       Date:  2020-02-16       Impact factor: 3.788

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Authors:  Giovanni Li Destri; Lidia Puzzo; Alessia Erika Russo; Francesco Ferraù; Antonio Di Cataldo; Stefano Puleo
Journal:  Int J Surg Case Rep       Date:  2016-11-23

6.  Nomograms to predict survival after colorectal cancer resection without preoperative therapy.

Authors:  Zhen-Yu Zhang; Qi-Feng Luo; Xiao-Wei Yin; Zhen-Ling Dai; Shiva Basnet; Hai-Yan Ge
Journal:  BMC Cancer       Date:  2016-08-19       Impact factor: 4.430

7.  A Novel Diagnostic Nomogram for Noninvasive Evaluating Liver Fibrosis in Patients with Chronic Hepatitis B Virus Infection.

Authors:  Danying Cheng; Gang Wan; Lei Sun; Xiaomei Wang; Weini Ou; Huichun Xing
Journal:  Biomed Res Int       Date:  2020-06-02       Impact factor: 3.411

8.  An Oxidative Stress Index-Based Score for Prognostic Prediction in Colorectal Cancer Patients Undergoing Surgery.

Authors:  Yinghao Cao; Shenghe Deng; Lizhao Yan; Junnan Gu; Fuwei Mao; Yifan Xue; Changmin Zheng; Ming Yang; Hongli Liu; Li Liu; Qian Liu; Kailin Cai
Journal:  Oxid Med Cell Longev       Date:  2021-01-09       Impact factor: 6.543

9.  A nomogram to predict the incidence of permanent stoma in elderly patients with rectal cancer.

Authors:  Chuangkun Li; Xiusen Qin; Zifeng Yang; Wentai Guo; Rongkang Huang; Huaiming Wang; Hui Wang
Journal:  Ann Transl Med       Date:  2021-02

10.  Development and Validation of a Prognostic Nomogram for Colorectal Cancer Patients With Synchronous Peritoneal Metastasis.

Authors:  Zifeng Yang; Yong Li; Xiusen Qin; Zejian Lv; Huaiming Wang; Deqing Wu; Zixu Yuan; Hui Wang
Journal:  Front Oncol       Date:  2021-07-01       Impact factor: 6.244

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