Literature DB >> 33174117

Factors affecting the survival of patients with colorectal cancer using random survival forest.

Ghodratollah Roshanaei1, Malihe Safari1, Javad Faradmal1, Mohammad Abbasi2, Salman Khazaei3.   

Abstract

PURPOSE: Colorectal cancer is one of the most common cancers and the leading cause of cancer death in Iran. This study aimed to develop and validate a random survival forest (RSF) to identify important risk factors on mortality in colorectal patients based on their demographic and clinical-related variables.
METHODS: In this retrospective cohort study, the information of 317 patients with colorectal cancer who were referred to Imam Khomeini Clinic of Hamadan during the years of 2002 to 2017 were examined. Patient survival was calculated from the time of diagnosis to death. In the present study, the RSF model was used to identify factors affecting patient survival. Also, the results of the RSF model were compared with the Cox model. The data were analyzed using R software (version 3.6.1) and survival packages.
RESULTS: One-, 2-, 3-, 4-, 5-, and 10-year survival rates of included patients were 81.4%, 63%, 57%, 52%, 45%, and 34%, respectively, and the median survival was obtained to be 53 months. The number of 150 patients was died at this time period. The four most important predictors of survival included metastasis to other organs, WBC count, disease stage, and number of lymphomas involved. RSF method predicted survival better than the conventional Cox proportional hazard model.
CONCLUSION: We found that metastasis to other organs, WBC count, disease stage, and number of lymphomas involved were the most four most important predictors of low survival for colorectal cancer patients.
© 2020. Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  Colorectal cancer; Death; Hazard; Random survival forest; Survival

Mesh:

Year:  2020        PMID: 33174117     DOI: 10.1007/s12029-020-00544-3

Source DB:  PubMed          Journal:  J Gastrointest Cancer


  4 in total

1.  Estimation of prediction error for survival models.

Authors:  Jerald F Lawless; Yan Yuan
Journal:  Stat Med       Date:  2010-01-30       Impact factor: 2.373

2.  Use of an artificial neural network to determine prognostic factors in colorectal cancer patients.

Authors:  Mahmood Reza Gohari; Akbar Biglarian; Enayatollah Bakhshi; Mohammad Amin Pourhoseingholi
Journal:  Asian Pac J Cancer Prev       Date:  2011

3.  Values of applying white blood cell counts in the prognostic evaluation of resectable colorectal cancer.

Authors:  Jing Wu; Xin-Xin Ge; Wenyu Zhu; Qiaoming Zhi; Meng-Dan Xu; Weiming Duan; Kai Chen; Fei-Ran Gong; Min Tao; Liu-Mei Shou; Meng-Yao Wu; Wen-Jie Wang
Journal:  Mol Med Rep       Date:  2019-01-10       Impact factor: 2.952

Review 4.  Epidemiology of colorectal cancer: incidence, mortality, survival, and risk factors.

Authors:  Prashanth Rawla; Tagore Sunkara; Adam Barsouk
Journal:  Prz Gastroenterol       Date:  2019-01-06
  4 in total
  1 in total

1.  Random survival forest model identifies novel biomarkers of event-free survival in high-risk pediatric acute lymphoblastic leukemia.

Authors:  Zachary S Bohannan; Frederick Coffman; Antonina Mitrofanova
Journal:  Comput Struct Biotechnol J       Date:  2022-01-06       Impact factor: 6.155

  1 in total

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