Literature DB >> 29680180

Nomograms are key decision-making tools in prostate cancer radiation therapy.

Sarah Caulfield1, Gerard Menezes1, Laure Marignol1, Claire Poole2.   

Abstract

BACKGROUND: The use of nomograms for predicting clinical endpoints has been well documented. Nomograms provide an individualized prognosis and help clinicians determine the effectiveness of treatment for a given patient. Early identification of potential treatment failure or toxicity allows alternative approaches to be considered, reducing unnecessary treatment, morbidity, and cost. This review aims to evaluate clinical potential of nomogram use for the management of prostate cancer radiotherapy patients.
METHODS: PubMed, Embase, and Scopus were searched for literature published between 2006 and 2016. The reported correlation between measured and nomogram-predicted probabilities of biochemical control, disease progression, survival and toxicity was reviewed, through an analysis of concordance indexes and areas under the curves.
RESULTS: Sixteen studies were reviewed. Outcomes predicted by the nomogram were very close to outcomes measured (concordance index of 0.7 and above) in the majority. But a combination of under and overestimation of outcome was also reported. The predictive accuracy of nomograms was very variable, however, most nomograms had accuracy greater than chance, indicated by a concordance index higher than 0.5.
CONCLUSION: Nomograms can be used as prognostic guides to aid clinical decision-making for prostate cancer patients until further research addresses the limitations presented in this review. Strict definitions of end points should be added to future models and perhaps models could be enhanced with the incorporation of genomic variables or tumor specific parameters.
Copyright © 2018 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Decision-making tool; Individualized prognosis; Nomograms; Prostate cancer

Mesh:

Year:  2018        PMID: 29680180     DOI: 10.1016/j.urolonc.2018.03.017

Source DB:  PubMed          Journal:  Urol Oncol        ISSN: 1078-1439            Impact factor:   3.498


  12 in total

1.  Nomograms for predicting long-term overall survival and cancer-specific survival in patients with primary urethral carcinoma: a population-based study.

Authors:  Hao Zi; Lei Gao; Zhaohua Yu; Chaoyang Wang; Xuequn Ren; Jun Lyu; Xiaodong Li
Journal:  Int Urol Nephrol       Date:  2019-10-14       Impact factor: 2.370

2.  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

3.  The Number of Lymph Nodes Examined is Associated with Survival Outcomes of Neuroendocrine Tumors of the Jejunum and Ileum (siNET): Development and Validation of a Prognostic Model Based on SEER Database.

Authors:  Peng Wang; Erlin Chen; Mingjie Xie; Wei Xu; Chaoyang Ou; Zhou Zhou; Yuanjie Niu; Wei Song; Qingfeng Ni; Jianwei Zhu
Journal:  J Gastrointest Surg       Date:  2022-06-10       Impact factor: 3.267

4.  Prognostic analysis and clinical characteristics of dual primary lung cancer: a population study based on surveillance, epidemiology, and end results (SEER) database.

Authors:  Guanghui Wang; Yukai Zeng; Haotian Zheng; Xiaogang Zhao; Yadong Wang; Hongchang Shen; Jiajun Du
Journal:  Gen Thorac Cardiovasc Surg       Date:  2022-03-22

5.  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

6.  Development and validation of a SEER-based prognostic nomogram for patients with bone metastatic prostate cancer.

Authors:  Guangdong Hou; Yu Zheng; Di Wei; Xi'an Li; Fuli Wang; Jingyang Tian; Geng Zhang; Fei Yan; Zheng Zhu; Ping Meng; Jiarui Yuan; Ming Gao; Zhibin Li; Bin Zhang; Zibao Xing; Jianlin Yuan
Journal:  Medicine (Baltimore)       Date:  2019-09       Impact factor: 1.817

7.  Circulating tumor cells as a new predictive and prognostic factor in patients with small cell lung cancer.

Authors:  Pei-Pei Wang; Si-Hong Liu; Cun-Te Chen; Lin Lv; Dan Li; Qiong-Yao Liu; Guo-Long Liu; Yong Wu
Journal:  J Cancer       Date:  2020-02-03       Impact factor: 4.207

8.  Prognostic Factors and Nomograms to Predict Overall and Cancer-Specific Survival for Children with Wilms' Tumor.

Authors:  Fucai Tang; Hanbin Zhang; Zechao Lu; Jiamin Wang; Chengwu He; Zhaohui He
Journal:  Dis Markers       Date:  2019-12-03       Impact factor: 3.434

9.  Nomogram Model for Dynamic and Individual Prediction of Cardiac Response and Survival for Light Chain Amyloidosis in 737 Patients With Cardiac Involvement.

Authors:  Yang Li; Yanze Cao; Mingxin Zheng; Jiaqi Hu; Wei Yan; Xiaoyu Liu; Aijun Liao; Wei Yang; Jian Li; Huihan Wang
Journal:  Front Oncol       Date:  2021-12-09       Impact factor: 6.244

10.  Development and Validation of a Personalized Prognostic Prediction Model for Patients With Spinal Cord Astrocytoma.

Authors:  Sheng Yang; Xun Yang; Huiwen Wang; Yuelin Gu; Jingjing Feng; Xianfeng Qin; Chaobo Feng; Yufeng Li; Lijun Liu; Guoxin Fan; Xiang Liao; Shisheng He
Journal:  Front Med (Lausanne)       Date:  2022-01-18
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