Related Experiment Video
Updated: Jul 28, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
A catalog of prostate cancer nomograms
P L Ross1, P T Scardino, M W Kattan
1Department of Urology, Memorial Sloan-Kettering Cancer Center, New York, New York 10021, USA.
Purpose:
Prediction is central to the management of prostate cancer. Nomograms are devices that make predictions. We organized many nomograms for prostate cancer.
Materials And Methods:
Using MEDLINE a literature search was performed on prostate cancer nomograms from January 1966 to February 2000. We recorded input variables, prediction form, the number of patients used to develop the nomogram and the outcome being predicted. We also recorded the accuracy measures reported by the original authors and whether the nomograms have withstood validation. In addition, we noted whether the nomograms were proprietary or in the public domain. Each nomogram was classified into patient clinical disease state and the outcome being predicted.
Results:
The literature search generated 42 published nomograms that may be applied to patients in various clinical stages of disease. Of the 42 nomograms only 18 had undergone validation, of which 2 partially failed. Few nomograms have been compared for predictive superiority and none appears to have been compared with clinical judgment alone.
Conclusions:
Patients with prostate cancer need accurate predictions. Prognostic nomograms are available for many clinical states and outcomes, and may provide the most accurate predictions currently available. Selection among them and progress in this field are hampered by the lack of comparisons for predictive accuracy.
More Related Videos
06:46Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
07:13Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
Published on: April 18, 2025