Development of scoring system for risk stratification in clinical medicine : a step-by-step tutorial
Zhang, Zhongheng ; Zhang, Haoyang LU
and Khanal, Mahesh Kumar
(2017)
In Annals of Translational Medicine
5(21).
p.1-9
- Abstract
Risk scores play an important role in clinical medicine. With advances in information technology and availability of electronic healthcare record, scoring systems of less commonly seen diseases and population can be developed. The aim of the article is to provide a tutorial on how to develop and validate risk scores based on a virtual dataset by using R software. The dataset we generated including numeric and categorical variables and firstly the numeric variables would be converted to factor variables according to cutoff points identified by the LOESS smoother. Then risk points of each variable, which are related to the coefficients in logistic regression, are assigned to each level of the converted factor variables and other... (More)
Risk scores play an important role in clinical medicine. With advances in information technology and availability of electronic healthcare record, scoring systems of less commonly seen diseases and population can be developed. The aim of the article is to provide a tutorial on how to develop and validate risk scores based on a virtual dataset by using R software. The dataset we generated including numeric and categorical variables and firstly the numeric variables would be converted to factor variables according to cutoff points identified by the LOESS smoother. Then risk points of each variable, which are related to the coefficients in logistic regression, are assigned to each level of the converted factor variables and other categorical variables. Finally, the total score is calculated for each subject to represent the prediction of the outcome event probability. The original dataset is split into training and validation subsets. Discrimination and calibration are evaluated in the validation subset. R codes with explanations are presented in the main text.
(Less)
- author
- Zhang, Zhongheng
; Zhang, Haoyang
LU
and Khanal, Mahesh Kumar
- publishing date
- 2017-11
- type
- Contribution to journal
- publication status
- published
- in
- Annals of Translational Medicine
- volume
- 5
- issue
- 21
- article number
- 436
- pages
- 1 - 9
- publisher
- AME Publishing Company
- external identifiers
-
- scopus:85032798504
- pmid:29201888
- ISSN
- 2305-5839
- DOI
- 10.21037/atm.2017.08.22
- language
- English
- LU publication?
- no
- id
- a6331510-9018-4706-89a8-2f2c310f3a8e
- date added to LUP
- 2024-02-05 16:16:18
- date last changed
- 2024-07-16 20:08:48
@article{a6331510-9018-4706-89a8-2f2c310f3a8e,
abstract = {{<p>Risk scores play an important role in clinical medicine. With advances in information technology and availability of electronic healthcare record, scoring systems of less commonly seen diseases and population can be developed. The aim of the article is to provide a tutorial on how to develop and validate risk scores based on a virtual dataset by using R software. The dataset we generated including numeric and categorical variables and firstly the numeric variables would be converted to factor variables according to cutoff points identified by the LOESS smoother. Then risk points of each variable, which are related to the coefficients in logistic regression, are assigned to each level of the converted factor variables and other categorical variables. Finally, the total score is calculated for each subject to represent the prediction of the outcome event probability. The original dataset is split into training and validation subsets. Discrimination and calibration are evaluated in the validation subset. R codes with explanations are presented in the main text.</p>}},
author = {{Zhang, Zhongheng and Zhang, Haoyang and Khanal, Mahesh Kumar}},
issn = {{2305-5839}},
language = {{eng}},
number = {{21}},
pages = {{1--9}},
publisher = {{AME Publishing Company}},
series = {{Annals of Translational Medicine}},
title = {{Development of scoring system for risk stratification in clinical medicine : a step-by-step tutorial}},
url = {{http://dx.doi.org/10.21037/atm.2017.08.22}},
doi = {{10.21037/atm.2017.08.22}},
volume = {{5}},
year = {{2017}},
}