Introduction of the Prediction model Risk Of Bias ASsessment Tool: a tool to assess risk of bias and applicability of prediction model studies
10.3760/cma.j.cn112338-20190805-00580
- VernacularTitle:预测模型研究的偏倚风险和适用性评估工具解读
- Author:
Ru CHEN
1
;
Shengfeng WANG
;
Jiachen ZHOU
;
Feng SUN
;
Wenqiang WEI
;
Siyan ZHAN
Author Information
1. 国家癌症中心/国家肿瘤临床医学研究中心/中国医学科学院北京协和医学院肿瘤医院肿瘤登记办公室，北京 100021
- Keywords:
Risk of bias;
Tool for assessment;
Prediction model studies;
Systematic review
- From:
Chinese Journal of Epidemiology
2020;41(5):776-781
- CountryChina
- Language:Chinese
-
Abstract:
This paper introduceds the tool named as "Prediction model Risk Of Bias ASsessment Tool" (PROBAST) to assess the risk of bias and applicability in prediction model studies and the relevant items and steps of assessment. PROBAST is organized into four domains including participants, predictors, outcome and analysis. These domains contain a total of 20 signaling questions to facilitate structured judgment of risk of bias occurring in study design, conduct or analysis. Through comprehensive judgment, the risk of bias and applicability of original study is categorized as high, low or unclear. PROBAST enables a focused and transparent approach to assessing the risk of bias of studies that develop, validate, or update prediction models for individualized predictions. Although PROBAST was designed for systematic reviews, it can be also used more generally in critical appraisal of prediction model studies.
