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PubMed ID:
31412790
Public Release Type:
Journal
Publication Year: 2019
Affiliation: RAND Corporation, 1776 Main St, Santa Monica, CA, 90401, USA. parast@rand.org.; RAND Corporation, 1776 Main St, Santa Monica, CA, 90401, USA.; RAND Corporation, 20 Park Plaza # 920, Boston, MA, 02116, USA.
DOI:
https://doi.org/10.1186/s12874-019-0812-y
Authors:
Parast Layla, Mathews Megan, Friedberg Mark W
Request IDs:
20673
,
22454
Studies:
Diabetes Prevention Program
Dynamic risk models, which incorporate disease-free survival and repeated measurements over time, might yield more accurate predictions of future health status compared to static models. The objective of this study was to develop and apply a dynamic prediction model to estimate the risk of developing type 2 diabetes mellitus.
