Recalibrating Risk Prediction Models by Synthesizing Data Sources: Adapting the Lung Cancer PLCO Model for Taiwan

BACKGROUND: Methods synthesizing multiple data sources without prospective datasets have been proposed for absolute risk model development. This study proposed methods for adapting risk models for another population without prospective cohorts, which would help alleviate the health disparities cause...

Descripción completa

Detalles Bibliográficos
Autores principales: Chien, Li-Hsin, Chen, Tzu-Yu, Chen, Chung-Hsing, Chen, Kuan-Yu, Hsiao, Chin-Fu, Chang, Gee-Chen, Tsai, Ying-Huang, Su, Wu-Chou, Huang, Ming-Shyan, Chen, Yuh-Min, Chen, Chih-Yi, Liang, Sheng-Kai, Chen, Chung-Yu, Wang, Chih-Liang, Hung, Hsiao-Han, Jiang, Hsin-Fang, Hu, Jia-Wei, Rothman, Nathaniel, Lan, Qing, Liu, Tsang-Wu, Chen, Chien-Jen, Yang, Pan-Chyr, Chang, I-Shou, Hsiung, Chao A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Association for Cancer Research 2022
Materias:
Research Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9720426/
https://www.ncbi.nlm.nih.gov/pubmed/36129788
http://dx.doi.org/10.1158/1055-9965.EPI-22-0281

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9720426/
https://www.ncbi.nlm.nih.gov/pubmed/36129788
http://dx.doi.org/10.1158/1055-9965.EPI-22-0281

Ejemplares similares