Risk prediction model for lung cancer incorporating metabolic markers: Development and internal validation in a Chinese population

BACKGROUND: Low‐dose computed tomography screening has been proved to reduce lung cancer mortality, however, the issues of high false‐positive rate and overdiagnosis remain unsolved. Risk prediction models for lung cancer that could accurately identify high‐risk populations may help to increase effi...

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Detalles Bibliográficos
Autores principales: Lyu, Zhangyan, Li, Ni, Chen, Shuohua, Wang, Gang, Tan, Fengwei, Feng, Xiaoshuang, Li, Xin, Wen, Yan, Yang, Zhuoyu, Wang, Yalong, Li, Jiang, Chen, Hongda, Lin, Chunqing, Ren, Jiansong, Shi, Jufang, Wu, Shouling, Dai, Min, He, Jie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Cancer Prevention
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7286442/
https://www.ncbi.nlm.nih.gov/pubmed/32253829
http://dx.doi.org/10.1002/cam4.3025

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7286442/
https://www.ncbi.nlm.nih.gov/pubmed/32253829
http://dx.doi.org/10.1002/cam4.3025

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