A nomogram to predict outcomes of lung cancer patients after pneumonectomy based on 47 indicators

AIMS: We aimed to establish a nomogram for lung cancer using patients' characteristics and potential hematological biomarkers. METHODS: Principle component analysis was used to reduce the dimensions of the data, and each component was transformed into categorical variables based on cutoff value...

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Detalles Bibliográficos
Autores principales: Cheng, Bo, Wang, Cong, Zou, Bing, Huang, Di, Yu, Jinming, Cheng, Yufeng, Meng, Xue
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Clinical Cancer Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7013057/
https://www.ncbi.nlm.nih.gov/pubmed/31899603
http://dx.doi.org/10.1002/cam4.2805

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7013057/
https://www.ncbi.nlm.nih.gov/pubmed/31899603
http://dx.doi.org/10.1002/cam4.2805

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