Dead or alive? Pitfall of survival analysis with TCGA datasets.

Idogawa, Masashi; Koizumi, Masayo; Hirano, Tomomi; Tange, Shoichiro; Nakase, Hiroshi; Tokino, Takashi

Idogawa, Masashi; Koizumi, Masayo; Hirano, Tomomi; Tange, Shoichiro; Nakase, Hiroshi; Tokino, Takashi.

Afiliación

Idogawa M; Department of Medical Genome Sciences, Research Institute for Frontier Medicine, Sapporo Medical University School of Medicine, Sapporo, Japan.
Koizumi M; Department of Gastroenterology and Hepatology, Sapporo Medical University School of Medicine, Sapporo, Japan.
Hirano T; Department of Medical Genome Sciences, Research Institute for Frontier Medicine, Sapporo Medical University School of Medicine, Sapporo, Japan.
Tange S; Department of Medical Genome Sciences, Research Institute for Frontier Medicine, Sapporo Medical University School of Medicine, Sapporo, Japan.
Nakase H; Department of Medical Genome Sciences, Research Institute for Frontier Medicine, Sapporo Medical University School of Medicine, Sapporo, Japan.
Tokino T; Department of Gastroenterology and Hepatology, Sapporo Medical University School of Medicine, Sapporo, Japan.

Cancer Biol Ther ; 22(10-12): 527-528, 2021 12 02.

Article en En | MEDLINE | ID: mdl-34530682

Asunto(s)

Pronóstico; Humanos; Estimación de Kaplan-Meier; Análisis de Supervivencia

Palabras clave

Clinical data; KaplanMeier method; TCGA; reproducibility; survival analysis

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Pronóstico Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Cancer Biol Ther Asunto de la revista: NEOPLASIAS / TERAPEUTICA Año: 2021 Tipo del documento: Article País de afiliación: Japón Pais de publicación: Estados Unidos

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