A prediction model for severe hematological toxicity of BTK inhibitors.

Jiang, Dan; Song, Zaiwei; Liu, Peng; Wang, Zeyuan; Zhao, Rongsheng

Jiang, Dan; Song, Zaiwei; Liu, Peng; Wang, Zeyuan; Zhao, Rongsheng.

Afiliação

Jiang D; Department of Pharmacy, Peking University Third Hospital, Beijing, 100191, China.
Song Z; Institute for Drug Evaluation, Peking University Health Science Center, Beijing, 100191, China.
Liu P; Therapeutic Drug Monitoring and Clinical Toxicology Center, Peking University, Beijing, 100191, China.
Wang Z; Department of Pharmacy Administration and Clinical Pharmacy, School of Pharmaceutical Sciences, Peking University, Beijing, 100191, China.
Zhao R; Department of Pharmacy, Peking University Third Hospital, Beijing, 100191, China.

Ann Hematol ; 102(10): 2765-2777, 2023 Oct.

Article em En | MEDLINE | ID: mdl-37491631

Assuntos

Pesquisa Biomédica; Masculino; Humanos; Idoso; Feminino; Aspartato Aminotransferases; China; Fibrinogênio; Hospitais

Palavras-chave

BTK inhibitor; Hematological toxicity; Logistic regression; Machine learning; Prediction model; XGBoost

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Pesquisa Biomédica Tipo de estudo: Prognostic_studies / Risk_factors_studies Aspecto: Ethics Limite: Aged / Female / Humans / Male País/Região como assunto: Asia Idioma: En Revista: Ann Hematol Ano de publicação: 2023 Tipo de documento: Article

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