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Support to early clinical decisions in drug development and personalised medicine with checkpoint inhibitors using dynamic biomarker-overall survival models.
Bruno, René; Chanu, Pascal; Kågedal, Matts; Mercier, Francois; Yoshida, Kenta; Guedj, Jérémie; Li, Chunze; Beyer, Ulrich; Jin, Jin Y.
Afiliación
  • Bruno R; Clinical Pharmacology, Genentech-Roche, Marseille, France. rbruno100@gmail.com.
  • Chanu P; Clinical Pharmacology, Genentech-Roche, Lyon, France.
  • Kågedal M; Clinical Pharmacology, Genentech-Roche, Solna, Sweden.
  • Mercier F; Biostatistics, Roche, Basel, Switzerland.
  • Yoshida K; Clinical Pharmacology, Genentech, South San Francisco, CA, USA.
  • Guedj J; Université Paris Cité, IAME, INSERM, Paris, France.
  • Li C; Clinical Pharmacology, Genentech, South San Francisco, CA, USA.
  • Beyer U; Biostatistics, Roche, Basel, Switzerland.
  • Jin JY; Clinical Pharmacology, Genentech, South San Francisco, CA, USA.
Br J Cancer ; 129(9): 1383-1388, 2023 10.
Article en En | MEDLINE | ID: mdl-36765177
Longitudinal models of biomarkers such as tumour size dynamics capture treatment efficacy and predict treatment outcome (overall survival) of a variety of anticancer therapies, including chemotherapies, targeted therapies, immunotherapies and their combinations. These pharmacological endpoints like tumour dynamic (tumour growth inhibition) metrics have been proposed as alternative endpoints to complement the classical RECIST endpoints (objective response rate, progression-free survival) to support early decisions both at the study level in drug development as well as at the patients level in personalised therapy with checkpoint inhibitors. This perspective paper presents recent developments and future directions to enable wider and robust use of model-based decision frameworks based on pharmacological endpoints.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Medicina de Precisión / Neoplasias Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Br J Cancer Año: 2023 Tipo del documento: Article País de afiliación: Francia

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Medicina de Precisión / Neoplasias Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Br J Cancer Año: 2023 Tipo del documento: Article País de afiliación: Francia