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Independent action models and prediction of combination treatment effects for response rate, duration of response and tumor size change in oncology drug development.
Sun, Linda Z; Wu, Cai; Li, Xiaoyun; Chen, Cong; Schmidt, Emmett V.
Afiliación
  • Sun LZ; Biostatistics and Research Decision Sciences, Merck & Co., Inc., Kenilworth, NJ 07033, USA. Electronic address: linda_sun@merck.com.
  • Wu C; Biostatistics and Research Decision Sciences, Merck & Co., Inc., Kenilworth, NJ 07033, USA.
  • Li X; Biostatistics and Research Decision Sciences, Merck & Co., Inc., Kenilworth, NJ 07033, USA.
  • Chen C; Biostatistics and Research Decision Sciences, Merck & Co., Inc., Kenilworth, NJ 07033, USA.
  • Schmidt EV; Oncology Early Development, Merck & Co., Inc., Kenilworth, NJ 07033, USA.
Contemp Clin Trials ; 106: 106434, 2021 07.
Article en En | MEDLINE | ID: mdl-34004341
An unprecedented number of new cancer targets are in development, and most are being developed in combination therapies. Early oncology development is strategically challenged in choosing the best combinations to move forward to late stage development. The most common early endpoints to be assessed in such decision-making include objective response rate, duration of response and tumor size change. In this paper, using independent-drug-action and Bliss-drug-independence concepts as a foundation, we introduce simple models to predict combination therapy efficacy for duration of response and tumor size change. These models complement previous publications using the independent action models (Palmer 2017, Schmidt 2020) to predict progression-free survival and objective response rate and serve as new predictive models to understand drug combinations for early endpoints. The models can be applied to predict the combination treatment effect for early endpoints given monotherapy data, or to estimate the possible effect of one monotherapy in the combination if data are available from the combination therapy and the other monotherapy. Such quantitative work facilitates strategic planning and decision making in early stage oncology drug development.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neoplasias Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Contemp Clin Trials Asunto de la revista: MEDICINA / TERAPEUTICA Año: 2021 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neoplasias Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Contemp Clin Trials Asunto de la revista: MEDICINA / TERAPEUTICA Año: 2021 Tipo del documento: Article
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