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Linking Tumor Growth Dynamics to Survival in Ipilimumab‐Treated Patients With Advanced Melanoma Using Mixture Tumor Growth Dynamic Modeling

Early tumor assessments have been widely used to predict overall survival (OS), with potential application to dose selection and early go/no‐go decisions. Most published tumor dynamic models assume a uniform pattern of tumor growth dynamics (TGDs). We developed a mixture TGD model to characterize di...

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Detalles Bibliográficos
Autores principales: Feng, Yan, Wang, Xiaoning, Suryawanshi, Satyendra, Bello, Akintunde, Roy, Amit
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6875707/
https://www.ncbi.nlm.nih.gov/pubmed/31334596
http://dx.doi.org/10.1002/psp4.12454
Descripción
Sumario:Early tumor assessments have been widely used to predict overall survival (OS), with potential application to dose selection and early go/no‐go decisions. Most published tumor dynamic models assume a uniform pattern of tumor growth dynamics (TGDs). We developed a mixture TGD model to characterize different patterns of longitudinal tumor sizes. Data from 688 patients with advanced melanoma who received ipilimumab 3 or 10 mg/kg every 3 weeks in a phase III study (NCT01515189) were used in a TGD‐OS analysis. The mixture model described TGD profiles using three subpopulations (no‐growth, intermediate, and fast). The TGD model showed a positive exposure/dose‐response (i.e., a higher proportion of patients in no/intermediate growth subpopulations and a lower tumor growth rate with ipilimumab 10 mg/kg relative to the 3 mg/kg dose). Finally, the mixture TGD model‐based measures of tumor response provided better predictions of OS compared with the nonmixture model.