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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2019
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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 |
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author | Feng, Yan Wang, Xiaoning Suryawanshi, Satyendra Bello, Akintunde Roy, Amit |
author_facet | Feng, Yan Wang, Xiaoning Suryawanshi, Satyendra Bello, Akintunde Roy, Amit |
author_sort | Feng, Yan |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6875707 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-68757072019-11-29 Linking Tumor Growth Dynamics to Survival in Ipilimumab‐Treated Patients With Advanced Melanoma Using Mixture Tumor Growth Dynamic Modeling Feng, Yan Wang, Xiaoning Suryawanshi, Satyendra Bello, Akintunde Roy, Amit CPT Pharmacometrics Syst Pharmacol Research 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. John Wiley and Sons Inc. 2019-08-13 2019-11 /pmc/articles/PMC6875707/ /pubmed/31334596 http://dx.doi.org/10.1002/psp4.12454 Text en © 2019 Bristol‐Myers Squibb CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals, Inc. on behalf of the American Society for Clinical Pharmacology and Therapeutics. This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. |
spellingShingle | Research Feng, Yan Wang, Xiaoning Suryawanshi, Satyendra Bello, Akintunde Roy, Amit Linking Tumor Growth Dynamics to Survival in Ipilimumab‐Treated Patients With Advanced Melanoma Using Mixture Tumor Growth Dynamic Modeling |
title | Linking Tumor Growth Dynamics to Survival in Ipilimumab‐Treated Patients With Advanced Melanoma Using Mixture Tumor Growth Dynamic Modeling |
title_full | Linking Tumor Growth Dynamics to Survival in Ipilimumab‐Treated Patients With Advanced Melanoma Using Mixture Tumor Growth Dynamic Modeling |
title_fullStr | Linking Tumor Growth Dynamics to Survival in Ipilimumab‐Treated Patients With Advanced Melanoma Using Mixture Tumor Growth Dynamic Modeling |
title_full_unstemmed | Linking Tumor Growth Dynamics to Survival in Ipilimumab‐Treated Patients With Advanced Melanoma Using Mixture Tumor Growth Dynamic Modeling |
title_short | Linking Tumor Growth Dynamics to Survival in Ipilimumab‐Treated Patients With Advanced Melanoma Using Mixture Tumor Growth Dynamic Modeling |
title_sort | linking tumor growth dynamics to survival in ipilimumab‐treated patients with advanced melanoma using mixture tumor growth dynamic modeling |
topic | Research |
url | 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 |
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