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A new method to estimate parameters of the growth model for metastatic tumours

PURPOSE: Knowledge of natural tumour growth is valuable for understanding tumour biology, optimising screening programs, prognostication, optimal scheduling of chemotherapy, and assessing tumour spread. However, mathematical modelling in individuals is hampered by the limited data available. We aime...

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Autores principales: Mehrara, Esmaeil, Forssell-Aronsson, Eva, Johanson, Viktor, Kölby, Lars, Hultborn, Ragnar, Bernhardt, Peter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3663680/
https://www.ncbi.nlm.nih.gov/pubmed/23656695
http://dx.doi.org/10.1186/1742-4682-10-31
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author Mehrara, Esmaeil
Forssell-Aronsson, Eva
Johanson, Viktor
Kölby, Lars
Hultborn, Ragnar
Bernhardt, Peter
author_facet Mehrara, Esmaeil
Forssell-Aronsson, Eva
Johanson, Viktor
Kölby, Lars
Hultborn, Ragnar
Bernhardt, Peter
author_sort Mehrara, Esmaeil
collection PubMed
description PURPOSE: Knowledge of natural tumour growth is valuable for understanding tumour biology, optimising screening programs, prognostication, optimal scheduling of chemotherapy, and assessing tumour spread. However, mathematical modelling in individuals is hampered by the limited data available. We aimed to develop a method to estimate parameters of the growth model and formation rate of metastases in individual patients. MATERIALS AND METHODS: Data from one patient with liver metastases from a primary ileum carcinoid and one patient with lung metastases from a primary renal cell carcinoma were used to demonstrate this new method. Metastatic growth models were estimated by direct curve fitting, as well as with the new proposed method based on the relationship between tumour growth rate and tumour volume. The new model was derived from the Gompertzian growth model by eliminating the time factor (age of metastases), which made it possible to perform the calculations using data from all metastases in each patient. Finally, the formation time of each metastasis and, consecutively, the formation rate of metastases in each patient were estimated. RESULTS: With limited measurements in clinical studies, fitting different growth curves was insufficient to estimate true tumour growth, even if patients were followed for several years. Growth of liver metastases was well described with a general growth model for all metastases. However, the lung metastases from renal cell carcinoma were better described by heterogeneous exponential growth with various growth rates. CONCLUSION: Analysis of the regression of tumour growth rate with the logarithm of tumour volume can be used to estimate parameters of the tumour growth model and metastasis formation rates, and therefore the number and size distribution of metastases in individuals.
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spelling pubmed-36636802013-05-31 A new method to estimate parameters of the growth model for metastatic tumours Mehrara, Esmaeil Forssell-Aronsson, Eva Johanson, Viktor Kölby, Lars Hultborn, Ragnar Bernhardt, Peter Theor Biol Med Model Research PURPOSE: Knowledge of natural tumour growth is valuable for understanding tumour biology, optimising screening programs, prognostication, optimal scheduling of chemotherapy, and assessing tumour spread. However, mathematical modelling in individuals is hampered by the limited data available. We aimed to develop a method to estimate parameters of the growth model and formation rate of metastases in individual patients. MATERIALS AND METHODS: Data from one patient with liver metastases from a primary ileum carcinoid and one patient with lung metastases from a primary renal cell carcinoma were used to demonstrate this new method. Metastatic growth models were estimated by direct curve fitting, as well as with the new proposed method based on the relationship between tumour growth rate and tumour volume. The new model was derived from the Gompertzian growth model by eliminating the time factor (age of metastases), which made it possible to perform the calculations using data from all metastases in each patient. Finally, the formation time of each metastasis and, consecutively, the formation rate of metastases in each patient were estimated. RESULTS: With limited measurements in clinical studies, fitting different growth curves was insufficient to estimate true tumour growth, even if patients were followed for several years. Growth of liver metastases was well described with a general growth model for all metastases. However, the lung metastases from renal cell carcinoma were better described by heterogeneous exponential growth with various growth rates. CONCLUSION: Analysis of the regression of tumour growth rate with the logarithm of tumour volume can be used to estimate parameters of the tumour growth model and metastasis formation rates, and therefore the number and size distribution of metastases in individuals. BioMed Central 2013-05-09 /pmc/articles/PMC3663680/ /pubmed/23656695 http://dx.doi.org/10.1186/1742-4682-10-31 Text en Copyright © 2013 Mehrara et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Mehrara, Esmaeil
Forssell-Aronsson, Eva
Johanson, Viktor
Kölby, Lars
Hultborn, Ragnar
Bernhardt, Peter
A new method to estimate parameters of the growth model for metastatic tumours
title A new method to estimate parameters of the growth model for metastatic tumours
title_full A new method to estimate parameters of the growth model for metastatic tumours
title_fullStr A new method to estimate parameters of the growth model for metastatic tumours
title_full_unstemmed A new method to estimate parameters of the growth model for metastatic tumours
title_short A new method to estimate parameters of the growth model for metastatic tumours
title_sort new method to estimate parameters of the growth model for metastatic tumours
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3663680/
https://www.ncbi.nlm.nih.gov/pubmed/23656695
http://dx.doi.org/10.1186/1742-4682-10-31
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