Using First-Passage Times to Analyze Tumor Growth Delay
A central aspect of in vivo experiments with anticancer therapies is the comparison of the effect of different therapies, or doses of the same therapeutic agent, on tumor growth. One of the most popular clinical endpoints is tumor growth delay, which measures the effect of treatment on the time requ...
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doaj-f5b32ffac5d34b34835bd32fecafa2f12021-03-18T00:04:30ZengMDPI AGMathematics2227-73902021-03-01964264210.3390/math9060642Using First-Passage Times to Analyze Tumor Growth DelayPatricia Román-Román0Sergio Román-Román1Juan José Serrano-Pérez2Francisco Torres-Ruiz3Departamento de Estadística e Investigación Operativa, Facultad de Ciencias, Universidad de Granada, Avenida Fuente Nueva s/n, 18071 Granada, SpainDépartement de Recherche Translationnelle, Institut Curie, CEDEX 05, 75248 Paris, FranceDepartamento de Estadística e Investigación Operativa, Facultad de Ciencias, Universidad de Granada, Avenida Fuente Nueva s/n, 18071 Granada, SpainDepartamento de Estadística e Investigación Operativa, Facultad de Ciencias, Universidad de Granada, Avenida Fuente Nueva s/n, 18071 Granada, SpainA central aspect of in vivo experiments with anticancer therapies is the comparison of the effect of different therapies, or doses of the same therapeutic agent, on tumor growth. One of the most popular clinical endpoints is tumor growth delay, which measures the effect of treatment on the time required for tumor volume to reach a specific value. This effect has been analyzed through a variety of statistical methods: conventional descriptive analysis, linear regression, Cox regression, etc. We propose a new approach based on stochastic modeling of tumor growth and the study of first-passage time variables. This approach allows us to prove that the time required for tumor volume to reach a specific value must be determined empirically as the average of the times required for the volume of individual tumors to reach said value instead of the time required for the average volume of the tumors to reach the value of interest. In addition, we define several measures in random environments to compare the time required for the tumor volume to multiply k times its initial volume in control, as well as treated groups, and the usefulness of these measures is illustrated by means of an application to real data.https://www.mdpi.com/2227-7390/9/6/642tumor growthtumor growth delay measurementsfirst-passage timesdiffusion processes |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Patricia Román-Román Sergio Román-Román Juan José Serrano-Pérez Francisco Torres-Ruiz |
spellingShingle |
Patricia Román-Román Sergio Román-Román Juan José Serrano-Pérez Francisco Torres-Ruiz Using First-Passage Times to Analyze Tumor Growth Delay Mathematics tumor growth tumor growth delay measurements first-passage times diffusion processes |
author_facet |
Patricia Román-Román Sergio Román-Román Juan José Serrano-Pérez Francisco Torres-Ruiz |
author_sort |
Patricia Román-Román |
title |
Using First-Passage Times to Analyze Tumor Growth Delay |
title_short |
Using First-Passage Times to Analyze Tumor Growth Delay |
title_full |
Using First-Passage Times to Analyze Tumor Growth Delay |
title_fullStr |
Using First-Passage Times to Analyze Tumor Growth Delay |
title_full_unstemmed |
Using First-Passage Times to Analyze Tumor Growth Delay |
title_sort |
using first-passage times to analyze tumor growth delay |
publisher |
MDPI AG |
series |
Mathematics |
issn |
2227-7390 |
publishDate |
2021-03-01 |
description |
A central aspect of in vivo experiments with anticancer therapies is the comparison of the effect of different therapies, or doses of the same therapeutic agent, on tumor growth. One of the most popular clinical endpoints is tumor growth delay, which measures the effect of treatment on the time required for tumor volume to reach a specific value. This effect has been analyzed through a variety of statistical methods: conventional descriptive analysis, linear regression, Cox regression, etc. We propose a new approach based on stochastic modeling of tumor growth and the study of first-passage time variables. This approach allows us to prove that the time required for tumor volume to reach a specific value must be determined empirically as the average of the times required for the volume of individual tumors to reach said value instead of the time required for the average volume of the tumors to reach the value of interest. In addition, we define several measures in random environments to compare the time required for the tumor volume to multiply k times its initial volume in control, as well as treated groups, and the usefulness of these measures is illustrated by means of an application to real data. |
topic |
tumor growth tumor growth delay measurements first-passage times diffusion processes |
url |
https://www.mdpi.com/2227-7390/9/6/642 |
work_keys_str_mv |
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