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...

Full description

Bibliographic Details
Main Authors: Patricia Román-Román, Sergio Román-Román, Juan José Serrano-Pérez, Francisco Torres-Ruiz
Format: Article
Language:English
Published: MDPI AG 2021-03-01
Series:Mathematics
Subjects:
Online Access:https://www.mdpi.com/2227-7390/9/6/642
id doaj-f5b32ffac5d34b34835bd32fecafa2f1
record_format Article
spelling 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 AT patriciaromanroman usingfirstpassagetimestoanalyzetumorgrowthdelay
AT sergioromanroman usingfirstpassagetimestoanalyzetumorgrowthdelay
AT juanjoseserranoperez usingfirstpassagetimestoanalyzetumorgrowthdelay
AT franciscotorresruiz usingfirstpassagetimestoanalyzetumorgrowthdelay
_version_ 1724218011057913856