Evidence map›Paper›PMID 35710563›Full record

ArticleScientific reports2022

Extended transit compartment model to describe tumor delay using Coxian distribution.

Jong Hyuk Byun, In-Soo Yoon, Song Yi Lee, Hyun-Jong Cho, Il Hyo Jung

Abstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Jong Hyuk ByunDepartment of Mathematics, College of Natural Sciences, Pusan National University, Busan, 46241, South Korea.
In-Soo YoonDepartment of Manufacturing Pharmacy, College of Pharmacy and Research Institute of Drug Development, Pusan National University, Busan, 46241, South Korea.
Song Yi LeeDepartment of Pharmacy, College of Pharmacy, Kangwon National University, Chuncheon, 24341, South Korea.
Hyun-Jong ChoDepartment of Pharmacy, College of Pharmacy, Kangwon National University, Chuncheon, 24341, South Korea.
Il Hyo JungDepartment of Mathematics, College of Natural Sciences, Pusan National University, Busan, 46241, South Korea. ilhjung@pusan.ac.kr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The measured response of cell population is often delayed relative to drug injection, and individuals in a population have a specific age distribution. Common approaches for describing the delay are to apply transit compartment models (TCMs). This model reflects that all damaged cells caused by drugs suffer transition processes, resulting in death. In this study, we present an extended TCM using Coxian distribution, one of the phase-type distributions. The cell population attacked by a drug is described via age-structured models. The mortality rate of the damaged cells is expressed by a convolution of drug rate and age density. Then applying to Erlang and Coxian distribution, we derive Erlang TCM, representing the existing model, and Coxian TCMs, reflecting sudden death at all ages. From published data of drug and tumor, delays are compared after parameter estimations in both models. We investigate the dynamical changes according to the number of the compartments. Model robustness and equilibrium analysis are also performed for model validation. Coxian TCM is an extended model considering a realistic case and captures more diverse delays.

Indexed as

NeoplasmsHumansModels, Biological

Identifiers

PMID35710563
PMCPMC9203540

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.