Evidence map›Paper›PMID 24799130›Full record

ArticleJournal of theoretical biology2014

The additive damage model: a mathematical model for cellular responses to drug combinations.

Leslie Braziel Jones, Timothy W Secomb, Mark W Dewhirst, Ardith W El-Kareh

Abstract read
In one paragraph

Article in Journal of theoretical biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.5field-weighted citation impact, top 16% of its field
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

7 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Article
  3. Effect of the adsorption pH and temperature on the parameters of the Brouers-Sotolongo models.Environmental science and pollution research international · 2020
    Article
  4. Article
  5. Article
  6. Article
  7. Review
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

4 authors at 2 institutions in 1 country.

Leslie Braziel JonesDepartment of Mathematics, University of Arizona, Tucson, AZ, USA.
Timothy W SecombDepartment of Physiology, University of Arizona, Tucson, AZ, USA.
Mark W DewhirstDepartment of Radiation Oncology, Duke University Medical Center, Durham, NC, USA.
Ardith W El-KarehArizona Research Laboratories, University of Arizona, Tucson, AZ, USA. Electronic address: elkareh@u.arizona.edu.
University of Arizona · USDuke Medical Center · US

Funding

Heat And Radiation Effects On Tumor MicrocirulationR01CA040355 · NCI · DUKE UNIVERSITY · PI DEWHIRST, MARK WESLEY · 1985 to 2013
$4.5M
NCI NIH HHS CA040355NCI NIH HHS R01 CA040355
6 · The paper itself

Abstract

Mathematical models to describe dose-dependent cellular responses to drug combinations are an essential component of computational simulations for predicting therapeutic responses. Here, a new model, the additive damage model, is introduced and tested in cases where varying concentrations of two drugs are applied with a fixed exposure schedule. In the model, cell survival is determined by whether cellular damage, which depends on the concentrations of the drugs, exceeds a lethal threshold, which varies randomly in the cell population with a prescribed statistical distribution. Cellular damage is assumed to be additive, and is expressed as a sum of separate terms for each drug. Each term has a saturable dependence on drug concentration. The model has appropriate behavior over the entire range of drug concentrations, and is predictive, given single-agent dose-response data for each drug. The proposed model is compared with several other models, by testing their ability to fit 24 data sets for platinum-taxane combinations and 21 data sets for various other combinations. The Akaike Information Criterion is used to assess goodness of fit, taking into account the number of unknown parameters in each model. Overall, the additive damage model provides a better fit to the data sets than any previous model. The proposed model provides a basis for computational simulations of therapeutic responses. It predicts responses to drug combinations based on data for each drug acting as a single agent, and can be used as an improved null reference model for assessing synergy in the action of drug combinations.

Indexed as

Drug CombinationsModels, BiologicalDose-Response Relationship, DrugDrug CombinationsCellular pharmacodynamicsChemotherapyCytotoxicityDose–responseDrug synergy

Identifiers

PMID24799130
PMCPMC4367491
OpenAlexW2150498613

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.