ArticlePeerJ2019
A simple model of a growing tumour.
Article in PeerJ, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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.
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.
Who cites it
6 citing papers in PubMed.
- A missed synthesis from the 1930s: Teorell, Mayneord, and the origins of physiological PK-TGI modelling.Journal of pharmacokinetics and pharmacodynamics · 2026Article
- [A coupled diffusion-based model of interaction between tumor metastasis and myeloid-derived suppressive cells].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2025Article
- Semi-mechanistic efficacy model for PARP + ATR inhibitors-application to rucaparib and talazoparib in combination with gartisertib in breast cancer PDXs.British journal of cancer · 2025Article
- Radius additivity score: a novel combination index for tumour growth inhibition in fixed-dose xenograft studies.Frontiers in pharmacology · 2023Article
- Exploring a model-based analysis of patient derived xenograft studies in oncology drug development.PeerJ · 2021Article
- A simple model of a growing tumour.PeerJ · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This paper presents the CellCycler, a model of a growing tumour which aims to simulate and predict the effect of treatment on xenograft studies or in the clinic. The model, which is freely available as a web application, uses ordinary differential equations (ODEs) to simulate cells as they pass through the phases of the cell cycle. However the guiding philosophy of the model is that it should only use parameters that can be observed or reasonably well approximated. There is no representation of the complex internal dynamics of each cell; instead the level of analysis is limited to cell state observables such as cell phase, apoptosis, and damage. We show that this approach, while limited in many respects, still naturally accounts for a heteregenous cell population with varying doubling time, and closely captures the dynamics of a growing tumour as it is exposed to treatment. The program is demonstrated using three case studies.
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What OpenQuestion holds
Registered trials
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.