ReviewExpert review of anticancer therapy2018
Mathematical models of tumor cell proliferation: A review of the literature.
Review in Expert review of anticancer therapy, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 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
57 citing papers in PubMed.
- Computational reactive-diffusive modeling for stratification and prognosis determination of patients with breast cancer receiving Olaparib.Scientific reports · 2023Trial
- Transition between cell states of sensitivity reveals molecular vulnerability of drug-tolerant cells.Molecular systems biology · 2025Article
- Hydrogel Micro/Nanostructures for the Delivery of Oncolytic Viruses: Overcoming Limitations and Improving Efficacy.Advanced pharmaceutical bulletin · 2025Review
- Analysing the Structural Identifiability and Observability of Mechanistic Models of Tumour Growth.Bioengineering (Basel, Switzerland) · 2025Article
- Role of intratumoral heterogeneity in metastatic progression and drug resistance.Discover oncology · 2025Review
- Quantitative Method for Monitoring Tumor Evolution During and After Therapy.Journal of personalized medicine · 2025Article
- Cell populations simulated in silico within SimulCell accurately reproduce the behaviour of experimental cell cultures.NPJ systems biology and applications · 2025Article
- The Evolution of Systems Biology and Systems Medicine: From Mechanistic Models to Uncertainty Quantification.Annual review of biomedical engineering · 2025Review
- Precision matters: the value of PET/CT and PET/MRI in the clinical management of cervical cancer.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2025Review
- Validating the predictions of mathematical models describing tumor growth and treatment response.ArXiv · 2025Article
- Proper likelihood functions for parameter estimation in S-shaped models of unperturbed tumor growth.Scientific reports · 2025Article
- Regression models for the prediction of the influence of magnesium ions on primary endothelial cell (HUVEC) proliferation and migration.Computational and structural biotechnology journal · 2025Article
- Tissue stresses caused by invasive tumour: a biomechanical model.Journal of the Royal Society, Interface · 2025Article
- Modeling of chemo-radiotherapy targeting growing vascular tumors: A continuum-level approach.PloS one · 2025Article
- A systematic review and meta-analysis of the effects of green tea extracts and polyphenols in female hormone-dependent cancers for benefit-risk evaluation.Frontiers in oncology · 2025Article
- Melatonin: a natural guardian in cancer treatment.Frontiers in pharmacology · 2025Review
- Shape modeling of longitudinal medical images: from diffeomorphic metric mapping to deep learning.Frontiers in artificial intelligence · 2025Review
- A mathematical model for predicting the spatiotemporal response of breast cancer cells treated with doxorubicin.Cancer biology & therapy · 2024Article
- Fatty acid synthase (FASN) is a tumor-cell-intrinsic metabolic checkpoint restricting T-cell immunity.Cell death discovery · 2024Article
- An agent-based modelling framework to study growth mechanisms inRoyal Society open science · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
introductionA defining hallmark of cancer is aberrant cell proliferation. Efforts to understand the generative properties of cancer cells span all biological scales: from genetic deviations and alterations of metabolic pathways to physical stresses due to overcrowding, as well as the effects of therapeutics and the immune system. While these factors have long been studied in the laboratory, mathematical and computational techniques are being increasingly applied to help understand and forecast tumor growth and treatment response. Advantages of mathematical modeling of proliferation include the ability to simulate and predict the spatiotemporal development of tumors across multiple experimental scales. Central to proliferation modeling is the incorporation of available biological data and validation with experimental data. Areas covered: We present an overview of past and current mathematical strategies directed at understanding tumor cell proliferation. We identify areas for mathematical development as motivated by available experimental and clinical evidence, with a particular emphasis on emerging, non-invasive imaging technologies. Expert commentary: The data required to legitimize mathematical models are often difficult or (currently) impossible to obtain. We suggest areas for further investigation to establish mathematical models that more effectively utilize available data to make informed predictions on tumor cell proliferation.
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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.