ArticleScientific reports2020
Statistical analysis of longitudinal data on tumour growth in mice experiments.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Hyaluronic Acid-Modified Nanoparticles Loaded with Cabazitaxel: A Promising Nanomedicine for Malignant Prostate Tumors.Current drug delivery · 2026Article
- Reanalysis of in vivo drug synergy validation study rules out synergy in most cases.Nature communications · 2025Article
- biogrowleR: Enhancing Longitudinal Data Analysis.Journal of mammary gland biology and neoplasia · 2025Article
- Co-inhibition of Notch1 and ChK1 triggers genomic instability and melanoma cell death increasing the lifespan of mice bearing melanoma brain metastasis.Journal of experimental & clinical cancer research : CR · 2025Article
- Functional genomics pipeline identifies CRL4 inhibition for the treatment of ovarian cancer.Clinical and translational medicine · 2025Article
- Lessons learned in application driven imaging agent design for image-guided surgery.European journal of nuclear medicine and molecular imaging · 2024Review
- Mathematical Modeling of Tumor Growth in Preclinical Mouse Models with Applications in Biomarker Discovery and Drug Mechanism Studies.Cancer research communications · 2024Article
- Exploring acenocoumarol and silodosin in non-small cell lung cancer: Insights into EGFR-linked signaling mechanisms.F1000Research · 2024Article
- Leveraging homologous hypotheses for increased efficiency in tumor growth curve testing.Scientific reports · 2023Article
- Effects of regorafenib on the mononuclear/phagocyte system and how these contribute to the inhibition of colorectal tumors in mice.European journal of medical research · 2023Article
- Oxidative Stress-Induced Silver Nano-Carriers for Chemotherapy.Pharmaceuticals (Basel, Switzerland) · 2022Article
- Multiscale computational modeling of cancer growth using features derived from microCT images.Scientific reports · 2021Article
- Article
- Temporal dynamics of mesenchymal stem cell administration influence immune modulation in a 4T1 breast cancer model.Cell transplantationArticle
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We consider mice experiments where tumour cells are injected so that a tumour starts to grow. When the tumour reaches a certain volume, mice are randomized into treatment groups. Tumour volume is measured repeatedly until the mouse dies or is sacrificed. Tumour growth rates are compared between groups. We propose and evaluate linear regression for analysis accounting for the correlation among repeated measurements per mouse. More specifically, we examined five models with three different variance-covariance structures in order to recommend the least complex method for small to moderate sample sizes encountered in animal experiments. We performed a simulation study based on data from three previous experiments to investigate the properties of estimates of the difference between treatment groups. Models were estimated via marginal modelling using generalized least squares and restricted maximum likelihood estimation. A model with an autoregressive (AR-1) covariance structure was efficient and unbiased retaining nominal coverage and type I error when the AR-1 variance-covariance matrix correctly specified the association between repeated measurements. When the variance-covariance was misspecified, that model was still unbiased but the type I error and the coverage rates were affected depending on the degree of misspecification. A linear regression model with an autoregressive (AR-1) covariance structure is an adequate model to analyse experiments that compare tumour growth rates between treatment groups.
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