ReviewCancer informatics2014
Growth rate analysis and efficient experimental design for tumor xenograft studies.
Review in Cancer informatics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 93 papers.
What it found
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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.
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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.
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Who cites it
93 citing papers in PubMed, 137 citations in OpenAlex.
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- Systemically inducing trained immunity overcomes solid tumors' immunosuppressive microenvironment.Science advances · 2026Article
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- Mapping the genetic landscape establishing a tumor immune microenvironment favorable for anti-PD-1 response.Cell reports · 2025Article
- hu128.1, a humanized antibody targeting transferrin receptor 1, blocks erythroleukemia growth in xenograft mouse models.Haematologica · 2025Article
- Functional genomics pipeline identifies CRL4 inhibition for the treatment of ovarian cancer.Clinical and translational medicine · 2025Article
- The E2F4 transcriptional repressor is a key mechanistic regulator of colon cancer resistance tobioRxiv : the preprint server for biology · 2025Article
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- Receptor tyrosine kinase inhibition leads to regression of acral melanoma by targeting the tumor microenvironment.Journal of experimental & clinical cancer research : CR · 2024Article
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- Deep PIM kinase substrate profiling reveals new rational cotherapeutic strategies for acute myeloid leukemia.Blood advances · 2024Article
- Bicalutamide Enhances Conventional Chemotherapy in In Vitro and In Vivo Assays Using Human and Canine Inflammatory Mammary Cancer Cell Lines.International journal of molecular sciences · 2024Article
- Receptor tyrosine kinase inhibition leads to regression of acral melanoma by targeting the tumor microenvironment.bioRxiv : the preprint server for biology · 2024Article
- Targeting neddylation and sumoylation in chemoresistant triple negative breast cancer.NPJ breast cancer · 2024Article
- Coiled-Coil Protein Hydrogels Engineered with Minimized Fiber Diameters for Sustained Release of Doxorubicin in Triple-Negative Breast Cancer.ACS biomaterials science & engineering · 2024Article
33 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Human tumor xenograft studies are the primary means to evaluate the biological activity of anticancer agents in late-stage preclinical drug discovery. The variability in the growth rate of human tumors established in mice and the small sample sizes make rigorous statistical analysis critical. The most commonly used summary of antitumor activity for these studies is the T/C ratio. However, alternative methods based on growth rate modeling can be used. Here, we describe a summary metric called the rate-based T/C, derived by fitting each animal's tumor growth to a simple exponential model. The rate-based T/C uses all of the data, in contrast with the traditional T/C, which only uses a single measurement. We compare the rate-based T/C with the traditional T/C and assess their performance through a bootstrap analysis of 219 tumor xenograft studies. We find that the rate-based T/C requires fewer animals to achieve the same power as the traditional T/C. We also compare 14-day studies with 21-day studies and find that 14-day studies are more cost efficient. Finally, we perform a power analysis to determine an appropriate sample size.
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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.