ArticleCancer immunology, immunotherapy : CII1986
A survey of some formal models in tumor immunology.
Article in Cancer immunology, immunotherapy : CII, 1986. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed.
- Spatially fractionated GRID radiation potentiates immune-mediated tumor control.Radiation oncology (London, England) · 2024Article
- Opportunities for improving brain cancer treatment outcomes through imaging-based mathematical modeling of the delivery of radiotherapy and immunotherapy.Advanced drug delivery reviews · 2022Review
- Assessing the interactions between radiotherapy and antitumour immunity.Nature reviews. Clinical oncology · 2019Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Computer technology has acquired an important role in structuring a variety of biological systems. The availability of modern powerful computers has stimulated the development of good and accurate models of biological systems. Biological systems, such as the immune response against cancer, are complex and it is difficult to experimentally control all the interacting elements constituting the immune response of a host to cancer. Complex biosystems do not always behave or act as expected during experimental investigation. In these cases computer models can be helpful in understanding the behavior of such complex systems. The purpose of this review is to consider the use of mathematical models to study the immune response against cancer. The logic and design of some operable models relevant for tumor immunology will be discussed. Special attention is given to the conceptualization of a model based upon a new hypothesis of tumor rejection presented by De Weger et al. [10]. Technical details concerning the mathematical aspects, differential equations, details on hardware and software package etc. are not included in this survey. These details are contained to in the original papers.
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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.