The application of mathematical modelling to aspects of adjuvant chemotherapy scheduling.
In this paper simple models for tumour growth incorporating age-structured cell cycle dynamics are considered in the presence of two non-cross-resistant S-phase specific chemotherapeutic drugs. According to the seminal work of Goldie and Coldman, if one cannot deliver two cell cycle phase non-specific, non-cross-resistant drugs simultaneously, for example due to toxicity, and both drugs are identical apart from resistance, one should alternate their delivery as rapidly as possible. However consider S-phase specific drugs. One might speculate that, for example, alternating the two drugs at intervals of T, where T is the mean cell cycle time, is better than alternating the drugs at intervals of T/2, as the latter strategy allows the possibility of a cell cycle sanctuary. Such speculation implicitly requires a sufficiently low variance of the cell cycle time, and hence it is not clear if such reasoning prevents a generalisation of the results of Goldie and Coldman. This question is addressed in this paper via a detailed modelling investigation, as motivated by suggestions for future colorectal adjuvant chemotherapy trials and developments in hepatic arterial infusion technology. It is shown that the cell cycle distribution of the resistant cell populations is strongly influenced by the chemotherapy schedule. The consequences of this can be dramatic, and can lead to chemotherapy failure at resonant chemotherapy timings, especially for a small standard deviation of the cell cycle time. The novel aspects of this observation are highlighted compared to other models in the literature exhibiting resonant behaviour in the timing of a periodic chemotherapy protocol. The above investigation also results in the principal prediction of this paper that reducing the drug alternation time to approximately a few hours, if possible, can result in substantial improvements in predicted chemotherapy outcomes. Critically, such improvements are not predicted by the Goldie Coldman model or other chemotherapy scheduling models in the literature.
Gaffney
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EA
The school of Mathematics and Statistics, The University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK. eag@for.mat.bham.ac.uk
D000465:Algorithms; D000971:Antineoplastic Combined Chemotherapy Protocols / Q000008:administration & dosage / Q000627:therapeutic use*; D017209:Apoptosis / Q000187:drug effects; D002453:Cell Cycle / Q000187:drug effects / Q000502:physiology; D002455:Cell Division / Q000187:drug effects / Q000502:physiology; D017024:Chemotherapy, Adjuvant / Q000379:methods*; D004334:Drug Administration Schedule; D019008:Drug Resistance, Neoplasm / Q000235:genetics; D006801:Humans; D008962:Models, Theoretical; D009154:Mutation / Q000235:genetics; D009369:Neoplasms / Q000188:drug therapy / Q000473:pathology; D016196:S Phase / Q000187:drug effects / Q000502:physiology; D013997:Time Factors