Mathematical oncology and it's application in non melanoma skin cancer - A primer for radiation oncology professionals

Oral Oncol. 2020 Apr;103:104473. doi: 10.1016/j.oraloncology.2019.104473. Epub 2020 Feb 25.


Cancers of the skin (the majority of which are basal and squamous cell skin carcinomas, but also include the rarer Merkel cell carcinoma) are overwhelmingly the most common of all types of cancer. Most of these are treated surgically, with radiation reserved for those patients with high risk features or anatomical locations less suitable for surgery. Given the high incidence of both basal and squamous cell carcinomas, as well as the relatively poor outcome for Merkel cell carcinoma, it is useful to investigate the role of other disciplines regarding their diagnosis, staging and treatment. Mathematical modelling is one such area of investigation. The use of mathematical modelling is a relatively recent addition to the armamentarium of cancer treatment. It has long been recognised that tumour growth and treatment response is a complex, non-linear biological phenomenon with many mechanisms yet to be understood. Despite decades of research, including clinical, population and basic science approaches, we continue to be challenged by the complexity, heterogeneity and adaptability of tumours, both in individual patients in the oncology clinic and across wider patient populations. Prospective clinical trials predominantly focus on average outcome, with little understanding as to why individual patients may or may not respond. The use of mathematical models may lead to a greater understanding of tumour initiation, growth dynamics and treatment response.

Keywords: Mathematical modelling; Mathematical oncology; Radiation oncology; Skin cancer.

MeSH terms

  • Humans
  • Models, Biological
  • Models, Statistical
  • Precision Medicine / methods
  • Radiation Oncologists
  • Radiation Oncology / methods*
  • Skin Neoplasms / radiotherapy*
  • Skin Neoplasms / therapy