Medicos are increasingly turning to mathematical and computer models of disease to better understand how it works. But these models ain’t easy to build: the human body has many nonlinear properties that are hard to measure let alone model.
But mathematicians have a tool called superstatistics for dealing with nonlinear phenomena. It’s essentially the superposition of two statistical approaches that when combined can model nonlinear behavior. But it ain’t well known outside the mathematical world.
Now Leon Chen at the Massachussetts General Hospital and a buddy from England have used superstatistics for the first time in medicine to model cancer survival rates associated with metastasis (the formation of secondary tumors from cells from a primary tumor). The data is non-linear and although nobody is quite sure why, the new model offers some intriguing insights.
Metastasis puzzles medicos because it is a rather inefficient process: cancer cells generally find it hard to gain a foothold in the body. So why is it so deadly?
Chen raises the intriguing possibility that surgery to remove primary tumors may encourage the formation of blood vessels, so-called angiogenesis, elsewhere in the body. And this might have the unintended consequence of giving any cancer cells still circulating a foothold to metastasize.
That’s not a new idea and Chen points out that many factors are likely to contribute. But it’s interesting that the superstatistics bear it out
Ref: arxiv.org/abs/0711.4687: A Superstatistical Model of Metastasis and Cancer Survival