Russian scientist finds a new way to predict cancer development

(Moscow Institute of Physics and Technology) Aleksey V. Belikov, a scientist from the MIPT Laboratory of Innovative Medicine and Agrobiotechnology, used the publicly available data on 20 million cancer cases and examined 16 probability distributions, finding that the incidence of 20 most prevalent cancer types in relation to patients’ age closely follows the Erlang probability distribution, which is widely used in telecommunications for incoming call simulations. Notably, it is the only probability distribution that describes the waiting time for several random events, such as DNA mutations.