I have recently shown that the number of rate-limiting driver events per tumor can be estimated from the age distribution of cancer incidence using the gamma/Erlang probability distribution. It is important to understand how these predictions relate to established risk factors. Methods: The number of rate-limiting driver events per tumor was estimated using the gamma/Erlang distribution and correlated to the percentage of cancer cases attributable to modifiable risk factors. Results: The

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... ed number of rate-limiting driver events per tumor strongly correlates with the proportion of cancer cases attributable to modifiable risk factors for all cancers except those induced by infection or ultraviolet radiation. The correlation was confirmed for three countries, three corresponding incidence databases and risk estimation studies, as well as for both sexes: USA, males [r=0.80, P=0.002], females [r=0.81, P=0.0003]; England, males [r=0.90, P<0.0001], females [r=0.67, P=0.002]; Australia, males [r=0.90, P=0.0004], females [r=0.68, P=0.01]. Conclusions: It is thus confirmed that predictions based on interpreting the age distribution of cancer incidence as the gamma/Erlang probability distribution have biological meaning, validating the underlying Poisson process as the law governing the development of the majority of cancer types, especially those driven by chemical mutagens. Importantly, this study suggests that the majority of driver events (60-80% in males, 50-70% in females) are induced by anthropogenic carcinogens, and not by cell replication errors or other internal processes.