Background
The causes of long-term temporal variation in the severity of skin disease - psoriasis in
particular - is currently unknown. Here we propose a mechanism - first
described in a non-dermatologic journal in 2011 by one of us - that can account for
such temporal fluctuations in psoriasis severity. We update the original model
with new insights from the psoriasis literature and with new simulations.
Methods
We suggest that stochastic interaction events between T-cells within the skin
associated lymphoid tissue - perhaps involving the
auto-catalytic TNF-alpha - can be amplified to a level where they become clinically manifest. We
report on a simple Monte-Carlo model that validates the hypothesis.
Results
The model accounts for the coexistence between the generally stable nature of disease on one
hand, and the possibility of dramatic and unforeseen exacerbations or remissions on the
other, and is able to accurately reproduce severity data derived from a cohort of 800 psoriatic
patients tracked for 20 years.
Conclusions
It is demonstrated that stochastic effects can be amplified to levels that have clinical
consequences, suggesting novel lines of clinical and laboratory investigation. We show
that the model’s explanatory power in reproducing clinical data is a necessary
consequence of its simple assumptions.