Herpes zoster or shingles is a frequent occurrence in both elderly individu
als and immunocompromised hosts. The pain associated with herpes zoster is
the most debilitating complication of the disease. It can be described as a
cute pain and post-herpetic neuralgia or zoster associated pain (ZAP). The
latter definition encompasses pain from the onset of disease through its re
solution and provides a convenient analytic toot for evaluation of antivira
l therapy. A heuristic examination of ZAP historical data suggests the exis
tence of three phases of pain resolution: the acute, subacute and chronic p
hases. The subacute and chronic phases comprise the post-herpetic neuralgia
(PHN) stage. Common analytic methods, such as a Kaplan-Meier survival func
tion or a Cox's model, have been used to assess the pain. However, such app
roaches do not adequately allow for phase comparison. Notably, in the clini
cal trial setting the comparison of specific treatment effects on the latte
r stages of pain are of the greatest medical relevance since this is the mo
st debilitating phase of the illness. In order to incorporate the phase-spe
cific information in the modelling of time to cessation of ZAP, we assumed
the hazard function was a stepwise constant. Utilizing the full likelihood
function, we obtained the maximum likelihood estimate for the transition ti
mes (that is, change-points), and other parameters of medical importance. T
he standard error of the change-point estimates were obtained through a boo
tstrapping method. The asymptotic properties of the parameter estimates are
also discussed. Hence, the rates of pain resolution across all phases can
be examined in order to precisely define the existence of multiple phases.
In addition, the covariates effect can be examined across phases and popula
tions, thereby allowing us to translate potential efficacy of a standard th
erapy to different populations. These results can be utilized in the design
of clinical trials or in targeting the outcome for a specific phase while
controlling for the effect of other variables. Copyright (C) 2001 John Wile
y & Sons, Ltd.