Identifying methodologies in the assessment of treatment effects on the repeated occurrences of hot flashes in postmenopausal women.
BACKGROUND
Two methods that are commonly used in most clinical trials for evaluating the effect of treatment on hot flashes are frequency only and severity score methods. However, in these crude methods, composite recurrent hot flash data on a patient are reduced to a one-dimensional summary measure, an approach which may not be optimal. In addition, the duration of a hot flash event provides additional information, which is not accounted for in the two methods mentioned above.


OBJECTIVE
We propose two new methods in the analysis of hot flash data in this paper.


METHODS
The first method utilizes a generalization of the continuation ratio model to model the severity of a hot flash event. The model accounts for individual random effects and dependence of recurrent events within an individual. The other method that accounts for the duration of a hot flash event is a 3-Dimensional (3D) score method, which incorporates hot flash information on frequency, severity, and duration.


RESULTS
Simulation studies were conducted to evaluate the properties of our proposed methods. The results indicate that our proposed generalized continuation ratio model has appreciably high power in detecting small treatment effects on severity compared with the two commonly used methods. The proposed 3D score, on the other hand, is sensitive in detecting treatment effects on both frequency and duration, but has low power in detecting treatment effects on severity alone.


CONCLUSIONS
Our proposed generalized continuation ratio model approach provides a valuable and powerful alternative to the two commonly used methods in the analysis of treatment effects on hot flash severity. Our proposed 3D score method incorporates the additional information hot flash duration provides, and is another analysis option for the practitioners to employ.
He
Weili
W
Clinical Biostatistics, Merck Research Laboratories, RY34-A316, 126 Lincoln Avenue, Rahway, NJ 07065, USA. weili_he@merck.com
Deng
Weiping
W
D000704:Analysis of Variance; D002986:Clinical Trials as Topic / Q000379:methods* / Q000706:statistics & numerical data*; D003198:Computer Simulation; D005260:Female; D019584:Hot Flashes / Q000188:drug therapy*; D006801:Humans; D016015:Logistic Models; D008390:Markov Chains; D015233:Models, Statistical; D020849:Raloxifene Hydrochloride / Q000494:pharmacology; D012008:Recurrence; D012107:Research Design; D020845:Selective Estrogen Receptor Modulators / Q000494:pharmacology; D012720:Severity of Illness Index; D013997:Time Factors; D016896:Treatment Outcome
D020845:Selective Estrogen Receptor Modulators; D020849:Raloxifene Hydrochloride