What is PAGE?

We represent a community with a shared interest in data analysis using the population approach.


2003
   Verona, Italy

A pharmacodynamic model for Scandinavian Stroke Scale data

Fredrik Jonsson and Niclas Jonsson

Uppsala University, Sweden

Objectives: Stroke severity is commonly measured on aggregate clinical assessment scales. While such scales are convenient tools in the clinical setting, it is often difficult to make use of all the information present in clinical assessment data when such data are analyzed using pharmacokinetic-pharmacodynamic (PK-PD) modeling. Therefore, it is of interest that better models for the analysis of such data are developed.

Methods: This study relates modeling of recent data from a phase II study of a treatment against stroke. In the study, drug efficacy was monitored using the Scandinavian Stroke Scale (SSS). SSS is an ordered categorical scale, where several endpoints for neurological performance (speech, gait, motor performance, etc) are rated on several multi-item subscales. These ratings are subsequently added and summarized as a total SSS score.

Results: We propose the use of a two-part modeling approach as a new tool for the modeling of data such as these. This approach is similar to that in a recently published study on alcohol use among teens [1]. Probabilistic models are used to describe the transitional properties of the data, thus explaining the probability of occurences of transition events such as dropout or a score decline, while linear models are used to relate the magnitude of the score change, given the observed transition. In this manner, the transition properties of the scale are taken into account, and the occurrence of random adverse events is modeled more realistically than if other available methods are used.

Conclusion: We believe that our new approach may be useful not only for the analysis of SSS score data in the development of new treatments against stroke, but also in other therapeutic areas where aggregate clinical assessment scales are used in a similar manner.

Reference:
[1] M. K. Olsen and J. L. Schafer. A two-part random-effects model for semicontinuous longitudinal data. J. Am. Stat. Ass 96: 730-745 (2001)



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