Summary
Early stopping of clinical trials either in case of beneficial or deleterious effect of treatment on quality of life (QoL) is an important issue. QoL is usually evaluated using self-assessment questionnaires and responses to the items are combined into scores assumed to be normally distributed (which is rarely the case). An alternative is to use item response theory (IRT) models such as the Rasch model for binary items which takes into account the categorical nature of the items.
Sequential analysis and mixed Rasch models (MRM) were combined in the context of phaseII non-comparative trials. The statistical properties of the Sequential Probability Ratio Test (SPRT) and of the Triangular Test (TT) were compared using MRM and traditional average scores methods (ASM) by means of simulations.
The type I error of the SPRT and TT was correctly maintained for both methods. While remaining a bit underpowered, MRM displayed higher power than the ASM for both sequential tests. Both methods allowed substantial reductions in average sample numbers as compared with fixed sample designs (about 60%).
The use of IRT models in sequential analysis of QoL endpoints is promising and should provide a more powerful method to detect therapeutic effects than the traditional ASM.
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Sebille, V., Mesbah, M. (2006). Sequential Analysis of Quality of Life Rasch Measurements. In: Nikulin, M., Commenges, D., Huber, C. (eds) Probability, Statistics and Modelling in Public Health. Springer, Boston, MA. https://doi.org/10.1007/0-387-26023-4_28
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