Finding unrecognized information in overactive bladder clinical trial data: a new approach to understanding placebo and treatment effects.

Aims: To identify combinations of variables among overactive bladder (OAB) clinical trial subjects that allow prediction of those who are more--or less--likely to respond strongly to placebo, or to medication.

Methods: Data from two Phase IIIb clinical trials of solifenacin in OAB were combined. Predictive models for placebo and treatment responses were constructed using baseline variables including individual items from the OAB questionnaire. These models were reduced to an essential subset of predictor variables. Two outcome measures are reported: urgency and incontinence.

Results: In placebo subjects, 14 selected variables permitted distinction between those who responded with significant reductions in urgency and those who did not. A subset of nine variables in treated subjects permitted distinction between those more--or less--likely to respond to medication. Data for urgency were combined from both placebo and actively treated subjects to identify those who had one of the previously identified clusters of variables. It was possible to predict, among all subjects, who would be likely to experience a strong placebo or active treatment response and who would not. This process was also applied to incontinence data.

Conclusions: We have developed a new process to help understand placebo and treatment responses and their relationships to baseline conditions. The effectiveness of these methods was indicated using data from two solifenacin clinical trials and would benefit from future validation using other data sets. Methods used here are suitable for predicting the placebo effect in other clinical trials.