gms | German Medical Science

Introduction: A Patient-reported outcome (PRO) is a measurement based on a report coming directly from the patient on his/her status of health condition. It can be captured by questionnaires to be filled out by the patient or interview. PROs have become increasingly important for assessing the effectiveness of treatments in clinical trials. In some disease areas such as irritable bowel syndrome, primary efficacy is measured by PROs. Responsiveness, i.e. the ability to reflect clinically important treatment effects, needs to be demonstrated for each questionnaire to be used in a clinical trial. A variety of ways to measure the responsiveness of a questionnaire have been proposed. Different measures might lead to different conclusions about whether a questionnaire’s responsiveness is demonstrated or not. The question arises how well the different responsiveness measures reflect responsiveness of a questionnaire.

Methods: We assess this by modeling the PRO data captured by the given questionnaire and derive the expected values of responsiveness measures. In this way, we can study the relationship between the responsiveness of the questionnaire per the model and the values of responsiveness measures.

Results: Based on modeling, it can be clarified which factors, other than responsiveness in itself, play a role for the value of responsiveness as generated by a given measure. For example, some responsiveness measures involve PRO data from a second questionnaire or clinical data on the status of the patient’s health condition to define conditions which should be differentiated by the questionnaire of interest to establish responsiveness. For these measures, the correlation between the PRO data of interest and the other assessments contributes to the value of responsiveness. It is unclear how to interpret this contribution in the context of responsiveness.

Discussion: For the responsiveness measures involving PRO data from a second questionnaire or clinical data on the status of the patient’s health condition it is unclear how to interpret their values for the questionnaire of interest. The reason is that other factors than responsiveness contribute to these values

This insight aids the assessment of responsiveness for a given questionnaire. The approach of modeling was found useful in this context. It is proposed to use modeling more often to assess properties of health economic measures.