Original ArticleMind the MIC: large variation among populations and methods
Introduction
Patient-reported outcomes (PROs) have become important outcome measures, because they supplement what is known about the effectiveness of interventions based on the clinician's perspective or physiological measures. If we want PRO instruments to be accepted as primary outcomes in clinical studies, we need to know the extent to which changes in scores on the instrument reflect changes in health status that the patients would consider important.
One problem is the lack of consensus about the best methodology to determine this minimal important change (MIC). Broadly speaking, there are two main approaches: anchor-based methods, which use an external criterion or “anchor” to define an important change (often a patient-based judgment) and distribution-based methods, which use statistical measures as a value for MIC. Within these two methods is a range of approaches to the actual measurement of the MIC. Recent publications recommend to use multiple MIC methods followed by triangulation (an approach to synthesize data from multiple sources) by eyeballing into one value or a small range of values for the MIC [1], [2], [3], [4], [5].
The aim of this study was to assess whether different commonly used methods lead to more or less consistent values for the MIC when applying these methods to data from five different studies.
Section snippets
Application of different MIC methods to the same data
We used two commonly used anchor-based methods and three commonly used distribution-based methods to determine the MIC of the subscales pain and physical functioning of the Western Ontario and McMaster University Osteoarthritis Index (WOMAC). The WOMAC is one of the most commonly used, and most extensively validated, outcome measures for patients with osteoarthritis [6]. It consists of three subscales measuring pain, stiffness, and physical functioning. We used the version with five-point
Results
All the MIC values for the WOMAC subscales pain and physical functioning are presented in Table 2. We found extreme wide and unsystematic variation in MIC values, ranging from −4.6 to 70.8 points (with 95% of the values lying between −3.0 and 29.7) for the subscale pain (Table 2) and from −37.4 to 59.3 (with 95% of the values lying between −2.8 and 23.7) for the subscale physical functioning (Table 3) (hip and knee combined).
We found similar variability in MIC values when using relative change
Discussion
Our results show that instead of converging into a small range of values, our MIC values are extremely variable. We are not aware of any guidelines or statistical tests for how homogeneous MIC values have to be to enable triangulation. However, regardless of the method of triangulation, we think that the variation found in this study was so large, that it is difficult to recommend any MIC value for the WOMAC for any patient subgroup.
Conclusions and recommendations for further research
We found large variation and lack of convergence in MIC values by the same method across studies and across different methods within studies. It is not possible to conclude whether this variation is due to true differences in MIC values between populations and situations or to differences in conceptual and methodological problems of the MIC methods. The answer might be a compromise, that is, that both explanations are playing a part and contributing to the variations observed in our analyses.
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