Three ways to quantify uncertainty in individually applied “minimally important change” values

• Published in: Journal of clinical epidemiology Vol. 63; no. 1; pp. 37 - 45
• Main Authors: de Vet, Henrica C.W, Terluin, Berend, Knol, Dirk L, Roorda, Leo D, Mokkink, Lidwine B, Ostelo, Raymond W.J.G, Hendriks, Erik J.M, Bouter, Lex M, Terwee, Caroline B
• Format: Journal Article
• Language: English
• Published: New York, NY Elsevier Inc 2010; Elsevier; Elsevier Limited
• Subjects: Anchor-based methods; Attitude to Health; Back pain; Biological and medical sciences; Change scores; Clinical outcomes; Computerized, statistical medical data processing and models in biomedicine; Data Interpretation, Statistical; Epidemiology; Humans; Internal Medicine; Low Back Pain - therapy; Medical sciences; Medical statistics; Minimally important change; Mortality; Outcome assessment; Patient Satisfaction; Patient-reported outcomes; Patients; Psychometrics; Quality of Life; Questionnaires; ROC Curve; ROC method; Treatment Outcome; Uncertainty; Anchor-based methods; ROC method; Patient-reported outcomes; Minimally important change; Outcome assessment; Change scores; Human; Uncertainty; Prognosis; Disease; Methodology; Self evaluation; Patient; Change; Receiver operating characteristic curves; Minimal important difference
• ISSN: 0895-4356; 1878-5921
• DOI: 10.1016/j.jclinepi.2009.03.011

Abstract Objective Determining “minimally important change” (MIC) facilitates the interpretation of change scores on multi-item instruments. This article focuses on how MIC values should be interpreted when applied to individual patients. Study Design and Setting The MIC value of a hypothetical questionnaire “Q” was determined in a sample of 400 patients who improved and 100 patients who did not improve, using the receiver operating characteristic (ROC) method, and three methods to quantify the uncertainty. Results The MIC value on questionnaire Q was 10.5. Firstly, the 95% confidence interval (CI) of the MIC value (for questionnaire Q: 5.6–14.2) quantifies the uncertainty of the estimation of the MIC value. Secondly, “how sure we are that this MIC value holds for every patient” is quantified by the values for sensitivity (74%) and specificity (91%). Thirdly, the smallest detectable change (SDC) on questionnaire Q is calculated (16.0) to consider whether the MIC value (10.5) falls outside or within the measurement error. Conclusion For application in clinical research and practice, MIC values are always considered at the individual level, but determined in groups of patients. The interpretation comes with different forms of uncertainty. To appreciate the uncertainty, knowledge of the underlying distributions of change scores is indispensable.