Practical issues encountered while determining Minimal Clinically Important Difference in Patient-Reported Outcomes

Pascal Woaye-Hune (1) , Jean-Benoit Hardouin (1, 2) , Paul-Antoine Lehur (3) , Guillaume Meurette (3) , Antoine Vanier (1)

1 SPHERE - MethodS in Patients-centered outcomes and HEalth ResEarch
2 Plateforme de Méthodologie et Biostatistique, Direction de la Recherche [CHU Nantes]
3 CHU Nantes - Centre Hospitalier Universitaire de Nantes

Background: Using a real dataset, we highlighted several major methodological issues raised by the estimation of the Minimal Clinically Important Difference (MCID) of a Patient-Reported Outcomes instrument. We especially considered the management of missing data and the use of more than two times of measurement. While inappropriate missing data management and inappropriate use of multiple time points can lead to loss of precision and/or bias in MCID estimation, these issues are almost never dealt with and require cautious considerations in the context of MCID estimation. Methods: We used the LIGALONGO study (French Randomized Controlled Trial). We estimated MCID on the SF-36 General Health score by comparing many methods (distribution or anchor-based). Different techniques for imputation of missing data were performed (simple and multiple imputations). We also consider all measurement occasions by longitudinal modeling, and the dependence of the score difference on baseline. Results: Three hundred ninety-three patients were studied. With distribution-based methods, a great variability in MCID was observed (from 3 to 26 points for improvement). Only 0.2 SD and 1/3 SD distribution methods gave MCID values consistent with anchor-based methods (from 4 to 7 points for improvement). The choice of missing data imputation technique clearly had an impact on MCID estimates. Simple imputation by mean score seemed to lead to out-of-range estimate, but as missing not at random mechanism can be hypothesized, even multiple imputations techniques can have led to an slight underestimation of MCID. Using 3 measurement occasions for improvement led to an increase in precision but lowered estimates. Conclusion: This practical example illustrates the substantial impact of some methodological issues that are usually never dealt with for MCID estimation. Simulation studies are needed to investigate those issues. Trial registration NCT01240772 (ClinicalTrials.gov) registered on November 15, 2010.

Mots clés: Minimal clinically important difference; Minimal important difference; Patient-reported outcomes; Methodology; Missing data; Longitudinal modeling; Minimal clinically important difference Minimal important difference Patient-reported outcomes Methodology Missing data Longitudinal modeling; Minimal clinically important difference

Domaines: Médecine humaine et pathologie

Pascal Woaye-Hune, Jean-Benoit Hardouin, Paul-Antoine Lehur, Guillaume Meurette, Antoine Vanier. Practical issues encountered while determining Minimal Clinically Important Difference in Patient-Reported Outcomes. Health and Quality of Life Outcomes, 2020, 18 (1), pp.156. ⟨10.1186/s12955-020-01398-w⟩. ⟨hal-04041547⟩