Responsiveness, minimal important difference, minimal relevant difference, and optimal number of patients for a study

Area of Science:

• Orthopedics
• Clinical Research Methodology
• Health Outcomes Research

Background:

• Patient-reported outcome measures (PROMs) are vital for assessing treatment efficacy.
• Interpreting changes in PROM scores, such as minimal important difference (MID), is complex and varies.
• These scores influence treatment recommendations and sample size calculations in studies.

Purpose of the Study:

• To provide a theoretical explanation of key terms: responsiveness, minimal important difference (MID), minimal important change (MIC), minimal relevant difference (MIREDIF), and threshold of clinical importance.
• To offer guidance on calculating these measures and determining optimal study sample sizes.
• To illustrate calculations using real-world data from anterior cruciate ligament reconstruction patients.

Main Methods:

• Theoretical explanation of PROM interpretation concepts.
• Illustrative calculations using Knee Injury and Osteoarthritis Outcome Score (KOOS) data from 164 patients.
• Presentation of common methods for calculating and interpreting MID.

Main Results:

• Results for MID calculations vary significantly based on PROM domains, patient scale position, and health conditions.
• Optimal sample size determination is influenced by MIREDIF, standard error of the measure (SEM), statistical power, and PROM responsiveness.
• Uncertainty exists in calculating and interpreting responsiveness, MID, and MIREDIF due to their complexity.

Conclusions:

• Authors must specify MID calculation methods and relevance to the study population when reporting research.
• Clearer understanding and application of MID, MIREDIF, and responsiveness are needed for robust healthcare decisions.
• These measures require careful consideration to justify clinical and research decisions.