Determination of the minimal clinically important difference for seven fatigue measures in rheumatoid arthritis

J Clin Epidemiol. 2008 Jul;61(7):705-13. doi: 10.1016/j.jclinepi.2007.08.016. Epub 2008 Mar 21.


Objective: To estimate the minimal clinically important difference (MCID) of seven measures of fatigue in rheumatoid arthritis.

Study design and setting: A cross-sectional study design based on interindividual comparisons was used. Six to eight subjects participated in a single meeting and completed seven fatigue questionnaires (nine sessions were organized and 61 subjects participated). After completion of the questionnaires, the subjects had five one-on-one 10-minute conversations with different people in the group to discuss their fatigue. After each conversation, each patient compared their fatigue to their conversational partners on a global rating. Ratings were compared to the scores of the fatigue measures to estimate the MCID. Both nonparametric and linear regression analyses were used.

Results: Nonparametric estimates for the MCID relative to "little more fatigue" tended to be smaller than those for "little less fatigue." The global MCIDs estimated by linear regression were: Fatigue Severity Scale, 20.2; Vitality scale of the MOS-SF36, 14.8; Multidimensional Assessment of Fatigue, 18.7; Multidimensional Fatigue Inventory, 16.6; Functional Assessment of Chronic Illness Therapy-Fatigue, 15.9; Chalder Fatigue Scale, 9.9; 10-point numerical Rating Scale, 19.7, for normalized scores (0-100). The standardized MCIDs for the seven measures were roughly similar (0.67-0.76).

Conclusion: These estimates of MCID will help to interpret changes observed in a fatigue score and will be critical in estimating sample size requirements.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Arthritis, Rheumatoid / complications*
  • Arthritis, Rheumatoid / psychology
  • Disability Evaluation*
  • Fatigue / etiology*
  • Fatigue / psychology
  • Female
  • Humans
  • Linear Models
  • Male
  • Middle Aged
  • Psychometrics
  • Sickness Impact Profile