Meaningful Change for PROMIS^®

Estimates for the magnitude of change that corresponds to “important” change are published.

 [KFC1]Kozlowski AJ, Cella D, Nitsch KP, Heinemann AW. Evaluating Individual Change

Watch this 3-minute video about meaningful change in PROMIS scores.

Meaningful Change Values

When comparing group-level change in PROMIS scores, even trivial differences can be statistically significant if the sample size is large enough. For this reason, PROMIS users should seek to observe differences between groups at a magnitude deemed to be meaningful or important to patients.

The threshold to evaluate within-group change or to make a between-group comparison generally ranges between 2 and 6 T-score points (Terwee et al., 2021). Their recommendation is based on a systematic review of 31 studies that used appropriate methods for estimating minimal important change (MIC) in PROMIS adult and pediatric measures. Consensus from a meeting of PROMIS leadership pointed to a threshold of 3 T-score points when comparing groups may be reasonable for most contexts.

Bookmarking Methods for Individual Change

Standard Setting using Bookmarking methods have been used to estimate score cut points (e.g., within normal limits, mild, moderate, severe) at a single point in time. Bingham and colleagues (2021) applied this method to estimate the magnitude of change that was meaningful for making treatment decisions in rheumatoid arthritis. Patients and clinicians agreed about improvement. Patients identified a larger amount of deterioration than clinicians in order to consider a change in therapy. Learn more>>

• PROMIS Pain Interference
  • Improvement: 10 points (patients and clinicians)
  • Deterioration: 10 points (patients), 5 points (clinicians)
• PROMIS Fatigue
  • Improvement: 10 points (patients and clinicians)
  • Deterioration: 15 points (patients), 5 points (clinicians)

 Guidance for Selecting Meaningful Change Thresholds

Evidence continues to accumulate regarding reasonable estimates of meaningful change score thresholds. There are several things you should keep in mind when using these estimates.

• There is no single number that reflects a meaningful or important change for all patients in all circumstances for all purposes.
• There are different methods for calculating change thresholds (see Meaningful Change Methods) and they will yield different estimates. Also, analyses in different samples and contexts will lead to different estimates. Compile results from multiple studies.
• Selecting a value requires a judgment on your part. You should consider, for example, the use of the value. Estimates on the lower end of the reported important change range (for example, Minimally Important Difference [MID], Minimally Important Change [MIC], Minimal Clinically Important Difference [MCID]) might be appropriate for group comparisons. A higher estimate is more appropriate to categorize change in an individual (within-person change). Consider the consequences of how the estimate will be used (e.g., what is the cost-benefit ratio of a lower versus a higher threshold for a given context). Evaluate the relative risk of missing people who had meaningful change but were below the selected threshold versus identifying people as having experienced meaningful change when they did not (false positives).
• Values for improvement may vary from values for deterioration.
• If there is no empirical literature on which to base a meaningful change score estimate, you may consider a half standard deviation (e.g., 5 points on a T-score metric). Beware that a half standard deviation does not, in and of itself, indicate a meaningful or important change. Also note that this rule of thumb is not without controversy.
• Finally, you should keep in mind that most estimates of meaningful or important change are an average across the range of scores from a group of patients. It may be that people require more or less change to consider it meaningful depending on where they started. In addition, especially in the context of clinical monitoring of individuals, an average score may or may not be considered important to any given individual person.