We observed a lack of consistency in the application of methods for computing MID or MCID for generic and disease-specific HRQoL measures .
The anchor-based method yields conservative estimates of MID or MCID , compared to the distribution-based method .
OBJECTIVES The objective of the study was to assess the usability of minimal important difference ( MID ) and minimal clinical ly important difference ( MCID ) for measuring meaningful changes in disease-specific and generic health-related quality -of-life ( HRQoL ) outcomes in patient-centered care .
A combination of distribution- and anchor-based approaches determined minimally important differences (MIDs) for four endpoints in a breast cancer scale.
OBJECTIVE To determine distribution- and anchor-based minimal important difference ( MID ) estimates for four scores from the Functional Assessment of Cancer Therapy-Breast ( FACT-B ) : the breast cancer subscale ( BCS ) , Trial Outcome Index ( TOI ) , FACT-G ( the general version ) , and FACT-B. STUDY DESIGN AND SETTING We used data from a Phase III clinical trial in metastatic breast cancer ( ECOG study 1193 ; n=739 ) and a prospect i ve observational study of pain in metastatic breast cancer ( n=129 ) . One third and one half of the st and ard deviation and 1 st and ard error of measurement were used as distribution-based criteria . Clinical indicators used to determine anchor-based differences included ECOG performance status , current pain , and response to treatment . RESULTS FACT-B scores were responsive to performance status and pain anchors , but not to treatment response . By combining the results of distribution- and anchor-based methods , MID estimates were obtained : BCS=2 - 3 points , TOI=5 - 6 points , FACT-G=5 - 6 points , and FACT-B=7 - 8 points . CONCLUSION Distribution- and anchor-based estimates of the MID do show convergence . These estimates can be used in combination with other measures of efficacy to determine meaningful benefit and provide a basis for sample size estimation in clinical trials
We observed a lack of consistency in the application of methods for computing MID or MCID for generic and disease-specific HRQoL measures .
The anchor-based method yields conservative estimates of MID or MCID , compared to the distribution-based method .
OBJECTIVES The objective of the study was to assess the usability of minimal important difference ( MID ) and minimal clinical ly important difference ( MCID ) for measuring meaningful changes in disease-specific and generic health-related quality -of-life ( HRQoL ) outcomes in patient-centered care .