QOL Disease Impact Scale (QDIS) standardized scores agree nearly perfectly with study-specific scores in independent test of acute coronary syndrome patients

WORCESTER, MA, January 29, 2015 -- JWRG’s pursuit of disease-specific QOL measurement innovation appears to be on the right track toward filling the gap between disease-specific measures that do not measure QOL and QOL measures that are not disease-specific.  

Studies conducted during the development of the Quality of Life Disease Impact Scale (QDIS^®) showed that it differs from widely-used disease-specific measures in a number of important ways.  First, QDIS increases disease-specific QOL content representation enough to be on a par with widely-used generic QOL measures. At the same time, QDIS provides a single overall QOL impact score, despite its breadth of content.  While QDIS item content overlaps substantially with the item content of generic measures, because QDIS items are disease-specific, QDIS consistently achieves greater convergent and discriminant validity in comparison with generic measures. QDIS also is the first disease-specific measure to be scored using norm-based scoring, based on a representative sample of the entire U.S. chronically ill general population, as opposed to a single disease.  This advance in standardized scoring is based on evaluation of crucial assumptions about IRT item parameters used in scoring disease-specific QOL impact across diseases that were made during the development of QDIS.  Due to its standardization of content and scoring across diseases, QDIS also is the first disease-specific measure that allows comparisons of disease-specific outcomes across diseases.

Nina Deng and her UMass Medical School (UMMS) and JWRG collaborators tested assumptions underlying standardized scoring of QDIS, including differential item functioning (DIF) and other psychometric properties of items, using a 7-item short-form version of QDIS (QDIS-7).  They studied an independent sample of patients (N=1,544) interviewed after hospitalization for acute coronary syndrome (ACS) in the UMMS Transitions, Risks, and Action in Coronary Events – Center for Outcomes Research and Education (TRACE-CORE) study. TRACE-CORE data was compared to the Internet-based QDIS standardization sample (N=5,418) from JWRG’s Computerized Adaptive Assessment of Disease Impact (DICAT) Project.  “ACS-specific” IRT item parameters were compared to DICAT “standardized” IRT item parameters using a variety of methods as published Quality of Life Research [http://www.ncbi.nlm.nih.gov/pubmed/25601166].  These tests were very stringent because item parameters and scale scores for patients interviewed after an acute coronary event were compared with results from Internet-based self-administered surveys for chronically ill household samples.

In the UMMS TRACE-CORE study, no items with meaningful DIF were detected and IRT-based theta scores for ACS patients using standardized and ACS-specific item parameters were nearly perfectly correlated (r = 0.995).  Interesting differences observed in item slopes between studies suggest that items self-administered on the Internet may discriminate better than those that are interviewer administered.  Population norms indicated that ACS patients scored about one-half standard deviation higher (worse QOL impact) compared to chronically ill adults in the US population standardization sample.  Deng and her co-authors concluded that the UMMS TRACE-CORE study “showed sufficient IRT invariance to warrant use of standardized IRT scoring of QDIS-7 for studies comparing the QOL impact attributed to acute coronary disease and other chronic conditions.”

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