Gregor Liegl1, Matthias Rose2, Fabian Knebel3, Andreas Stengel4, Frank Buttgereit5, Alexander Obbarius2, H Felix Fischer2, Sandra Nolte6. 1. Department of Psychosomatic Medicine, Center for Internal Medicine and Dermatology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany. Electronic address: gregor.liegl@charite.de. 2. Department of Psychosomatic Medicine, Center for Internal Medicine and Dermatology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany. 3. Clinic for Cardiology and Angiology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany. 4. Department of Psychosomatic Medicine, Center for Internal Medicine and Dermatology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany; Clinic for Rheumatology and Clinical Immunology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany; Department of Psychosomatic Medicine and Psychotherapy, Medical University Hospital Tübingen, Tübingen, Germany. 5. Clinic for Rheumatology and Clinical Immunology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany. 6. Department of Psychosomatic Medicine, Center for Internal Medicine and Dermatology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany; Population Health Strategic Research Centre, School of Health and Social Development, Deakin University, Burwood, Australia.
Abstract
OBJECTIVES: The Patient-Reported Outcomes Measurement Information System (PROMIS) physical function (PF) item bank has been developed to standardize patient-reported PF across medical fields. However, evidence of scoring equivalence across cardiology and rheumatology patients is still missing. Therefore, this study aims to investigate both (1) the extent of disease-related differential item functioning (DIF) and (2) the impact of the disease group on using subdomain-specific item sets for generating PROMIS PF scores in cardiology and rheumatology patients. STUDY DESIGN AND SETTING: Ordinal regression was used to evaluate DIF between cardiology (n = 201) and rheumatology (n = 200) inpatients. To explore the disease-specific impact of PF subdomains on scoring, we compared scores derived from the full item bank with scores derived from subdomain-specific item sets for each disease group. RESULTS: DIF was detected in 18 items, predominately from the upper extremity subdomain. When upper extremity items were used, cardiology patients reached systematically higher scores than using the full item bank. Rheumatology patients scored substantially higher when mobility items were used. CONCLUSION: Applying the PROMIS PF metric to disease-specific item sets including items from differing subdomains may lead to biased comparisons of PF levels across disease groups. Disease-specific item parameters should be provided for items showing DIF, and subdomain-related content balancing is recommended for scoring the generic PROMIS PF construct.
OBJECTIVES: The Patient-Reported Outcomes Measurement Information System (PROMIS) physical function (PF) item bank has been developed to standardize patient-reported PF across medical fields. However, evidence of scoring equivalence across cardiology and rheumatology patients is still missing. Therefore, this study aims to investigate both (1) the extent of disease-related differential item functioning (DIF) and (2) the impact of the disease group on using subdomain-specific item sets for generating PROMIS PF scores in cardiology and rheumatology patients. STUDY DESIGN AND SETTING: Ordinal regression was used to evaluate DIF between cardiology (n = 201) and rheumatology (n = 200) inpatients. To explore the disease-specific impact of PF subdomains on scoring, we compared scores derived from the full item bank with scores derived from subdomain-specific item sets for each disease group. RESULTS: DIF was detected in 18 items, predominately from the upper extremity subdomain. When upper extremity items were used, cardiology patients reached systematically higher scores than using the full item bank. Rheumatology patients scored substantially higher when mobility items were used. CONCLUSION: Applying the PROMIS PF metric to disease-specific item sets including items from differing subdomains may lead to biased comparisons of PF levels across disease groups. Disease-specific item parameters should be provided for items showing DIF, and subdomain-related content balancing is recommended for scoring the generic PROMIS PF construct.