Jin-Shei Lai1, David Cella2, Betina Yanez2, Arthur Stone3. 1. Department of Medical Social Sciences, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA; Department of Pediatrics, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA. Electronic address: js-lai@northwestern.edu. 2. Department of Medical Social Sciences, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA. 3. Department of Psychiatry and Behavioral Science, Stony Brook University, Stony Brook, New York, USA.
Abstract
CONTEXT: Fatigue is one of the most common and debilitating symptoms experienced by patients living with chronic conditions and is also commonly experienced in the general U.S. population. Linking fatigue scores from some of the most widely used measure of fatigue to the same metric will facilitate interpretation of fatigue outcomes. OBJECTIVES: The goal of this study is to report the methods used to develop linking (crosswalk) tables to enable the direct comparison of Patient-Reported Outcomes Measurement Information System-Fatigue with fatigue scores on the Functional Assessment of Chronic Illness Therapy-Fatigue Scale, the Medical Outcomes Study Short Form-36 four-item Vitality Scale, and the Quality of Life in Neurological Disorders Fatigue Scale. METHODS: Participants were recruited from two data sets (n=1120 and n=803). Two item response theory-based linking methods, the Stocking-Lord calibration and fixed-parameter calibration, were used to establish linking between measures. The item response theory calibrations were derived using the graded response model. RESULTS: Both the Stocking-Lord calibration and fixed-parameter calibration linking methods produced comparable results. Final crosswalk tables are reported for the fixed-parameter calibration. CONCLUSION: Findings can facilitate comparison of scores across some of the most widely used fatigue measures and assist in comparing patient-reported fatigue outcomes in clinical trials, comparative effectiveness research, and clinical practice.
CONTEXT: Fatigue is one of the most common and debilitating symptoms experienced by patients living with chronic conditions and is also commonly experienced in the general U.S. population. Linking fatigue scores from some of the most widely used measure of fatigue to the same metric will facilitate interpretation of fatigue outcomes. OBJECTIVES: The goal of this study is to report the methods used to develop linking (crosswalk) tables to enable the direct comparison of Patient-Reported Outcomes Measurement Information System-Fatigue with fatigue scores on the Functional Assessment of Chronic Illness Therapy-Fatigue Scale, the Medical Outcomes Study Short Form-36 four-item Vitality Scale, and the Quality of Life in Neurological Disorders Fatigue Scale. METHODS:Participants were recruited from two data sets (n=1120 and n=803). Two item response theory-based linking methods, the Stocking-Lord calibration and fixed-parameter calibration, were used to establish linking between measures. The item response theory calibrations were derived using the graded response model. RESULTS: Both the Stocking-Lord calibration and fixed-parameter calibration linking methods produced comparable results. Final crosswalk tables are reported for the fixed-parameter calibration. CONCLUSION: Findings can facilitate comparison of scores across some of the most widely used fatigue measures and assist in comparing patient-reported fatigue outcomes in clinical trials, comparative effectiveness research, and clinical practice.
Authors: Bryce B Reeve; Ron D Hays; Jakob B Bjorner; Karon F Cook; Paul K Crane; Jeanne A Teresi; David Thissen; Dennis A Revicki; David J Weiss; Ronald K Hambleton; Honghu Liu; Richard Gershon; Steven P Reise; Jin-shei Lai; David Cella Journal: Med Care Date: 2007-05 Impact factor: 2.983
Authors: Jin-Shei Lai; David Cella; Kelly Dineen; Rita Bode; Jamie Von Roenn; Richard C Gershon; Daniel Shevrin Journal: J Clin Epidemiol Date: 2005-02 Impact factor: 6.437
Authors: N K Aaronson; S Ahmedzai; B Bergman; M Bullinger; A Cull; N J Duez; A Filiberti; H Flechtner; S B Fleishman; J C de Haes Journal: J Natl Cancer Inst Date: 1993-03-03 Impact factor: 13.506
Authors: D M Hann; P B Jacobsen; L M Azzarello; S C Martin; S L Curran; K K Fields; H Greenberg; G Lyman Journal: Qual Life Res Date: 1998-05 Impact factor: 4.147
Authors: Benjamin D Schalet; Nan E Rothrock; Ron D Hays; Lewis E Kazis; Karon F Cook; Joshua P Rutsohn; David Cella Journal: J Gen Intern Med Date: 2015-07-16 Impact factor: 5.128
Authors: Benjamin D Schalet; Dennis A Revicki; Karon F Cook; Eswar Krishnan; Jim F Fries; David Cella Journal: J Gen Intern Med Date: 2015-10 Impact factor: 5.128
Authors: Jennifer C Plumb Vilardaga; Joseph G Winger; Irene Teo; Lynda Owen; Linda M Sutton; Francis J Keefe; Tamara J Somers Journal: J Pain Symptom Manage Date: 2019-09-17 Impact factor: 3.612
Authors: Fengmin Zhao; David Cella; Judith Manola; Robert S DiPaola; Lynne I Wagner; Naomi S B Haas Journal: Support Care Cancer Date: 2017-12-23 Impact factor: 3.603
Authors: Jin-Shei Lai; Jennifer L Beaumont; Sally E Jensen; Karen Kaiser; David L Van Brunt; Amy H Kao; Shih-Yin Chen Journal: Clin Rheumatol Date: 2016-11-15 Impact factor: 2.980
Authors: Zeeshan Butt; Andrea F DiMartini; Qian Liu; Mary Ann Simpson; Abigail R Smith; Jarcy Zee; Brenda W Gillespie; Susan Holtzman; Daniela Ladner; Kim Olthoff; Robert A Fisher; Silvia Hafliger; Chris E Freise; Mercedes Susan Mandell; Averell H Sherker; Mary Amanda Dew Journal: Liver Transpl Date: 2018-09 Impact factor: 5.799