Daphna Harel1, Marie Hudson2, Alexandra Iliescu1, Murray Baron1, Russell Steele1. 1. From the Center for the Promotion of Research Involving Innovative Statistical Methodology (PRIISM) Applied Statistics Center, New York University; Department of Humanities and Social Sciences in the Professions, New York University, New York, New York, USA; Division of Rheumatology, Jewish General Hospital; Lady Davis Institute, Jewish General Hospital; Department of Medicine, McGill University; Mathematics and Statistics, McGill University, Montreal, Quebec, Canada.D. Harel, PhD, PRIISM Applied Statistics Center, New York University, and the Department of Humanities and Social Sciences in the Professions, New York University; M. Hudson, MD, MPH, Division of Rheumatology, Jewish General Hospital, and the Lady Davis Institute, Jewish General Hospital, and the Department of Medicine, McGill University; A. Iliescu, BS, Lady Davis Institute, Jewish General Hospital, Montreal; M. Baron, MD, Division of Rheumatology, Jewish General Hospital, and the Lady Davis Institute, Jewish General Hospital, and the Department of Medicine, McGill University; R. Steele, PhD, Lady Davis Institute, Jewish General Hospital, Montreal, and Mathematics and Statistics, McGill University. 2. From the Center for the Promotion of Research Involving Innovative Statistical Methodology (PRIISM) Applied Statistics Center, New York University; Department of Humanities and Social Sciences in the Professions, New York University, New York, New York, USA; Division of Rheumatology, Jewish General Hospital; Lady Davis Institute, Jewish General Hospital; Department of Medicine, McGill University; Mathematics and Statistics, McGill University, Montreal, Quebec, Canada.D. Harel, PhD, PRIISM Applied Statistics Center, New York University, and the Department of Humanities and Social Sciences in the Professions, New York University; M. Hudson, MD, MPH, Division of Rheumatology, Jewish General Hospital, and the Lady Davis Institute, Jewish General Hospital, and the Department of Medicine, McGill University; A. Iliescu, BS, Lady Davis Institute, Jewish General Hospital, Montreal; M. Baron, MD, Division of Rheumatology, Jewish General Hospital, and the Lady Davis Institute, Jewish General Hospital, and the Department of Medicine, McGill University; R. Steele, PhD, Lady Davis Institute, Jewish General Hospital, Montreal, and Mathematics and Statistics, McGill University. marie.hudson@mcgill.ca.
Abstract
OBJECTIVE: To develop a weighted summary score for the Medsger Disease Severity Scale (DSS) and to compare its measurement properties with those of a summed DSS score and a physician's global assessment (PGA) of severity score in systemic sclerosis (SSc). METHODS: Data from 875 patients with SSc enrolled in a multisite observational research cohort were extracted from a central database. Item response theory was used to estimate weights for the DSS weighted score. Intraclass correlation coefficients (ICC) and convergent, discriminative, and predictive validity of the 3 summary measures in relation to patient-reported outcomes (PRO) and mortality were compared. RESULTS: Mean PGA was 2.69 (SD 2.16, range 0-10), mean DSS summed score was 8.60 (SD 4.02, range 0-36), and mean DSS weighted score was 8.11 (SD 4.05, range 0-36). ICC were similar for all 3 measures [PGA 6.9%, 95% credible intervals (CrI) 2.1-16.2; DSS summed score 2.5%, 95% CrI 0.4-6.7; DSS weighted score 2.0%, 95% CrI 0.1-5.6]. Convergent and discriminative validity of the 3 measures for PRO were largely similar. In Cox proportional hazards models adjusting for age and sex, the 3 measures had similar predictive ability for mortality (adjusted R(2) 13.9% for PGA, 12.3% for DSS summed score, and 10.7% DSS weighted score). CONCLUSION: The 3 summary scores appear valid and perform similarly. However, there were some concerns with the weights computed for individual DSS scales, with unexpected low weights attributed to lung, heart, and kidney, leading the PGA to be the preferred measure at this time. Further work refining the DSS could improve the measurement properties of the DSS summary scores.
OBJECTIVE: To develop a weighted summary score for the Medsger Disease Severity Scale (DSS) and to compare its measurement properties with those of a summed DSS score and a physician's global assessment (PGA) of severity score in systemic sclerosis (SSc). METHODS: Data from 875 patients with SSc enrolled in a multisite observational research cohort were extracted from a central database. Item response theory was used to estimate weights for the DSS weighted score. Intraclass correlation coefficients (ICC) and convergent, discriminative, and predictive validity of the 3 summary measures in relation to patient-reported outcomes (PRO) and mortality were compared. RESULTS: Mean PGA was 2.69 (SD 2.16, range 0-10), mean DSS summed score was 8.60 (SD 4.02, range 0-36), and mean DSS weighted score was 8.11 (SD 4.05, range 0-36). ICC were similar for all 3 measures [PGA 6.9%, 95% credible intervals (CrI) 2.1-16.2; DSS summed score 2.5%, 95% CrI 0.4-6.7; DSS weighted score 2.0%, 95% CrI 0.1-5.6]. Convergent and discriminative validity of the 3 measures for PRO were largely similar. In Cox proportional hazards models adjusting for age and sex, the 3 measures had similar predictive ability for mortality (adjusted R(2) 13.9% for PGA, 12.3% for DSS summed score, and 10.7% DSS weighted score). CONCLUSION: The 3 summary scores appear valid and perform similarly. However, there were some concerns with the weights computed for individual DSS scales, with unexpected low weights attributed to lung, heart, and kidney, leading the PGA to be the preferred measure at this time. Further work refining the DSS could improve the measurement properties of the DSS summary scores.