Polina Putrik1,2, Sofia Ramiro3, Elisabeth Lie4, Kaleb Michaud5,6, Maria K Kvamme4,7, Andras P Keszei8, Tore K Kvien4, Till Uhlig4, Annelies Boonen1. 1. Rheumatology, Maastricht University Medical Center and CAPHRI Research Institute, Maastricht, the Netherlands. 2. Health Promotion and Education, Maastricht University, Maastricht, the Netherlands. 3. Rheumatology, Leiden University Medical Center, Leiden, the Netherlands. 4. Rheumatology, Diakonhjemmet Hospital, Oslo, Norway. 5. Division of Rheumatology, University of Nebraska Medical Center, Omaha, Nebraska. 6. National Data Bank for Rheumatic Diseases, Wichita, KS, USA. 7. Market Access, MSD, Drammen, Norway. 8. Medical Informatics, Uniklinik RWTH Aachen University, Aachen, Germany.
Abstract
OBJECTIVE: To develop algorithms for calculating the Rheumatic Diseases Comorbidity Index (RDCI), Charlson-Deyo Index (CDI) and Functional Comorbidity Index (FCI) from the Medical Dictionary for Regulatory Activities (MedDRA), and to assess how these MedDRA-derived indices predict clinical outcomes, utility and health resource utilization (HRU). METHODS: Two independent researchers linked the preferred terms of the MedDRA classification into the conditions included in the RDCI, the CDI and the FCI. Next, using data from the Norwegian Register-DMARD study (a register of patients with inflammatory joint diseases treated with DMARDs), the explanatory value of these indices was studied in models adjusted for age, gender and DAS28. Model fit statistics were compared in generalized estimating equation (prediction of outcome over time) models using as outcomes: modified HAQ, HAQ, physical and mental component summary of SF-36, SF6D and non-RA related HRU. RESULTS: Among 4126 patients with RA [72% female, mean (s.d.) age 56 (14) years], median (interquartile range) of RDCI at baseline was 0.0 (1.0) [range 0-6], CDI 0.0 (0.0) [0-7] and FCI 0.0 (1.0) [0-6]. All the comorbidity indices were associated with each outcome, and differences in their performance were moderate. The RDCI and FCI performed better on clinical outcomes: modified HAQ and HAQ, hospitalization, physical and mental component summary, and SF6D. Any non-RA related HRU was best predicted by RDCI followed by CDI. CONCLUSION: An algorithm is now available to compute three commonly used comorbidity indices from MedDRA classification. Indices performed comparably well in predicting a variety of outcomes, with the CDI performing slightly worse when predicting outcomes reflecting functioning and health.
OBJECTIVE: To develop algorithms for calculating the Rheumatic Diseases Comorbidity Index (RDCI), Charlson-Deyo Index (CDI) and Functional Comorbidity Index (FCI) from the Medical Dictionary for Regulatory Activities (MedDRA), and to assess how these MedDRA-derived indices predict clinical outcomes, utility and health resource utilization (HRU). METHODS: Two independent researchers linked the preferred terms of the MedDRA classification into the conditions included in the RDCI, the CDI and the FCI. Next, using data from the Norwegian Register-DMARD study (a register of patients with inflammatory joint diseases treated with DMARDs), the explanatory value of these indices was studied in models adjusted for age, gender and DAS28. Model fit statistics were compared in generalized estimating equation (prediction of outcome over time) models using as outcomes: modified HAQ, HAQ, physical and mental component summary of SF-36, SF6D and non-RA related HRU. RESULTS: Among 4126 patients with RA [72% female, mean (s.d.) age 56 (14) years], median (interquartile range) of RDCI at baseline was 0.0 (1.0) [range 0-6], CDI 0.0 (0.0) [0-7] and FCI 0.0 (1.0) [0-6]. All the comorbidity indices were associated with each outcome, and differences in their performance were moderate. The RDCI and FCI performed better on clinical outcomes: modified HAQ and HAQ, hospitalization, physical and mental component summary, and SF6D. Any non-RA related HRU was best predicted by RDCI followed by CDI. CONCLUSION: An algorithm is now available to compute three commonly used comorbidity indices from MedDRA classification. Indices performed comparably well in predicting a variety of outcomes, with the CDI performing slightly worse when predicting outcomes reflecting functioning and health.
Authors: Veerle Stouten; Sofia Pazmino; P Verschueren; Pavlos Mamouris; René Westhovens; Kurt de Vlam; Delphine Bertrand; Kristien Van der Elst; Bert Vaes; Diederik De Cock Journal: RMD Open Date: 2021-06