Deriving common comorbidity indices from the meddra classification and exploring their performance on key outcomes in patients with rheumatoid arthritis

Polina Putrik, Sofia Ramiro, Elisabeth Lie, Kaleb D Michaud, Maria K. Kvamme, Andras P. Keszei, Tore K. Kvien, Till Uhlig, Annelies Boonen

Research output: Contribution to journalArticle

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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.

Original languageEnglish (US)
Pages (from-to)548-554
Number of pages7
JournalRheumatology (United Kingdom)
Volume57
Issue number3
DOIs
StatePublished - Mar 1 2018

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Comorbidity
Rheumatoid Arthritis
ametantrone
Medical Dictionaries
Rheumatic Diseases
Health Resources
Antirheumatic Agents
Joint Diseases
Hospitalization
Research Personnel
Health

Keywords

  • Comorbidity index
  • Health resource utilization
  • Meddra
  • Physical function
  • Quality of life
  • Rheumatoid arthritis
  • Utility

ASJC Scopus subject areas

  • Rheumatology
  • Pharmacology (medical)

Cite this

Deriving common comorbidity indices from the meddra classification and exploring their performance on key outcomes in patients with rheumatoid arthritis. / Putrik, Polina; Ramiro, Sofia; Lie, Elisabeth; Michaud, Kaleb D; Kvamme, Maria K.; Keszei, Andras P.; Kvien, Tore K.; Uhlig, Till; Boonen, Annelies.

In: Rheumatology (United Kingdom), Vol. 57, No. 3, 01.03.2018, p. 548-554.

Research output: Contribution to journalArticle

Putrik, Polina ; Ramiro, Sofia ; Lie, Elisabeth ; Michaud, Kaleb D ; Kvamme, Maria K. ; Keszei, Andras P. ; Kvien, Tore K. ; Uhlig, Till ; Boonen, Annelies. / Deriving common comorbidity indices from the meddra classification and exploring their performance on key outcomes in patients with rheumatoid arthritis. In: Rheumatology (United Kingdom). 2018 ; Vol. 57, No. 3. pp. 548-554.
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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.",
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AU - Putrik, Polina

AU - Ramiro, Sofia

AU - Lie, Elisabeth

AU - Michaud, Kaleb D

AU - Kvamme, Maria K.

AU - Keszei, Andras P.

AU - Kvien, Tore K.

AU - Uhlig, Till

AU - Boonen, Annelies

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N2 - 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.

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