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Sökning: WFRF:(Frech M) > (2015-2019)

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  • Morrisroe, Kathleen, et al. (författare)
  • Determinants of health-related quality of life in a multinational systemic sclerosis inception cohort
  • 2018
  • Ingår i: Clinical and Experimental Rheumatology. - 0392-856X. ; 36:4, s. 53-60
  • Tidskriftsartikel (refereegranskat)abstract
    • OBJECTIVES: To evaluate health-related quality of life (HRQoL) and its determinants in a systemic sclerosis (SSc) multinational inception cohort. We performed a meta-analysis of data from individual countries, and compared the meta-analysis to individual country results by pooling data from each of the countries.METHODS: SSc patients within 2 years of disease onset were recruited from 5 countries participating in the International Systemic Sclerosis Inception Cohort (INSYNC). Data from each country's database were exported for analysis using a harmonised platform. HRQoL was assessed using the Medical Outcomes Short Form-36 (SF-36). Multivariate linear regression assessed associations between HRQoL and predictors in cohorts separately and meta-analyzed to generate pooled estimates. The analyses were repeated using individual patient data.RESULTS: Of the 637 SSc patients recruited, the majority was female (80.2%-83.3%), aged between 52.4-56.7 years with limited cutaneous disease subtype (48.6%-66.7%). HRQoL scores were lower for SSc patients than the general population (SF-36 physical component summary (PCS) score (36.4-39.6), mental component summary (MCS) score (41.0-46.4)). Determinants of SF-36 PCS by meta-analysis included increasing age (β=-0.1, 95%CI -0.2, -0.01), diffuse cutaneous disease subtype (β=-8.4, 95%CI -10.6, -6.3), and pulmonary arterial hypertension (β=-10.9, 95%CI -16.6, -5.3). Increasing age (β=0.09, 95%CI 0.0, 0.18) was the only variable associated with SF-36 MCS. Analyses using individual patient data revealed similar results to those of the meta-analysis of cohort data.CONCLUSIONS: Our study provides estimates of HRQoL in a large inception SSc cohort and provides evidence that individual patient data analysis is valid in the INSYNC dataset.
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