Outcome Measures in Large Vessel Vasculitis: Relationship Between Patient-, Physician-, Imaging-, and Laboratory-Based Assessments

Abstract

Objective: To assess the relationship between measures of disease assessment in patients with large vessel vasculitis.

Methods: Patients with giant cell arteritis (GCA) or Takayasu arteritis (TAK) were recruited into a prospective, observational cohort. Assessments within the following outcomes were independently recorded: 1) patient-reported outcomes (Multidimensional Fatigue Inventory, patient global assessment of disease activity [PtGA], Short Form 36 health survey [SF-36], Brief Illness Perception Questionnaire), 2) physician global assessment of disease activity (PhGA), 3) laboratory outcomes (C-reactive protein [CRP] level, erythrocyte sedimentation rate [ESR]), and 4) imaging outcomes (PETVAS, a qualitative score of vascular 18 F-fluorodeoxyglucose-positron emission tomography activity).

Results: Analyses were performed on 112 patients (GCA = 56, TAK = 56), over 296 visits, with a median follow-up of 6 months. Correlation network analysis revealed assessment measures clustered independently by type of outcome. PhGA was centrally linked to all other outcome types, but correlations were modest (ρ = 0.12-0.32; P < 0.05). PETVAS, CRP level, and PtGA were independently associated with clinically active disease. All 4 patient-reported outcomes strongly correlated with each other (ρ = 0.35-0.60; P < 0.0001). Patient-reported outcomes were not correlated with PETVAS, and only PtGA correlated with CRP level (ρ = 0.16; P < 0.01). Patients whose clinical assessment changed from active disease to remission (n = 29) had a corresponding significant decrease in ESR, CRP level, and PETVAS at the remission visit. Patients whose clinical assessment changed from remission to active disease (n = 11) had a corresponding significant increase in CRP level and PtGA at the active visit.

Conclusion: Measures of disease assessment in large vessel vasculitis consist of independent, yet complementary, outcomes, supporting the need to develop composite outcome measures or a standard set of measures covering multiple types of outcomes.

Trial registration: ClinicalTrials.gov NCT02257866.

© 2019, American College of Rheumatology. This article has been contributed to by US Government employees and their work is in the public domain in the USA.

Figures

Figure 1.. Correlation network of outcome measures in all patients with LVV

Correlation network of the significant Spearman ρ correlation coefficients (p<0.05) between outcome measures created using the R package corrr. Color and thickness of the edges between nodes indicates the strength of the correlation. Nodes for each outcome measure are clustered in space using multidimensional scaling of the absolute values of the correlations, such that outcome measures with the highest overall magnitude of correlation with each other are closer in space. For ease of visualization, the SF-36 PCS and MCS measures were multiplied by −1 so that a higher score would indicate a worse outcome. MFI= Multi-dimensional fatigue inventory; BIPQ= brief illness perception questionnaire; Neg SF-36 PCS= negatively transformed 36-item short form health survey physical component summary score; Neg SF-36 MCS= negatively transformed 36-item short form health survey mental component summary score; CRP= c-reactive protein; ESR= erythrocyte sedimentation rate; PETVAS= qualitative score of vascular FDG-PET activity.

Figure 2.. Longitudinal analysis of outcome measures in patients experiencing a change in clinical disease activity from active disease to remission

(A) Patient reported outcomes, (B) Laboratory Outcomes, and (C) Imaging Outcome. Data is plotted as median and interquartile range and n=22–29. Wilcoxon signed rank test was used to compare outcome measure scores between active and remission visits. *p

Figure 3.. Longitudinal analysis of outcome measures in patients experiencing a change in clinical disease activity from remission to active disease

(A) Patient reported outcomes, (B) Laboratory Outcomes, and (C) Imaging Outcome. Data is plotted as median and interquartile range and n=8–11. Wilcoxon signed rank test was used to compare outcome measure scores between remission and active visits. *p