Quantification of the whole-body burden of radiographic osteoarthritis using factor analysis

Abstract

IntroductionAlthough osteoarthritis (OA) commonly involves multiple joints, no widely accepted method for quantifying whole-body OA burden exists. Therefore, our aim was to apply factor analytic methods to radiographic OA (rOA) grades across multiple joint sites, representing both presence and severity, to quantify the burden of rOA.MethodsWe used cross-sectional data from the Johnston County Osteoarthritis Project. The sample (n = 2092) had a mean age of 65 ± 11 years, body mass index (BMI) 31 ± 7 kg/m2, with 33% men and 34% African Americans. A single expert reader (intra-rater κ = 0.89) provided radiographic grades based on standard atlases for the hands (30 joints, including bilateral distal and proximal interphalangeal [IP], thumb IP, metacarpophalangeal [MCP] and carpometacarpal [CMC] joints), knees (patellofemoral and tibiofemoral, 4 joints), hips (2 joints), and spine (5 levels [L1/2 to L5/S1]). All grades were entered into an exploratory common factor analysis as continuous variables. Stratified factor analyses were used to look for differences by gender, race, age, and cohort subgroups.ResultsFour factors were identified as follows: IP/CMC factor (20 joints), MCP factor (8 joints), Knee factor (4 joints), Spine factor (5 levels). These factors had high internal consistency reliability (Cronbach's α range 0.80 to 0.95), were not collapsible into a single factor, and had moderate between-factor correlations (Pearson correlation coefficient r = 0.24 to 0.44). There were no major differences in factor structure when stratified by subgroup.ConclusionsThe 4 factors obtained in this analysis indicate that the variables contained within each factor share an underlying cause, but the 4 factors are distinct, suggesting that combining these joint sites into one overall measure is not appropriate. Using such factors to reflect multi-joint rOA in statistical models can reduce the number of variables needed and increase precision.

Lumbar spine radiographic features and demographic, clinical, and radiographic knee, hip, and hand osteoarthritis

“…Previous work in the JoCo OA Project and others have questioned whether the process of hip OA is a separate entity and not considered as part of generalized OA. 32-34 Our findings here indicate that hip degeneration may occur through a different etiologic process when compared to that of the lumbar spine. This is not surprising given the prevalence of morphometric abnormalities cited as common etiologies for hip OA.…”

Establishment of reference intervals for osteoarthritis-related soluble biomarkers: the FNIH/OARSI OA Biomarkers Consortium

“…Radiographs were obtained of the knees, hips, hands and spine as described previously 9. All radiographs were read by a single experienced musculoskeletal radiologist (JBR), previously shown to have high intrarater and inter-rater reliability (kappa 0.89 and 0.86, respectively) 10…”

Composite measures of multi-joint symptoms, but not of radiographic osteoarthritis, are associated with functional outcomes: the Johnston County Osteoarthritis Project

“…During the clinic examination, we obtained radiographs, physical performance-based measures, and body mass index (BMI, calculated in kg/m 2 from measured height (cm) and weight (kg)). Individuals included in these analyses had complete multi-joint radiographic data (obtained 2003–4 and 2006–10, n=1373, see also [6]), symptom and outcome data, resulting in 1307 individuals available for the HAQ outcome and 1303 individuals for the gait speed outcome (although 3 were excluded for implausible gait speed values before analysis, table 1). The JoCo OA study has been continuously approved by the Institutional Review Boards of the University of North Carolina and the Centers for Disease Control and Prevention in Atlanta, GA.…”

“…Functional outcomes, both self-reported (HAQ), and performance-based (gait speed), are of interest as they represent the impact of OA on daily life and function of affected individuals [3–5]. We have previously reported the factor structure underlying multiple joint rOA grades [6] and presented composite scores as a potential method to include information about multiple joint sites in models of systemic outcomes. By combining variables that represent a common, empirically determined, underlying construct, for example by including a sum of radiographic grades from 20 hand joints as a single variable in a model, we can account for the impact of rOA at all of these sites on a given outcome.…”