Predicting Disease Activity in Rheumatoid Arthritis with the Fibromyalgia Survey Questionnaire: Does the Severity of Fibromyalgia Symptoms Matter?

Methods

Results

Of the 295 participants in the CPIRA study, 57 were excluded from this study because they were lost to follow-up, and another 46 were excluded due to missing baseline data. There were no significant differences in baseline clinical variables between included and excluded participants.

Clinical characteristics of the included participants are found in Table 1. Among the 192 participants in this analysis, the majority were women (83.9%) and white (76.0%). The mean ± SD of age and RA disease duration were 55.2 ± 14.4 and 10.4 ± 12.5 years, respectively. The average baseline scores for the FSQ, WPI and SSS was 11.1, 5.8 and 5.3, respectively. The observed range of baseline FSQ scores was 0 to 28, while the potential range was 0 to 31. The observed range was identical to the potential range for the WPI [0,19] and the SSS [0,12], respectively. Mean ± SD baseline DAS28-CRP was 4.3 ± 1.3, which is within range of moderate disease activity (DAS28-CRP >3.2 and ≤ 5.1)(18). Mean ± SD follow-up DAS28-CRP was 3.3 ± 1.3, decreasing by 1.0 ± 1.1 from mean baseline DAS28-CRP. Tender joint count decreased by 4.5 ± 6.8 joints, swollen joint count decreased by 2.6 ± 5.0 joints, patient global assessment decreased by 1.4 ± 2.5, and hsCRP decreased by 2.7 ± 11.4 mg/L.

We hypothesized that a higher FSQ score prior to DMARD initiation or switch would predict a higher DAS28-CRP score at follow-up. Univariable linear regression (Table 2) demonstrated that participants’ baseline FSQ score significantly predicted follow-up DAS28-CRP (B= 0.090, 95%CI=[0.060, 0.121], β=0.389, 95%CI=[0.258, 0.521], p<0.001). The fit of the model, however, was limited, with an adjusted R² of 0.147. When adjusted for baseline DAS28-CRP and other demographic characteristics, baseline FSQ score likewise positively predicted DAS28-CRP score after 12 weeks of DMARD treatment, though with a lower regression coefficient (B=0.037, 95%CI=[0.008, 0.066], β=0.159, 95%CI=[0.033, 0.285], p=0.014). The adjusted R² of this model was 0.419. The addition of further covariates to model 3 did not appreciably change the regression coefficient or confidence intervals (B= 0.039, 95%CI=[0.009, 0.069], β=0.168, 95%CI=[0.037, 0.299], p=0.012).

We hypothesized that, upon splitting the FSQ into its component scales, the WPI and the SSS, both the WPI and the SSS would positively predict follow-up DAS28-CRP. Multivariable linear regression (Table 3) demonstrated, however, that the WPI was the only component of the FSQ score that significantly predicted follow-up DAS28-CRP (B=0.077, 95%CI=[0.031, 0.124], β=0.230, 95%CI=[0.093, 0.367], p=0.001 for model 3). Conversely, the SSS did not predict follow-up DAS28-CRP (B=−0.028, 95%CI=[−0.095, 0.040], β=−0.055, 95%CI=[−0.191, 0.081], p=0.425 for model 3). In comparing standardized coefficients of WPI and FSQ across equivalent models, the standardized coefficient of WPI was greater (WPI, β=0.230 vs. FSQ, β=0.168 for models 3, respectively).

Discussion

Fibromyalgia symptom severity, defined by the FSQ score, weakly predicts RA disease activity levels after patients initiate or switch DMARD therapy. Upon separating the FSQ into its two components, the WPI and the SSS, the WPI predicted RA disease activity, but the SSS did not. While the standardized coefficients for the SSS were close to zero with nonsignificant p-values, the standardized coefficients for the WPI were statistically significant and greater than the standardized coefficients for the FSQ in equivalent models, providing evidence that the WPI is the major component of the FSQ that predicts RA disease activity. To our knowledge, this is the first longitudinal analysis to demonstrate that FSQ scores independently predict RA disease activity after treatment, and that the WPI is the primary source of the FSQ’s predictive value for DAS28-CRP score after DMARD treatment.

Our results are consistent with previous studies showing that, among patients with RA, a comorbid fibromyalgia diagnosis is associated with higher RA disease activity (19–23). In particular, previous studies have shown that the patient-determined components of RA disease activity scores (i.e., tender joint count and patient global assessment) are elevated for patients who have both RA and fibromyalgia relative to patients with RA who do not have concomitant fibromyalgia. Conversely, the clinician-determined and laboratory components of RA disease activity scores (i.e., swollen joint count and CRP/ESR) are typically equivalent among RA patients with and without fibromyalgia(20–23). Likewise, Duran et al. found that patients with RA and concomitant fibromyalgia are less likely to reach DAS28-CRP remission upon treatment, with persistently elevated tender joint count, the sole patient-determined variable of DAS28-CRP(3), preventing DAS28-CRP remission(22). Andersson et al. similarly showed that, over a 5-year period, persistently elevated tender joint counts and patient global assessments led to higher DAS28-CRP scores among patients with RA who have chronic widespread pain, a diagnosis on the spectrum of fibromyalgia(24).

Our study builds upon these studies by using the FSQ, a continuous measure of the severity of fibromyalgia symptoms, rather than the binary outcome of physician-diagnosed fibromyalgia. Recent studies suggest that fibromyalgia may be more appropriately conceived as a condition that spans a continuum of severity, rather than as a discrete, binary diagnosis(25–28). Wolfe et al. reported in a cross-sectional analysis that, with increasing FSQ scores, the severity of common clinical indicators of RA disease activity likewise increases, though the relationship is stronger with patient-determined rather than clinician-determined variables(29). In terms of the relationship between FSQ and long-term outcomes, Kim et al. showed that, among RA patients, increased FSQ scores at baseline are independently predictive of worse MDHAQ scores, a measure of functional status, two years later(30). Our study contributes additional information by demonstrating that baseline FSQ scores predict DAS28-CRP scores approximately 12 weeks after initiating or changing DMARD treatment.

This study also builds upon previous analyses from the CPIRA study in which we evaluated the ability of QST to predict treatment response(12). Inefficient conditioned pain modulation (CPM), a measure of endogenous analgesia, was associated with significantly lower odds of good treatment response. These results are consistent with findings from our current study because abnormalities in endogenous analgesia have been implicated in the pathogenesis of fibromyalgia(31,32). In subsequent analyses of CPIRA data, however, we found no association between FSQ and CPM and only weak correlations between FSQ and other QST measures(33). These results suggest that the FSQ likely reflects different aspects of the fibromyalgia experience than the abnormalities in endogenous analgesia assessed by CPM.

The predictive ability of FSQ does not seem limited to RA. A few studies have also reported that the FSQ predicts pain-related outcomes after surgery. A study by Cheng et al. indicated that greater FSQ scores are predictive of worse quality of recovery from shoulder arthroscopy(34). Others studies revealed higher FSQ scores to be associated with postoperative opioid use after a hysterectomy and lower-extremity joint arthroplasty(35,36). Taken together, these studies suggest that the pathway linking the FSQ to treatment outcomes is likely related to its ability to predict individuals’ pain experience, as opposed to specific disease mechanisms.

In addition to analyzing the FSQ as a whole, this study was the first to examine associations between the two scales that compose the FSQ (i.e., the WPI and the SSS) and RA treatment outcomes. The WPI was the main source of the FSQ’s predictive value for DAS28-CRP, while the SSS did not contribute to FSQ’s prediction of RA disease activity after treatment. One potential implication is that the WPI better captures CNS regulatory processes that do not respond to the anti-inflammatory effects of DMARDs. Alternatively, we must also consider the possibility that the WPI and DAS28-CRP do not have sufficient specificity to distinguish between abnormalities in CNS regulation associated with non-inflammatory muscle pain versus inflammatory joint pain. For example, patients may indicate that they have pain in the forearm on the WPI, when the pain is actually due to inflammation at the wrist. Conversely, patients may be tender at joint sites because of widespread pain sensitivity due to fibromyalgia, rather than joint inflammation. Further investigation is warranted to determine if there is overlap or conflation between RA patients’ joint and non-joint pain sites and, if so, whether the WPI and/or DAS28-CRP may warrant modification.

Our study has many strengths. First, we assessed the severity of fibromyalgia symptoms as a continuous variable rather than simply the binary outcome of physician-diagnosed fibromyalgia. There was a wide range of baseline FSQ scores (0-28 out of a possible range of 0-31), enabling assessment of a per-unit increase across a sufficient range of FSQ. Second, the FSQ is based on the 2010 modified American College of Rheumatology Diagnostic Criteria for Fibromyalgia, which is a validated measure for diagnosing fibromyalgia(13). The use of a validated, standardized assessment is important because fibromyalgia is frequently over-diagnosed when the diagnosis is based primarily on physician gestalt(37). Third, our study goes beyond examining the FSQ’s association with RA disease activity by investigating the distinctive relationships of the two components of the FSQ with RA disease activity. Lastly, our study incorporated multivariable analyses, enabling adjustment for confounders. Unlike many prior analyses, we included baseline DAS28-CRP as a covariate. This decision was based on previous literature indicating that: a) fibromyalgia is cross-sectionally associated with elevated DAS28-CRP(20,22,23), and b) higher DAS28 scores at baseline are predictive of elevated DAS28 scores in the future(3,38,39). Thus, excluding baseline DAS28-CRP scores may lead to an overestimation of FSQ’s relationship to treatment outcomes.

The study also has several limitations. First, the regression coefficient for the association between baseline FSQ and follow-up DAS28-CRP was small, with a 1-unit difference in FSQ predicting a 0.037 difference in follow-up DAS28-CRP. Second, the statistical models have a notable amount of unexplained variation, with R² = 0.414 for the most robust model in the primary analysis. The degree of unexplained variation is consistent with the absence of strong predictors for RA treatment outcomes in the literature(3–6). In addition, composite measures, such as the FSQ and DAS28-CRP, likely capture signs and symptoms from heterogenous pathologies, contributing to variance. We also did not control for the potential initiation of nonpharmacologic treatments, such as mental health care or exercise, which have beneficial impacts on chronic pain outcomes that may be partially captured in the tender joint and patient global assessment components of the DAS28-CRP. Furthermore, patients received heterogenous RA therapies with differing mechanisms of action. Lastly, our study included only two time points over a 12-week period. A study of longer duration with more time points would provide added confidence in the observed changes.

The findings of this study have notable clinical implications. First, this study provides further evidence that non-inflammatory processes impact DAS28-CRP, a tool designed to assess the activity of an inflammatory disease. Given the influence of fibromyalgia symptoms on RA disease activity as measured by DAS28-CRP, accounting for the effect of fibromyalgia symptoms on RA treatment outcomes should be considered. Second, the easily administered FSQ can contribute to a more informed prognosis of patients’ RA. The results, moreover, suggest that specific fibromyalgia symptoms have prognostic implications. A patient with high FSQ scores due to widespread pain may be more likely to have high RA disease activity after DMARD initiation than a patient with high FSQ scores due to fatigue and cognitive symptoms. These patients may benefit from adjunctive pharmacologic and non-pharmacologic therapies to address fibromyalgia symptoms, such as tricyclic antidepressants, serotonin and norepinephrine reuptake inhibitors, exercise, and cognitive behavioral therapy. Healthcare providers should consider using the FSQ, in particular the WPI component of the FSQ, when developing personalized care plans for patients with RA.