Abstract
Objective
Among rheumatoid arthritis (RA) patients, pain may exist out of proportion to peripheral inflammation. This observation suggests that central nervous system pain amplification mechanisms, such as diminished conditioned pain modulation (CPM), may play a role in enhancing pain perception among some RA patients. We examined CPM, pressure pain threshold and pressure pain tolerance among RA patients compared to controls.
Methods
Fifty-eight female RA patients and 54 age-matched controls without chronic pain underwent quantitative sensory testing (QST) to assess CPM, pressure pain threshold and pressure pain tolerance. CPM was induced using a cold water bath, and pain threshold (when patients first felt pain) and tolerance (when pain was too much to bear) were assessed with an algometer. Associations between RA and QST measures were analyzed using linear regression. Sleep problems, mental health and inflammation were assessed as mediators of the relationship between RA and QST measures.
Results
Median CPM levels were 0.5 kg/cm2 (interquartile range (IQR) −0.1, 1.6) among RA patients compared to 1.5 kg/cm2 (IQR −0.1, 2.5) among controls (P = 0.04). Relative to controls, RA patients had lower pain threshold and tolerance at the wrists (P ≤ 0.05). Compared to controls, RA patients had greater problems with sleep, catastrophizing, depression and anxiety (P < 0.0001). Mediation analyses suggested that low CPM levels may be partially attributable to sleep disturbance (P = 0.04).
Conclusion
RA patients have impaired CPM relative to pain-free controls. Sleep problems may mediate the association between RA and attenuated CPM.
Pain is the most common and disabling symptom of rheumatoid arthritis (RA). Although physicians often assume that inflammation is the stimulus for pain, many RA patients continue to have pain despite adequately suppressed inflammation (1). Studies of experimental pain sensitivity have shown that pressure pain thresholds, the degree of pressure eliciting pain, are lower in RA patients than healthy controls (2, 3). These thresholds are lower at joint and non-joint sites (4, 5). The widespread distribution of hyperalgesia suggests that the underlying mechanisms originate from the central nervous system (CNS), rather than focal sites of peripheral inflammation.
In animal models, one well-described CNS mechanism for modulating pain involves descending analgesic pathways, which “descend” from the cerebral cortex, hypothalamus and brainstem to regulate peripheral sensory input in the spinal cord (6). In response to acutely painful stimuli, inhibitory pathways are activated, leading to a diffuse decrease in pain. In humans, the effects of these pathways may be seen when the perception of noxious stimuli, such as arthritis pain, is momentarily attenuated after experiencing another strong noxious stimulus, such as stubbing one’s toe. In the experimental setting, this phenomenon has been termed “loss of diffuse noxious inhibitory controls” or diminished “conditioned pain modulation” (CPM) (7). CPM can be measured with a non-invasive test and is a sensitive measure of deficits in central pain modulation in chronic widespread pain conditions (8).
In this study, we measured CPM and pressure pain threshold and pressure pain tolerance (the degree of pressure eliciting unbearable pain) among RA patients and age-matched controls. We also assessed the role of sleep problems, mental health and inflammatory markers in mediating differences in CPM and pain sensitivity. Variables were considered mediators if, when added to the models, they partially or completely diminished the association between RA and the outcomes of CPM, pressure pain threshold or pressure pain tolerance. We hypothesized that RA patients would have diminished CPM and lower pressure pain threshold and pressure pain tolerance relative to controls. We also hypothesized that sleep problems and catastrophizing would mediate the differences in CPM and pressure pain threshold and pain tolerance between RA patients and controls.
PATIENTS AND METHODS
This study compared quantitative sensory testing measures (QST), including CPM, pain threshold and pain tolerance, between RA patients and age-matched controls.
Study population
We recruited female RA patients from the rheumatology clinics of an academic medical center and age-matched controls from a hospital-based registry for study volunteers and from the surrounding community between April 2010 and July 2011. Inclusion criteria included female sex and age ≥ 40 years. We limited the study to women because RA occurs predominantly in women, and pain threshold and pain tolerance are lower among women than men. Exclusion criteria included the use of opioid pain medications and cold-sensitive conditions). We required RA patients to have a confirmed diagnosis by a board-certified rheumatologist. Controls were recruited to match RA patients in age. Exclusion criteria for controls included1) systemic inflammatory diseases, 2) chronic pain and 3) chronic pain for any other reason. The Partner Institutional Review Board approved the study. All participants provided written informed consent.
Assessment of clinical variables
A board-certified rheumatologist performed a physical examination, including tender and swollen joint counts. We collected blood samples to assess C-reactive protein (CRP), tumor necrosis factor-alpha (TNF-α) and interleukin-6 (IL-6). We calculated the disease activity score in 28 joints (DAS28) from the tender joint count, swollen joint count and CRP (9). A list of all current medications was obtained. Mental health was measured using the Hospital Anxiety and Depression Scale (HADS), a validated 14-item questionnaire that assesses depression and anxiety in physically ill patients (10). We quantified sleep disturbances using the Sleep Problems Index II of the Medical Outcomes Study (MOS) sleep scale, a validated, 12-item questionnaire that assesses sleep problems in chronically ill patients (11). We measured pain catastrophizing using the Pain Catastrophizing Scale (PCS), a validated, 13-item scale that assesses a set of negative cognitive and emotional processes, including helplessness, pessimism, rumination and magnification of symptoms (12). All data were double-entered by two individuals and checked against each other for accuracy.
Quantitative sensory testing
QST consisted of pressure pain threshold and pressure pain tolerance testing as well as a paradigm to test CPM. One rheumatologist (YCL), trained in QST, performed all testing. She explained the procedures using standard scripts and was blinded to case-control status. To ensure that she could not determine whether a patient had RA based on physical examination, participants wore large cotton gloves to cover the hands and wrists, the most common sites of RA-related inflammation and structural damage.
All pain threshold and pain tolerance tests were performed twice on the same day, with two to five minutes separating tests. The first test was designated a trial run, to accustom participants to testing procedures. The second test was designated the test run, from which all data were obtained. Tests were performed on the same day to minimize heterogeneity caused by daily changes in environment, disease activity and mental status. Our previous studies have indicated that pressure pain thresholds and tolerances are highly reproducible when testing is done on the same day (13).
Pressure pain threshold and pressure pain tolerance testing was performed at joints (dorsal wrists on the ulnar side of the extensor pollicis longus tendon and knees, immediately proximal to the patella), sites close to joints (thumbnails) and sites distant from joints (superior trapezius muscles), using a Wagner FPK 20 algometer (Wagner Instruments, Greenwich, CT, USA). This instrument has an accuracy of ± 2 graduations for capacities through 2500 grams and ± 1 graduation over 2500 grams. It provides reproducible measurements of pain threshold and pain tolerance among RA patients, with intraclass correlations ranging from 0.75 to 0.92 (13).
Pressure was increased at a rate of approximately 1 kg/s to a maximum of 11 kg. The pain threshold was defined as the pressure at which the participants first felt pain. The pain tolerance was defined as the pressure at which the participants wanted to stop testing due to “too much pain.” The order of testing was: 1) thumbnails, 2) wrists, 3) trapezius muscles, 4) knees. The order was standardized to provide uniformity to study measurements. The order was chosen such that non-joint areas were interspersed with joint areas, minimizing the risk for a systematic bias between joint versus non-joint sites. All assessments were performed bilaterally.
The CPM paradigm was performed using a conditioning stimulus (a relatively tonic noxious stimulus that leads to activation of CPM) and a test stimulus (a brief painful stimulus used to evaluate the analgesic response to the conditioning stimulus) (14–16). The conditioning stimulus was immersion of the right hand in a cold water bath at 6° C, and the test stimulus was pressure to the left superior portion of the trapezius muscle. Participants were instructed to put their hand in the water bath for 30 seconds. Pressure pain threshold was assessed immediately before immersion and 20 seconds after immersion, while the participants’ hand remained in the cold water. The magnitude of CPM was defined as the change in pressure pain threshold between baseline and 20 seconds after cold water immersion. Positive scores reflected a greater analgesic response to the cold pressor test (e.g., more CPM).
Power calculation
The standard deviation of CPM among RA patients and healthy controls was estimated from a small study of 21 RA patients and 21 healthy controls (4). With α = 0.05 and standard deviation = 1.5 kg/cm2, a sample size of 50 RA patients and 50 controls would give us 90% power to see a difference in CPM of 1.0 kg/cm2. Additional participants were enrolled to ensure adequate power in case data were not obtainable from all participants. This precaution was undertaken to account for participants with pain thresholds exceeding the upper limit of detection (11 kg/cm2) at baseline because further increases in pain threshold would not be detectable.
Statistical analyses
All statistical analyses were performed using the SAS 9.2 software package (SAS Institute, Cary, NC, USA). Descriptive measures, including medians and interquartile ranges (IQRs), were determined. Fisher’s exact tests, Wilcoxon rank sum tests and simple linear regression models were used to compare clinical variables among RA patients and controls, as appropriate. Unadjusted associations between RA and QST measures were assessed using simple linear regression. We analyzed adjusted associations between RA and QST measures using multivariable linear regression, including RA diagnosis first and subsequently adding covariates (MOS sleep problems index II, HADS depression, HADS anxiety, pain catastrophizing, swollen joint count, CRP, TNF-α, IL-6) to the models. We also examined first order interactions between RA and each covariate. The strength of association was determined using regression coefficients (β) and P values for the Type III Sum of Squares estimates, which are not affected by the order of variable entry. The β-coefficient represented the difference in outcome between cases and controls. The threshold for significance was set as a two-tailed P ≤ 0.05.
If the β-coefficient for RA decreased by > 20% in adjusted analyses compared to unadjusted analyses, we conducted mediation analyses according to the Baron and Kenny criteria (17). Specifically, we used simple and multivariable linear regression models to assess whether: 1) the independent variable was significantly associated with the dependent variable, 2) the independent variable was significantly associated with the proposed mediator and 3) the proposed mediator was significantly associated with the dependent variable, adjusted for the independent variable. To confirm these results, we also assessed mediation via the Sobel test and a nonparametric boot-strapping approach, utilizing 5000 bootstrap samples (18).
To explore the possibility that RA medications contributed to QST differences between RA patients and controls, we used simple linear regression to assess the association between medications (non-steroidal anti-inflammatory drugs (NSAIDs), corticosteroids, non-biologic disease-modifying antirheumatic drugs (DMARDs) and biologic DMARDs) and CPM and pressure pain threshold and pressure pain tolerance among RA patients.
RESULTS
Patient characteristics
RA patients (N = 58) did not differ from controls (N = 54) in age, race, smoking status or alcohol use (Table 1). No participants had a history of peripheral neuropathy. Six participants had diabetes. These participants were evenly distributed in the case and control groups. Eighteen patients were taking serotonin reuptake inhibitors. Five patients were taking neuroleptic medications, and one patient was taking a tricycyclic antidepressant. RA patients did not differ significantly from controls in the use of these medications.
Table 1.
Clinical characteristics of rheumatoid arthritis (RA) patients and controls. Values for continuous variables are expressed as medians and interquartile ranges. Values for dichotomous variables are expressed as counts and percentages.
| Characteristic | RA (N = 58) |
Controls (N = 54) |
P |
|---|---|---|---|
| Demographics | |||
| Age, years | 60.9 (9.7) | 62.5 (9.3) | 0.34 |
| White | 53 (91.4%) | 44 (81.5%) | 0.17 |
| Current smoking | 4 (6.9%) | 4 (7.4%) | 1.00 |
| Alcohol | 12 (20.7%) | 10 (18.5%) | 0.82 |
| Post-menopausal | 48 (82.8%) | 44 (81.4%) | 0.80 |
| Inflammatory/Pain Measures | |||
| Tender joint count | 3.0 (1.0, 5.0) | 0.0 (0.0, 0.0) | <0.0001 |
| Swollen joint count | 0.5 (0.0, 3.0) | 0.0 (0.0, 0.0) | <0.0001 |
| C-reactive protein | 1.4 (0.6, 4.1) | 0.6 (0.3, 1.4) | 0.03 |
| Interleukin-6 | 2.8 (1.6, 6.4) | 1.4 (1.2, 2.3) | 0.26 |
| TNF-αa | 1.9 (1.0, 5.0) | 1.3 (1.0, 1.8) | 0.01 |
| DAS28a | 2.7 (2.5, 3.3) | 1.4 (1.3, 1.7) | <0.0001 |
| BPI current pain | 2.0 (1.0, 4.0) | 0.0 (0.0, 0.0) | <0.0001 |
| Sleep/Psych Measures | |||
| HADS Anxietya | 5.5 (4.0, 9.0) | 2.0 (1.0, 4.0) | <0.0001 |
| HADS Depressiona | 3.0 (1.0, 6.0) | 1.0 (0.0, 3.0) | <0.0001 |
| MOS Sleep Index IIa | 30.6 (20.6, 48.9) | 13.3 (5.6, 20.6) | <0.0001 |
| Catastrophizing | 11.0 (4.0, 21.0) | 0.0 (0.0, 3.0) | <0.0001 |
| Medications | |||
| NSAIDs | 22 (37.9%) | 1 (4.4%) | <0.0001 |
| Corticosteroids | 16 (27.6%) | 0 (0.0%) | <0.0001 |
| Non-biologic DMARDs | 38 (65.5%) | 0 (0.0%) | <0.0001 |
| Biologic DMARDs | 27 (46.6%) | 0 (0.0%) | <0.0001 |
TNF-α = tumor necrosis factor-alpha. DAS28 = disease activity in 28 joints, measured from tender joint count, swollen joint count and C-reactive protein. HADS = Hospital Anxiety and Depression Scale. MOS = Medical Outcomes Study. NSAIDs = non-steroidal anti-inflammatory drugs. DMARDs = disease modifying anti-rheumatic drugs.
Relative to controls, RA patients had significantly higher serum levels of CRP (P = 0.0005), TNF-α (P = 0.01) and IL-6 (P < 0.0001). RA patients were also significantly more likely to have problems with anxiety, depression, sleep and catastrophizing (P ≤ 0.0001). RA patients were more likely to take NSAIDs, corticosteroids, non-biologic DMARDs and biologic DMARDs (P ≤ 0.0001).
Clinical pain severity scores were significantly higher among RA patients compared to controls (P < 0.0001). Spearman’s correlations between clinical pain scores and QST measures of pain varied from −0.12 for left trapezius threshold to −0.33 for right wrist tolerance. The correlation between clinical pain intensity and CPM was −0.17. Among RA patients, the median number of swollen joints was 0.5 with an interquartile range (IQR) of 0.0 to 3.0 (Table 1). Eight out of 116 wrists (6.9%) and 12 out of 116 knees (10.3%) were swollen. Compared to joints that were not swollen, joints that were swollen had lower pain thresholds, though this was only statistically significant at the right wrist (P = 0.05).
Unadjusted associations between RA and QST measures
Median CPM levels were lower among RA patients (0.5 kg/cm2 (IQR -0.1, 1.6)) compared to controls (1.5 kg/cm2 (IQR -0.1, 2.5)) without chronic pain conditions (P = 0.04) (Figure 1). Relative to controls, RA patients had significantly lower pressure pain threshold at the wrists and right knee (P ≤ 0.05) and lower pressure pain tolerance (P ≤ 0.03) at bilateral wrists and knees (Table 2). Pain threshold and pain tolerance at the thumbs and trapezius muscles were also lower among RA patients compared to controls, but these differences were not statistically significant (Table 2).
Figure 1.
Distribution of conditioned pain modulation levels among rheumatoid arthritis patients and controls.
Table 2.
Median values and interquartile ranges for CPM, pressure pain threshold and pressure pain tolerance in RA patients compared to controls.a
| Quantitative Sensory Test |
Unadjusted median values in kg/cm2 (Interquartile range) |
Model 1: Unadjustedb |
Model 2: Adjusted for sleepb |
Model 3: Adjusted for catastrophizi ngb |
||||
|---|---|---|---|---|---|---|---|---|
| RA (N = 58) |
Controls (N = 54) |
β | P | β | P | β | P | |
| Central Pain Measure |
||||||||
| CPM | 0.5 (−0.1, 1.6) | 1.5 (−0.1, 2.5) | −0.59 | 0.04 | −0.19c | 0.57 | −0.60 | 0.09 |
| Pain Threshold | ||||||||
| Left Wrist | 6.1 (4.8, 8.5) | 7.7 (5.7, 11.0) | −0.99 | 0.05 | −1.21 | 0.04 | −0.40c | 0.49 |
| Right Wrist | 6.8 (4.8, 8.8) | 8.1 (6.0, 10.3) | −1.06 | 0.03 | −0.99 | 0.08 | −0.54c | 0.32 |
| Left Knee | 8.4 (6.0, 11.0) | 9.2 (7.5, 11.0) | −0.76 | 0.10 | −0.90 | 0.10 | −0.05c | 0.93 |
| Right Knee | 7.5 (5.9, 11.0) | 9.4 (7.3, 11.0) | −1.17 | 0.01 | −1.30 | 0.02 | −0.67c | 0.19 |
| Left Thumb | 6.4 (4.4, 8.3) | 6.9 (5.7, 11.0) | −0.57 | 0.25 | - | - | - | - |
| Right Thumb | 6.7 (5.0, 9.8) | 8.1 (5.7, 9.8) | −0.53 | 0.31 | - | - | - | - |
| Left Trapezius | 5.5 (3.8, 7.8) | 6.2 (4.1, 8.1) | −0.37 | 0.45 | - | - | - | - |
| Right Trapezius | 5.2 (3.8, 7.9) | 6.4 (4.2, 9.3) | −0.61 | 0.23 | - | - | - | - |
| Pain Tolerance | ||||||||
| Left Wrist | 8.0 (6.2, 11.0) | 10.4 (7.3, 11.0) | −1.04 | 0.02 | −1.23 | 0.01 | −0.79c | 0.11 |
| Right Wrist | 8.8 (6.3, 11.0) | 11.0 (8.1, 11.0) | −1.28 | 0.002 | −1.31 | 0.007 | −0.89c | 0.05 |
| Left Knee | 9.8 (7.8, 11.0) | 11.0 (8.9, 11.0) | −0.90 | 0.03 | −0.89 | 0.06 | −0.40c | 0.35 |
| Right Knee | 9.0 (7.4, 11.0) | 11.0 (9.8, 11.0) | −1.28 | 0.001 | −1.39 | 0.004 | −0.86c | 0.20 |
| Left Thumb | 8.5 (6.2, 11.0) | 9.0 (7.1, 11.0) | −0.55 | 0.23 | - | - | - | - |
| Right Thumb | 9.8 (7.2, 11.0) | 11.0 (8.5, 11.0) | −0.60 | 0.17 | - | - | - | - |
| Left Trapezius | 7.1 (4.8, 9.5) | 8.2 (5.2, 10.5) | −0.51 | 0.32 | - | - | - | - |
| Right Trapezius | 7.0 (4.8, 9.0) | 8.8 (5.2, 11.0) | −0.82 | 0.12 | - | - | - | - |
CPM: conditioned pain modulation, RA: rheumatoid arthritis.
Each cell represents the β-coefficient or P-value for the association between RA and the outcome listed in the row. Model 1 is unadjusted. Model 2 is adjusted for sleep problems. Model 3 is adjusted for pain catastrophizing.
≥ 20% decrease in β from unadjusted model. Because mediation can only occur when the original association between the independent and dependent variables is significant, β and P values are only provided for models in which the P-value for the original association between RA and outcome was ≤ 0.10.
Adjusted associations between RA and CPM
The β-coefficient for the association between RA and CPM decreased by > 20% when the MOS sleep problems score was added to linear regression models assessing the association between RA and CPM, suggesting that sleep problems may mediate or confound this association (Table 2). In analyses stratified by clinical pain intensity, similar decrements in the β-coefficient for the association between RA and CPM were noted. No significant decreases in the β-coefficients for RA were noted when the pain catastrophizing score, HADS anxiety score, HADS depression score, swollen joint count, CRP, TNF-α or IL-6 was added individually to the models. No significant changes in the β-coefficients for RA were noted when diabetes mellitus, tricyclic antidepressant use, serotonin reuptake inhibitor or neuroleptic use was added individually to the models.
Adjusted associations between RA and pain threshold and pain tolerance
The β-coefficients for the association between RA and pain threshold and pain tolerance at the wrists and knees decreased by > 20% when pain catastrophizing was added to the models suggesting that pain catastrophizing may mediate or confound these relationships (Table 2). The β-coefficient for the association between RA and left wrist pain threshold increased by > 20% when the MOS sleep problems score was added to the model, and the β-coefficient for the association between RA and left knee threshold increased by >20% when the HADS anxiety score was added to the model. No changes in the β-coefficients for RA were noted when the HADS depression score, swollen joint count, CRP, TNF-α or IL-6 was added individually to models assessing the association between RA and pain threshold and tolerance at the wrists and knees.
Mediation analyses
Mediation analyses were conducted for the association between RA and CPM and the association between RA and wrist and knee pain threshold and tolerance. All three Baron and Kenny criteria were satisfied for sleep problems as a mediator of the association between RA and CPM: 1) RA was significantly associated with CPM (P = 0.04) (Figure 2A), 2) RA was significantly associated with the MOS sleep problems index II (P < 0.0001) and 3) the MOS sleep problems index II was significantly associated with CPM, adjusted for RA (P = 0.03) (Table 3, Figure 2B). According to the Sobel test, the association between RA and CPM was significantly reduced by inclusion of the MOS sleep problems index II in the model (β = − 0.59 vs. −0.19, P = 0.04) (Figure 2A and 2B). Based on the bootstrapping approach, the 95% confidence interval for the indirect effect of RA on CPM, mediated by sleep problems, did not overlap with zero (Table 3).
Figure 2.
A. Unadjusted association between RA and conditioned pain modulation (Baron and Kenny criterion #1). B. Mediation analyses showing1) the association between RA and conditioned pain modulation, adjusted for sleep problems and 2) the associations between RA and sleep problems (Baron and Kenny criterion #2) and sleep problems and conditioned pain modulation, adjusted for RA (Baron and Kenny criterion 3#).
Table 3.
Baron and Kenny, Sobel and bootstrapping analyses for sleep disturbances as a mediator of the association between RA and QST outcomes.†
| QST Measure | Baron and Kenny Criteria |
Sobel’s Test (P) |
Boot-strapping (95% CI for the indirect effect of RA on QST measures, through sleep) |
||
|---|---|---|---|---|---|
| Association between RA and QST (P) |
Association between RA and sleep problems (P) |
Association between sleep problems and QST, adjusted for RA (P) |
|||
| Central Pain Measure |
|||||
| CPM | 0.04 | <0.0001 | 0.03 | 0.04 | −0.74, −0.04 |
| Pain Threshold | |||||
| Left Wrist | 0.05 | <0.0001 | 0.49 | 0.49 | −0.76, 1.22 |
| Right Wrist | 0.03 | <0.0001 | 0.83 | 0.83 | −1.13, 0.83 |
| Left Knee | 0.10 | <0.0001 | 0.63 | 0.63 | −0.67, 0.92 |
| Right Knee | 0.01 | <0.0001 | 0.65 | 0.66 | −0.72, 1.02 |
| Pain Tolerance | |||||
| Left Wrist | 0.02 | <0.0001 | 0.41 | 0.42 | −0.58, 1.04 |
| Right Wrist | 0.02 | <0.0001 | 0.89 | 0.89 | −0.79, 0.77 |
| Left Knee | 0.03 | <0.0001 | 0.98 | 0.98 | −0.78, 0.65 |
| Right Knee | 0.001 | <0.0001 | 0.67 | 0.67 | −0.64, 0.88 |
Each row is a separate model. RA: rheumatoid arthritis, QST: quantitative sensory testing, CPM: conditioned pain modulation.
The Baron and Kenny criteria for pain catastrophizing as a mediator of the relationship between RA and pain threshold and pain tolerance at the wrists and knees were not satisfied. Although RA was significantly associated with pain threshold and pain tolerance and RA was significantly associated with pain catastrophizing, pain catastrophizing was not significantly associated with pain threshold and pain tolerance, adjusted for RA. Neither the Sobel test nor the bootstrapping approach indicated that pain catastrophizing was a mediator of the association between RA and pain threshold and pain tolerance at the wrists and knees.
Interactions
Interaction terms between RA diagnosis and the MOS sleep problems index II and between RA diagnosis and pain catastrophizing were not significantly associated with CPM. The interaction between RA diagnosis and the MOS sleep problems index II was significantly associated with left thumb threshold (P = 0.03), and the interaction between RA diagnosis and pain catastrophizing was significantly associated with right knee threshold (P = 0.04).
Medications
Among RA patients, non-biologic DMARDs were significantly associated with higher pain threshold (P ≤0.05) at the left thumb and right trapezius and pain tolerance (P ≤ 0.05) at bilateral thumbs and trapezius muscles. Non-biologic DMARDs were not significantly associated with CPM or pain threshold and pain tolerance at the wrist and knee. NSAIDs, corticosteroids and biologic DMARDs were not associated with CPM or pain threshold and pain tolerance at any site.
DISCUSSION
In this study, we examined QST measures of central pain among RA patients compared to controls. Our results show that RA patients have attenuated CPM compared to controls, suggesting that descending analgesic mechanisms are impaired. This observation is consistent with studies comparing CPM between other chronic pain populations (e.g., fibromyalgia and osteoarthritis) and healthy controls (19, 20). Functional neuroimaging studies have also identified changes in neural activity in the periaqueductal grey, anterior cingulate cortex and other pain-responsive areas of the brain in response to experimental induction of CPM (21, 22). Together, these studies suggest that a set of common central mechanisms, including impaired CPM, may contribute to numerous chronic pain states. The association between these measures and clinical pain intensity, however, has varied, with some studies showing a significant inverse correlation between CPM and clinical pain measures (23), and other studies showing no association (24).
Only one other study has examined the role of CPM in RA. In contrast to our study, Leffler et al. reported no statistically significant differences in CPM between 21 RA patients and 21 healthy controls (4). The differences in results may reflect differences in statistical power as the present study had over twice as many subjects. Similar to this study, mean CPM levels in the Leffler study were lower (though not at P < 0.05) among RA patients compared to pain-free controls.
Pressure pain threshold and pain tolerance were also lower among RA patients than controls in this study. However, in contrast to previous studies (4, 5), these differences were only significant at joint but not non-joint sites. The stronger association between pain threshold and pain tolerance at joint sites may, in part, be due to peripheral sensitization, resulting from inflammation at joint sites. In animal models, it is well established that peripheral inflammation can sensitize peripheral nerve endings, leading to lower pain thresholds (25). In a previous study, we also reported that serum CRP was significantly associated with pain threshold at the wrist but not at non-joint sites (26). Together, these results provide further support for the relationship between inflammation and peripheral sensitization in RA.
Interaction analyses did not suggest a differential association between either sleep problems or catastrophizing and CPM, depending on RA diagnosis. Although the P-values for the association between: 1) RA diagnosis by MOS sleep problems index II and left thumb threshold and 2) RA diagnosis by pain catastrophizing and right knee threshold were both < 0.05, the clinical significance of these associations is unclear since these interactions were performed ad hoc, and interactions at other sites were not significant. Statistical significance may have been a by-product of multiple comparisons. Future analyses are needed to replicate these results.
The association between RA and CPM was greatly attenuated when sleep problems were included as a covariate in the multivariable model. This observation suggested that sleep problems may confound or mediate the relationship between RA and CPM. Mediation analyses, including fulfillment of the Baron and Kenny criteria, the Sobel test and confidence intervals from the nonparametric bootstrapping approach, all indicated that the indirect effect of RA on CPM through sleep problems (e.g., the effect that occurred due to sleep problems, rather than the direct effect of RA itself on CPM) was statistically significant.
In the proposed mediation pathway (Figure 2B), RA is associated with lower CPM because" 1) RA patients have more sleep problems, and 2) sleep problems lead to impaired CPM. Sleep disturbances are more common among RA patients than the general population (27), occurring in 50–70% of RA patients (28). Although no studies have examined the association between sleep fragmentation and CPM among RA patients, studies of temperomandibular joint disorder suggest that sleep disturbances are cross-sectionally associated with experimental pain sensitivity (29) and prospectively associated with clinical pain severity (30). In addition, studies of healthy adults and adults with temperomandibular joint disorder indicate that sleep fragmentation is significantly associated with decreases in CPM (24, 31).
The relationship between sleep problems and pain, however, is complex. While sleep problems appear to mediate the association between RA and CPM, other variables, such as pain itself, may factor into this relationship. Given that control subjects were excluded if they reported chronic pain, cases and controls differed in the pain experience. A study of 106 RA patients reported that pain significantly contributes to sleep problems (32). Thus, the appearance of mediation by sleep may actually be the result of mediation by chronic pain, as both may be on the same causal pathway. However, because pain was an exclusion criterion for the controls, it was not possible to assess pain as a confounder or mediator in these analyses. Analyses stratified by clinical pain intensity in the RA group did not suggest differences in the mediating effect of sleep problems on CPM.
While sleep problems altered the strength of association between RA and CPM, pain catastrophizing diminished the association between RA and pain threshold and pain tolerance at the wrists and knees. However, mediation analyses did not support the role of pain catastrophizing as a mediator of the relationship between RA and pain threshold or pain tolerance. The associations between pain catastrophizing and pain threshold and pain tolerance were not significant after adjusting for RA, suggesting that pain catastrophizing may be collinear with other factors associated with RA diagnosis. Alternatively, the lack of significance in these tests may be due to the small sample size, limited distribution of pain catastrophizing scores and/or asymmetric distributions of the indirect effect of RA on pain threshold and tolerance.
Although no studies have examined the association between pain catastrophizing and either CPM or pain threshold and pain tolerance in RA, pain catastrophizing has been associated with high self-reported pain severity among RA patients (33, 34). Pain catastrophizing is also inversely associated with pressure pain threshold and pressure pain tolerance in patients with fibromyalgia and osteoarthritis (35–38). Future studies are needed to elucidate the role of pain catastrophizing in the processing and ultimate expression of pain in RA.
This study has several limitations. First, the cross-sectional design makes it impossible to assess causality. Because the distinction between confounding and mediation is based on a presumed causal relationship among variables, this study cannot distinguish between confounding and mediation, even though the results of mediation analyses were statistically significant (39, 40). In studies of other populations (e.g., patients status post knee arthroscopy), a causal relationship between sleep problems and pain has been suggested based on improvements in pain after treatment of sleep disturbances (41, 42). In future studies, it will be important to assess whether interventions that improve sleep in RA patients “normalize” CPM measures. Larger, longitudinal studies examining the interplay between pain, mental health, sleep problems, CPM, pain threshold and pain tolerance are also needed to understand how these factors interact in shaping CNS processing of pain-related information in RA.
Other potential limitations include confounding by medications. Although we excluded individuals taking opioids, participants could continue to take other medications that may alter CPM, pain threshold and pain tolerance. NSAIDs, corticosteroids, and DMARDs were used almost exclusively by RA patients and may be the cause of differences in CPM, pain threshold and pain tolerance between RA patients and controls. However, among RA patients, none of these medications, except non-biologic DMARDs, were significantly associated with CPM,pain threshold or pain tolerance. Non-biologic DMARDs were associated with high pain threshold and pain tolerance at the thumb and trapezius, but these associations were in the opposite direction of what would be expected if non-biologic DMARDs were a proxy for RA diagnosis. Future studies are needed to examine the effect of medications on central pain mechanisms.
Finally, it is possible that the use of large cotton gloves to blind the assessor to RA vs. control status altered pain testing results. In a pilot study of eight healthy women, the median difference in pain threshold between participants wearing and not wearing gloves was 0.30 kg/cm2, indicating that gloves do not significantly alter pain thresholds in healthy controls. In a separate study of eight women with RA, the median difference in pain threshold was 0.74 kg/cm2. These results suggest that, if anything, gloves increase pain thresholds in RA patients compared to controls, biasing results towards the null. Thus, the use of gloves, which was necessary for blinding, may have decreased our power, but there was no evidence that they confounded the analysis of group differences in CPM (which did not involve a gloved site) or produced spurious findings.
In conclusion, RA patients had lower CPM and lower pressure pain threshold and pressure pain tolerance at joint sites compared to pain-free controls. The association between RA and diminished CPM may be mediated by sleep problems. These results highlight the importance of considering central pain mechanisms when evaluating and addressing pain in chronic inflammatory diseases, such as RA. Future studies are needed to examine whether improving sleep and managing pain catastrophizing may prevent or reverse the development of abnormal pain mechanisms and ultimately improve pain control in RA. Functional neuroimaging studies may also be illuminating, as several recent functional magnetic resonance imaging studies have investigated the neural underpinnings of CPM (22, 43).
Acknowledgments
Grants/Financial interests: YCL is funded by the NIH (AR 057578). RRE is supported by the NIH (AG034982 and AR057920). DHS receives salary support from the NIH (AR 055989). EWK is supported by the NIH (AR49880, AR047782 and AR052403). This work was conducted with support from Harvard Catalyst | The Harvard Clinical and Translational Science Center (National Center for Research Resources and the National Center for Advancing Translational Sciences, National Institutes of Health Award #UL1 RR 025758 and financial contributions from Harvard University and its affiliated academic health care centers). The content is solely the responsibility of the authors and does not necessarily represent the official views of Harvard Catalyst, Harvard University and its affiliated academic health care centers, or the National Institutes of Health. YCL has stock in Merck, Novartis and Elan Corporation. She also receives research funding from Forest Research Institute. DJC has acted as a consultant for Jazz Pharmaceuticals, Pfizer, Lilly, Forest Laboratories, Pierre Fabre, UCB, Nuvo and Merck and Company, Inc. DJC has also received grant support from Pfizer, Nuvo and Forest Laboratories. DHS has received research grants from Amgen, Abbott and Lilly and is an unpaid member of committees overseeing pain-medication trials sponsored by Pfizer.
References
- 1.Lee YC, Cui J, Lu B, Frits ML, Iannaccone CK, Shadick NA, et al. Pain persists in DAS28 rheumatoid arthritis remission but not in ACR/EULAR remission: a longitudinal observational study. Arthritis Res Ther. 2011;13(3):R83. doi: 10.1186/ar3353. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Huskisson EC, Hart FD. Pain threshold and arthritis. Br Med J. 1972;4(5834):193–195. doi: 10.1136/bmj.4.5834.193. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Gerecz-Simon EM, Tunks ER, Heale JA, Kean WF, Buchanan WW. Measurement of pain threshold in patients with rheumatoid arthritis, osteoarthritis, ankylosing spondylitis, and healthy controls. Clin Rheumatol. 1989;8(4):467–474. doi: 10.1007/BF02032098. [DOI] [PubMed] [Google Scholar]
- 4.Leffler AS, Kosek E, Lerndal T, Nordmark B, Hansson P. Somatosensory perception and function of diffuse noxious inhibitory controls (DNIC) in patients suffering from rheumatoid arthritis. European Journal of Pain: Ejp. 2002;6(2):161–176. doi: 10.1053/eujp.2001.0313. [DOI] [PubMed] [Google Scholar]
- 5.Edwards RR, Wasan AD, Bingham CO, 3rd, Bathon J, Haythornthwaite JA, Smith MT, et al. Enhanced reactivity to pain in patients with rheumatoid arthritis. Arthritis Res Ther. 2009;11(3):R61. doi: 10.1186/ar2684. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Millan MJ. Descending control of pain. Prog Neurobiol. 2002;66(6):355–474. doi: 10.1016/s0301-0082(02)00009-6. [DOI] [PubMed] [Google Scholar]
- 7.Lee YC, Nassikas NJ, Clauw DJ. The role of the central nervous system in the generation and maintenance of chronic pain in rheumatoid arthritis, osteoarthritis and fibromyalgia. Arthritis Res Ther. 2011;13(2):211. doi: 10.1186/ar3306. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.van Wijk G, Veldhuijzen DS. Perspective on diffuse noxious inhibitory controls as a model of endogenous pain modulation in clinical pain syndromes. J Pain. 2010;11(5):408–419. doi: 10.1016/j.jpain.2009.10.009. [DOI] [PubMed] [Google Scholar]
- 9.Van Riel PL. The Home of the DAS. [Google Scholar]
- 10.Bjelland I, Dahl AA, Haug TT, Neckelmann D. The validity of the Hospital Anxiety and Depression Scale. An updated literature review. J Psychosom Res. 2002;52(2):69–77. doi: 10.1016/s0022-3999(01)00296-3. [DOI] [PubMed] [Google Scholar]
- 11.Hays RD, Stewart AL. Sleep Measures. In: Ware ALSaJE., editor. Measuring functioning and well-being: The Medical Outcomes Study approach. Durham, NC: Durham University Press; 1992. pp. 235–259. [Google Scholar]
- 12.Sullivan MJL, Bishop SR, Pivik J. The Pain Catastrophizing Scale: development and validation. Psychol Assess. 1995;7:524–532. [Google Scholar]
- 13.Lee YC, Chibnik LB, Fossel AH, Solomon DH, Clauw DJ, Karlson EW. The reproducibility of presure pain thresholds in RA patients. American College of Rheumatology Annual Scientific Meeting; October 2008; San Francisco, CA. 2008. 2008. [Google Scholar]
- 14.Wilder-Smith OH, Schreyer T, Scheffer GJ, Arendt-Nielsen L. Patients with chronic pain after abdominal surgery show less preoperative endogenous pain inhibition and more postoperative hyperalgesia: a pilot study. J Pain Palliat Care Pharmacother. 2010;24(2):119–128. doi: 10.3109/15360281003706069. [DOI] [PubMed] [Google Scholar]
- 15.Goodin BR, McGuire L, Allshouse M, Stapleton L, Haythornthwaite JA, Burns N, et al. Associations between catastrophizing and endogenous pain-inhibitory processes: sex differences. J Pain. 2009;10(2):180–190. doi: 10.1016/j.jpain.2008.08.012. [DOI] [PubMed] [Google Scholar]
- 16.Lariviere M, Goffaux P, Marchand S, Julien N. Changes in pain perception and descending inhibitory controls start at middle age in healthy adults. Clin J Pain. 2007;23(6):506–510. doi: 10.1097/AJP.0b013e31806a23e8. [DOI] [PubMed] [Google Scholar]
- 17.Baron RM, Kenny DA. The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. J Pers Soc Psychol. 1986;51(6):1173–1182. doi: 10.1037//0022-3514.51.6.1173. [DOI] [PubMed] [Google Scholar]
- 18.Preacher KJ, Hayes AF. SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behav Res Methods Instrum Comput. 2004;36(4):717–731. doi: 10.3758/bf03206553. [DOI] [PubMed] [Google Scholar]
- 19.Normand E, Potvin S, Gaumond I, Cloutier G, Corbin JF, Marchand S. Pain inhibition is deficient in chronic widespread pain but normal in major depressive disorder. J Clin Psychiatry. 2011;72(2):219–224. doi: 10.4088/JCP.08m04969blu. [DOI] [PubMed] [Google Scholar]
- 20.Arendt-Nielsen L, Nie H, Laursen MB, Laursen BS, Madeleine P, Simonsen OH, et al. Sensitization in patients with painful knee osteoarthritis. Pain. 2010 doi: 10.1016/j.pain.2010.04.003. [DOI] [PubMed] [Google Scholar]
- 21.Derbyshire SW, Osborn J. Offset analgesia is mediated by activation in the region of the periaqueductal grey and rostral ventromedial medulla. Neuroimage. 2009;47(3):1002–1006. doi: 10.1016/j.neuroimage.2009.04.032. [DOI] [PubMed] [Google Scholar]
- 22.Sprenger C, Bingel U, Buchel C. Treating pain with pain: supraspinal mechanisms of endogenous analgesia elicited by heterotopic noxious conditioning stimulation. Pain. 2011;152(2):428–439. doi: 10.1016/j.pain.2010.11.018. [DOI] [PubMed] [Google Scholar]
- 23.Edwards RR, Ness TJ, Weigent DA, Fillingim RB. Individual differences in diffuse noxious inhibitory controls (DNIC) association with clinical variables. Pain. 2003;106(3):427–437. doi: 10.1016/j.pain.2003.09.005. [DOI] [PubMed] [Google Scholar]
- 24.Edwards RR, Grace E, Peterson S, Klick B, Haythornthwaite JA, Smith MT. Sleep continuity and architecture: Associations with pain-inhibitory processes in patients with temporomandibular joint disorder. Eur J Pain. 2009 doi: 10.1016/j.ejpain.2008.12.007. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Schaible HG, Ebersberger A, Von Banchet GS. Mechanisms of pain in arthritis. Ann N Y Acad Sci. 2002;966:343–354. doi: 10.1111/j.1749-6632.2002.tb04234.x. [DOI] [PubMed] [Google Scholar]
- 26.Lee YC, Chibnik LB, Lu B, Wasan AD, Edwards RR, Fossel AH, et al. The relationship between disease activity, sleep, psychiatric distress and pain sensitivity in rheumatoid arthritis: a cross-sectional study. Arthritis Res Ther. 2009;11(5):R160. doi: 10.1186/ar2842. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Clegg DO, Reda DJ, Harris CL, Klein MA, O'Dell JR, Hooper MM, et al. Glucosamine, chondroitin sulfate, and the two in combination for painful knee osteoarthritis. N Engl J Med. 2006;354(8):795–808. doi: 10.1056/NEJMoa052771. [DOI] [PubMed] [Google Scholar]
- 28.Abad VC, Sarinas PS, Guilleminault C. Sleep and rheumatologic disorders. Sleep Med Rev. 2008;12(3):211–228. doi: 10.1016/j.smrv.2007.09.001. [DOI] [PubMed] [Google Scholar]
- 29.Smith MT, Wickwire EM, Grace EG, Edwards RR, Buenaver LF, Peterson S, et al. Sleep disorders and their association with laboratory pain sensitivity in temporomandibular joint disorder. Sleep. 2009;32(6):779–790. doi: 10.1093/sleep/32.6.779. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Quartana PJ, Wickwire EM, Klick B, Grace E, Smith MT. Naturalistic changes in insomnia symptoms and pain in temporomandibular joint disorder: a cross-lagged panel analysis. Pain. 2010;149(2):325–331. doi: 10.1016/j.pain.2010.02.029. [DOI] [PubMed] [Google Scholar]
- 31.Smith MT, Edwards RR, McCann UD, Haythornthwaite JA. The effects of sleep deprivation on pain inhibition and spontaneous pain in women. Sleep. 2007;30(4):494–505. doi: 10.1093/sleep/30.4.494. [DOI] [PubMed] [Google Scholar]
- 32.Nicassio PM, Ormseth SR, Kay M, Custodio M, Irwin MR, Olmstead R, et al. The contribution of pain and depression to self-reported sleep disturbance in patients with rheumatoid arthritis. Pain. 2012;153(1):107–112. doi: 10.1016/j.pain.2011.09.024. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Covic T, Adamson B, Spencer D, Howe G. A biopsychosocial model of pain and depression in rheumatoid arthritis: a 12-month longitudinal study. Rheumatology (Oxford) 2003;42(11):1287–1294. doi: 10.1093/rheumatology/keg369. Epub 2003 Jun 16. [DOI] [PubMed] [Google Scholar]
- 34.Edwards RR, Giles J, Bingham CO, 3rd, Campbell C, Haythornthwaite JA, Bathon J. Moderators of the negative effects of catastrophizing in arthritis. Pain Med. 2010;11(4):591–599. doi: 10.1111/j.1526-4637.2010.00804.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Edwards RR, Cahalan C, Mensing G, Smith M, Haythornthwaite JA. Pain, catastrophizing, and depression in the rheumatic diseases. Nat Rev Rheumatol. 2011;7(4):216–224. doi: 10.1038/nrrheum.2011.2. [DOI] [PubMed] [Google Scholar]
- 36.Geisser ME, Casey KL, Brucksch CB, Ribbens CM, Appleton BB, Crofford LJ. Perception of noxious and innocuous heat stimulation among healthy women and women with fibromyalgia: association with mood, somatic focus, and catastrophizing. Pain. 2003;102(3):243–250. doi: 10.1016/S0304-3959(02)00417-7. [DOI] [PubMed] [Google Scholar]
- 37.France CR, Keefe FJ, Emery CF, Affleck G, France JL, Waters S, et al. Laboratory pain perception and clinical pain in post-menopausal women and age-matched men with osteoarthritis: relationship to pain coping and hormonal status. Pain. 2004;112(3):274–281. doi: 10.1016/j.pain.2004.09.007. [DOI] [PubMed] [Google Scholar]
- 38.Campbell CM, Kronfli T, Buenaver LF, Smith MT, Berna C, Haythornthwaite JA, et al. Situational versus dispositional measurement of catastrophizing: associations with pain responses in multiple samples. J Pain. 2010;11(5):443–453. doi: 10.1016/j.jpain.2009.08.009. e2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.MacKinnon DP, Krull JL, Lockwood CM. Equivalence of the mediation, confounding and suppression effect. Prev Sci. 2000;1(4):173–181. doi: 10.1023/a:1026595011371. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Babyak MA. Understanding confounding and mediation. Evid Based Ment Health. 2009;12(3):68–71. doi: 10.1136/ebmh.12.3.68. [DOI] [PubMed] [Google Scholar]
- 41.Tashjian RZ, Banerjee R, Bradley MP, Alford W, Fadale PD. Zolpidem reduces postoperative pain, fatigue, and narcotic consumption following knee arthroscopy: a prospective randomized placebo-controlled double-blinded study. J Knee Surg. 2006;19(2):105–111. doi: 10.1055/s-0030-1248088. [DOI] [PubMed] [Google Scholar]
- 42.Tompkins M, Plante M, Monchik K, Fleming B, Fadale P. The use of a non-benzodiazepine hypnotic sleep-aid (Zolpidem) in patients undergoing ACL reconstruction: a randomized controlled clinical trial. Knee Surg Sports Traumatol Arthrosc. 2011;19(5):787–791. doi: 10.1007/s00167-010-1368-x. [DOI] [PubMed] [Google Scholar]
- 43.Piche M, Arsenault M, Rainville P. Cerebral and cerebrospinal processes underlying counterirritation analgesia. J Neurosci. 2009;29(45):14236–14246. doi: 10.1523/JNEUROSCI.2341-09.2009. [DOI] [PMC free article] [PubMed] [Google Scholar]