Abstract
Objective
To examine the association of socioeconomic status (SES) and delays in DMARD treatment with clinical measures in rheumatoid arthritis (RA) patients.
Methods
RA patients were recruited from rheumatology clinics. We assessed SES based on education, occupation and income and divided patients into tertiles. The time from RA symptom onset to DMARD initiation (DMARD lag) was determined by self-report of the two dates, and distance to the rheumatologist (Distance) was obtained from Google Maps. We examined disease activity, determined by DAS28ESR, joint damage, determined from hand radiographs by Sharp scores, and physical disability, determined by the Modified Health Assessment Questionnaire (MHAQ). We used linear regression models to examine the relationship between clinical measures and SES, Distance, and DMARD lag.
Results
We recruited 1,209 RA patients, 1159 of whom had received DMARD treatment. Average ± SD DMARD lag was 6.9 ± 9.0 years. On average, patients with lower SES waited 8.5 ± 10.2 years after onset of RA symptoms to begin DMARD treatment, compared to those in middle and upper SES tertiles who waited 6.1 ± 7.9 years (P=0.002) and 6.1 ± 8.6 years (P=0.009), respectively. Each year of delayed treatment was associated with a DAS28ESR increase of 0.02 (P≤0.001), a Sharp score increase of 1.33 (P≤0.001) and MHAQ score increase of 0.01 (P≤0.001).
Conclusion
Low SES was associated with delay in DMARD initiation, and both were independently associated with worse clinical measures in RA. Strategies to reduce treatment delay in low SES RA patients are needed.
Introduction
Rheumatoid arthritis (RA) is an autoimmune inflammatory disease that affects approximately 1% of adults in industrialized countries, most commonly affecting women.1 The incidence and prevalence increases with age.1 It is a debilitating disease that causes joint damage, increased risk for cardiovascular disease and other comorbidities. Several studies have shown that early treatment is critical for optimal care in these patients.2-5 In fact, the idea that a “window of opportunity” in the early stages of disease exists for ideal treatment and prevention of irreversible damage is gaining momentum in RA as well as other autoimmune diseases.6–9
There are many different variables implicated in delayed treatment by a rheumatologist. Notably, lengthy doctors’ wait times,10,11 time to referral to a rheumatologist,12 lower SES,13 as well as living in rural areas11 have all been shown to delay treatment of arthritis patients. In general, a greater distance to a provider has been correlated with lower usage of health services.14,15 Interestingly, in breast cancer patients, a shorter distance to mammography facility has been correlated with earlier stage diagnoses of cancer,16 which is crucial because, similar to RA patients, earlier treatment can lead to better outcomes.17,18 Given the importance of prompt initiation of disease-modifying antirheumatic drug (DMARD) treatment and appropriate follow-up visits of RA patients, we sought to examine the relationship between SES and disease activity, joint damage and disability, taking into account factors such as treatment delay and distance to the rheumatologist.
Methods
Patients
From 1996 to 2009, we recruited consecutive patients who met the 1987 criteria for RA19 from private, military and public rheumatology outpatient clinics in San Antonio, Texas. We have described this cohort in previous publications.20–22 All patients participated in a comprehensive baseline evaluation of their clinical and psychosocial characteristics conducted by a physician and trained research assistants.
Demographics
A trained interviewer asked patients for their date and place of birth, sex and race/ethnicity. For the latter, the interviewer asked patients to self-identify as “white,” “black,” “Asian,” “Hispanic,” or “other.”
Socioeconomic Status
We classified socioeconomic status (SES) according to Nam and Powers, using years of formal education, inflation-adjusted monthly household income, and current or past occupation to calculate an SES score on an ascending scale between 0 and 100.23
Lag Times
A trained interviewer asked patients at what age or in what year the patient began having painful joints, became diagnosed with RA, and first saw a rheumatologist. During the baseline visit, we asked patients which DMARDs they had taken previously and were taking at the time of the evaluation, as well as the approximate date these were first prescribed. Using these dates we measured four different lag times, measured in years: time between onset of joint pain and diagnosis date; time between onset of joint pain and beginning treatment with DMARDs; time between diagnosis date and beginning treatment with DMARDs; and time between diagnosis date and first rheumatologist visit. For these analyses, we used time between symptom onset and DMARD initiation (DMARD lag).
Measuring Distance to the Rheumatologist
We obtained the driving distance from the patient's home address to where they received their rheumatologic care (Distance) using Google Maps, choosing the shortest distance when multiple routes were possible. We did not account for public transportation. Zip code centroids were used to calculate distance for five participants that gave an address that could not be found by Google Maps.
Physical Disability
Physical disability was measured using the Modified Health Assessment Questionnaire (MHAQ), a self-administered, arthritis-specific survey that asks participants to rate the amount of difficulty they have performing 8 activities (dressing, getting out of bed, lifting a cup, walking, bathing, bending, turning faucets, and getting in and out of a car) on a scale ranging from 1 to 4 (without difficulty, with some, with much, and unable).24
Clinical Features
Disease duration
We defined RA duration as the interval between the date of RA diagnosis and time of the study visit.
Disease activity
For the assessment of disease activity, we used the Disease Activity Score (DAS) in 28 joints. At each visit, we assessed 28 joints for tenderness or pain on motion and swelling.25 In addition to tenderness and swelling in 28 joints, we measured the Westergren erythrocyte sedimentation rate at each visit. We used these three variables to calculate the Disease Activity Score in 28 joints (DAS28ESR).26
Joint findings
A physician examined 48 joints for tenderness or pain on motion, swelling or deformity, and for the presence of extra-articular subcutaneous nodules.24 Joint exam Spearman-Brown reliability coefficients are 0.94 for tender/pain on motion, 0.90 for swelling and 0.98 for deformity.27 In these analyses we used the 28 joints included in the DAS28ESR.
Hand radiographs
We quantified joint damage on a plain X-ray view of both hands and wrists according to Sharp and colleagues.28 In this study, all X-ray radiographs were scored by one rater (JFR).
Statistical Analysis
Both the Sharp score and the distance data showed skewed distributions. In order to normalize these, a square root transformation was applied to the Sharp score and the natural logarithm transformation was applied to the distance.
Linear regression models were used to compare clinical characteristics of RA across SES strata. We examined differences in disease activity, radiologic damage and physical disability across SES and DMARD lag tertiles, and adjusted for age, sex, duration of the disease and Distance. We assessed the effects of SES and these confounders on the association between DMARD lag and clinical measures. We further conducted a series of linear regression models examining these measures across SES strata within each DMARD lag tertile. Models were tested for co-linearity using variance inflation factor. All analyses were conducted using a desktop personal computer with the Stata statistical software package, version 9.0 (College Station, TX).
Results
There were a total of 1,328 participants recruited between 1996 and 2009. However, radiographs were unavailable for scoring from 117, and the ESR unavailable from 2 for a final sample size of 1,209 RA patients. Patients were recruited from four different health systems: 476 from the University Health System, Bexar County's public health system; 121 from the Veterans Affairs (VA) health system; 228 from the San Antonio military health systems; and 384 from independent rheumatology private practices.
Patients recruited from Bexar County's public health system were more likely to be younger, Hispanic, and have shorter Distance and lower SES scores compared to all three other health systems (P≤0.001). Military patients were most likely to be taking a DMARD at baseline, and patients from the VA were most likely to be taking corticosteroids. After adjusting for age, sex and ethnicity, patients from the military and private health systems had the highest SES scores and shortest DMARD lag compared to patients from the VA and public health systems. Hispanics had significantly worse DAS28ESR and MHAQ, independent of health system and SES. However, there was no association between ethnicity and Sharp score in any of the unadjusted and adjusted models.
Although DMARD lag did not vary according to Distance, all three clinical measures were inversely associated with Distance. We tested models adjusting for age, sex, ethnicity, duration of RA and SES, and found that the associations between Distance and DAS28ESR and MHAQ lost statistical significance after adjusting for SES.
We stratified the Nam & Powers SES score into three tertiles, lower, middle and upper, to examine its association with barriers to care and clinical measures. The ranges in Nam & Powers scores for each of these categories are 5 to 42, 43 to 62, and 63 to 95, respectively. After adjusting for age, sex, ethnicity and duration of RA, patients in the lower SES tertile showed significantly worse scores on all three clinical measures (Table 1). In each of these models, we tested for SES x Health System interactions and none were significant. Furthermore, patients in the lower SES tertile experienced significantly greater lag times between onset of symptoms to RA diagnoses, RA diagnoses to treatment with DMARDs, and RA diagnoses to first rheumatologist visit when compared to middle and upper classes. On average, patients in the lower SES tertile waited 8.5 ± 10.2 years after onset of RA symptoms to begin DMARD treatment, compared to those in middle and upper SES tertiles who waited 6.1 ± 7.9 years (P=0.002) and 6.1 ± 8.6 years (P=0.009), respectively (Table 1). Moreover, patients in the lower SES tertile waited almost one year longer to visit a rheumatologist than those in the upper SES tertile (Table 1). We subsequently examined the association between DMARD lag and clinical measures by stratifying DMARD lag into tertiles. After adjusting for age, sex and ethnicity, patients with the greatest DMARD lag showed greater DAS28ESR (P≤0.001), Sharp score (P≤0.001) and MHAQ (P≤0.001) (Table 2).
Table 1.
Characteristics of rheumatoid arthritis cohort, according to SES tertile (n=1209)
| Socioeconomic Status (Range) | |||
|---|---|---|---|
| Lower (5 – 42) n=406 | Middle (43 – 62) n=410 | Upper (63 – 95) n=393 | |
| Demographics | |||
| Age, median (range) years | 58 (21 - 87) | 57 (19 - 89) | 59 (23 - 83) |
| Women, n (%) | 326 (80.2)§ | 322 (78.5)§ | 268 (68.2) |
| Hispanic, n (%) | 338 (83.3)§ | 263 (64.1)§ | 131 (33.3) |
| RA Duration, mean (SD) years | 9.4 (10.2)† | 10.9 (10.1) | 11.9 (10.3) |
| Distance, mean (SD) miles | 18.8 (43.4)§ | 31.7 (54.3) | 29.0 (46.2) |
| Health System, n (%) | |||
| Bexar County (n=476) | 271 (66.7)§ | 161 (39.3)§ | 44 (11.2) |
| Veterans Affairs (n=121) | 25 (6.2) | 46 (11.2) | 50 (12.7) |
| Military (n=228) | 23 (5.7)§ | 79 (19.3)† | 126 (32.1) |
| Private (n=384) | 87 (21.4)§ | 124 (30.2)§ | 173 (44.0) |
| Lag Times in years mean ± SD | |||
| Symptoms to Diagnosis | 4.6 ± 7.8 | 3.1 ± 6.3 | 3.4 ± 6.5 |
| Symptoms to DMARDs* | 8.5 ± 10.2§ | 6.1 ± 7.9 | 6.2 ± 8.6 |
| Diagnosis to DMARDs* | 4.0 ± 7.3§ | 3.2 ± 5.5 | 2.7 ± 5.6 |
| Diagnosis to first Rheumatologist visit** | 1.8 ± 5.2§ | 1.2 ± 3.9 | 0.9 ± 3.6 |
| Medications at baseline, n (%) | |||
| On any DMARD | 321 (79) | 331 (81) | 325 (83) |
| On methotrexate | 254 (63) | 239 (58) | 226 (57) |
| On anti-TNF DMARD | 49 (12)§ | 68 (17)‡ | 100 (25) |
| On corticosteroids | 176 (43)† | 159 (39) | 144 (37) |
| Clinical Measures, mean ± SD | |||
| DAS28ESR | 4.99 ± 1.7§ | 4.37 ± 1.6§ | 3.49 ± 1.6 |
| Sharp Score | 50.2 ± 62.0§ | 48.0 ± 60.8§ | 41.8 ± 57.9 |
| MHAQ Score | 2.06 ± 0.70§ | 1.75 ± 0.60§ | 1.48 ± 0.48 |
Of 1209 patients, 50 had not begun DMARDs by the time of baseline evaluation, and thus were not included in these analyses. These patients were distributed as follows: 24 from the lower SES tertile, 14 from the middle SES tertile and 12 from the upper SES tertile.
Of 1209 patients, 2 had not previously seen a rheumatologist by the time of baseline evaluation and thus were not included in these analyses. One of these was from the lower and the other from the middle SES tertile.
P ≤ 0.05 versus upper SES tertile after adjusting for age, sex, duration, ethnicity, and Distance
P ≤ 0.01 versus upper SES tertile after adjusting for age, sex, duration, ethnicity, and Distance
P ≤ 0.001 versus upper SES tertile after adjusting for age, sex, duration, ethnicity, and Distance
Table 2.
Clinical measures according to DMARD lag tertile (n=1159)
| Shortest Lag 0 – 1.33 yrs. (n=387) | Intermediate Lag 1.34 – 6.62 yrs. (n=386) | Highest Lag 6.63 – 50.6 yrs. (n=386) | |
|---|---|---|---|
| DAS28ESR mean ± SD | 4.05 ± 1.8 | 4.25 ± 1.8 | 4.50 ± 1.6§ |
| Sharp Score mean ± SD | 30.1 ± 46.4 | 48.8 ± 59.6§ | 62.6 ± 68.9‡ |
| MHAQ mean ± SD | 1.64 ± 0.64 | 1.72 ± 0.65 | 1.90 ± 0.63§ |
† P ≤ 0.05 versus shortest lag tertile after adjusting for age, sex, duration, ethnicity and Distance
P ≤ 0.01 versus shortest lag tertile after adjusting for age, sex, duration, ethnicity and Distance
P ≤ 0.001 versus shortest lag tertile after adjusting for age, sex, duration, ethnicity and Distance
In models that included both the DMARD lag and SES variables, both were significantly associated with all three clinical measures (Table 3). We found no evidence of co-linearity in any of the models. The gradient across SES strata was maintained in all three DMARD categories for the DAS28ESR and MHAQ, but not for the Sharp scores (Table 4).
Table 3.
Multivariable associations of SES and DMARD lag on DAS28ESR, Sharp Score, and MHAQ (n=1159)*
| SES† | DMARD Lag‡ | |||
|---|---|---|---|---|
| Unadjusted | Adjusted | Unadjusted | Adjusted | |
| DAS28ESR | −0.32 (−0.36, −0.27) | −0.26 (−0.32, −0.20) | 0.06 (0.01, 0.1) | 0.08 (0.02, 0.13) |
| P-value | ≤0.001 | ≤0.001 | 0.021 | 0.004 |
| Sharp Score | −0.10 (−0.22, 0.01) | −0.14 (−0.28, −0.01) | 0.47 (0.35, 0.60) | 0.38 (0.25, 0.50) |
| P-value | 0.1 | 0.038 | ≤0.001 | ≤0.001 |
| MHAQ | −0.12 (−0.13, −0.10) | −0. 10 (−0.11, −0.08) | 0.05 (0.02, 0.06) | 0.06 (0.036, 0.074) |
| P-value | ≤0.001 | ≤0.001 | ≤0.001 | ≤0.001 |
Values shown are linear regression coefficients with 95% confidence intervals (95% CI). All models adjusted for age, sex and ethnicity.
Coefficients are per 10 unit increment in SES scale
Coefficients are per 5 year increment in DMARD lag
Table 4.
Clinical measures stratified according to SES and DMARD Lag tertiles (n=1159).
| DMARD Lag Tertiles |
||||
|---|---|---|---|---|
| SES Tertiles | Shortest Lag 0 – 1.33 yrs. (n=387) | Intermediate Lag 1.34 – 6.62 yrs. (n=386) | Highest Lag 6.63 – 50.6 yrs. (n=386) | |
| DAS28ESR mean ± SD | ||||
| Lower | 4.80 ± 1.9§ | 4.94 ± 1.7§ | 5.07 ± 1.5§ | |
| Middle | 4.33 ± 1.7§ | 4.40 ± 1.6§ | 4.33 ± 1.5 | |
| Upper | 3.28 ± 1.5 | 3.39 ± 1.6 | 3.80 ± 1.6 | |
| Sharp Score mean ± SD | ||||
| Lower | 23.9 ± 35.2 | 54.1 ± 61.6 | 66.2 ± 71.5‡ | |
| Middle | 35.8 ± 52.3‡ | 46.1 ± 58.7 | 65.9 ± 69.2† | |
| Upper | 28.8 ± 46.5 | 46.5 ± 58.6 | 53.9 ± 64.5 | |
| MHAQ mean ± SD | ||||
| Lower | 2.01 ± 0.76§ | 1.98 ± 0.75§ | 2.13 ± 0.63§ | |
| Middle | 1.63 ± 0.59 | 1.71 ± 0.55‡ | 1.89 ± 0.62‡ | |
| Upper | 1.41 ± 0.45 | 1.47 ± 0.51 | 1.58 ± 0.47 | |
P ≤ 0.05 versus upper SES tertile after adjusting for age, sex, duration, ethnicity and Distance
P ≤ 0.01 versus upper SES tertile after adjusting for age, sex, duration, ethnicity and Distance
P ≤ 0.001 versus upper SES tertile after adjusting for age, sex, duration, ethnicity and Distance
Discussion
Early initiation of DMARDs in RA is critical for best outcomes.2-5 A variety of factors may inhibit timely visits to a rheumatologist, including factors such as lower SES13 and living in a rural area.11 In this study we sought to determine the effect of potential health barriers—the distance that a patient has to travel to get to the rheumatologist (Distance) and the delay in treatment of DMARDs (DMARD lag)—and how these interact with SES and clinical measures in RA.
We describe baseline features of 1,209 patients with RA from four different health systems in San Antonio, Texas to determine the impact of Distance, DMARD lag times and SES on clinical measures in RA patients. We found that all three of these factors were independently associated with disease activity, joint damage, and physical disability. Interestingly, Distance was not significantly correlated with DMARD lag, and was inversely associated with these clinical measures, suggesting that patients who live closer to the rheumatologist have more severe RA. This result was unexpected as we had hypothesized that greater Distance would be associated with greater inflammation, joint damage and physical disability due to incurring an additional barrier to care. However, two of these paradoxical associations—both the DAS28ESR, indicating disease activity, and the MHAQ, indicating physical disability—lost their significance after adjustment of SES. This suggests that SES is the underlying cause for worse health status in patients living close to their provider. In our cohort, low SES patients are more likely to receive care from the Bexar County facility, which is located in a low-income area, therefore explaining the inverse relationship between the three clinical measures and Distance. Patients from this facility account for almost 40% of our cohort and thus largely affected our findings. When conducting the same analyses without including the Bexar County patients, we found that a greater Distance was associated with higher DAS28ESR independent of SES, but was not correlated with Sharp scores, MHAQ or DMARD lag.
In a San Francisco SLE cohort that focused on the role of health insurance on access to care, Medicaid patients were found to travel longer distances than those with other types of insurances.29 These patients were also more likely to be seen by a general practitioner instead of a rheumatologist, and had greater number of emergency room visits. However, in the San Francisco study, the authors did not examine health outcomes. In our study, we lacked access to visit frequency, but were able to analyze clinical measures of RA, which suggested that distance to a provider may continue to be a barrier to care for many patients but does not explain poorer clinical status in inner city patients.
Several studies have examined the role of socioeconomic status in the course of RA. Individuals with lower SES may be more susceptible to RA,30,31 more likely to experience worse outcomes in terms of greater inflammation,13,32,33 and physical disability,33,34 and show less frequent utilization of health services.13 Interestingly, in another study analyzing SES by zip code of RA patients, area of residence was related to disease severity at baseline,35 suggesting that SES influences disease expression in RA.
We stratified SES into tertiles and found that the DAS28ESR, Sharp scores and MHAQ were all significantly different across SES strata, despite adjusting for age, sex, ethnicity, duration of RA, Distance and DMARD lag. Furthermore, patients in the lower SES tertile waited, on average, approximately two years more than those in the upper SES tertile to be treated with DMARDs after onset of symptoms (Table 1). Similarly, we stratified DMARD lag into tertiles to assess its association with DAS28ESR, Sharp score and MHAQ. After adjusting for age, sex and ethnicity, experiencing a greater DMARD lag remained significantly correlated with greater inflammation, joint damage and physical disability (Table 2). We subsequently examined models including both SES and DMARD lag and found them both to be associated with greater DAS28ESR, higher Sharp score and worse MHAQ, suggesting that they each independently affect these measures (Table 3). Table 3 shows the coefficients for clinical measures as they relate to scaled SES and DMARD lag variables. For every five years of delay in DMARD treatment, the transformed Sharp score increased by 0.38. Furthermore, for every 10 points on the ascending SES scale, DAS28ESR decreased by 0.26 and MHAQ decreased by 0.1 (Table 3).
By stratifying both SES and DMARD lag into tertiles, we could examine any trends in clinical measures (Table 4). After adjusting for age, sex, and ethnicity, we assessed the role of SES within each DMARD lag tertile. Lower SES patients still experienced greater disease activity and worse physical disability, regardless of DMARD lag (Table 4). According to this table, on average, compared to upper SES, lower SES patients incurred 1.45 greater DAS28ESR and 0.55 greater MHAQ scores across all DMARD lag tertiles. The minimum clinically important difference is approximately 1.2 for DAS28ESR36 and 0.25 for MHAQ.37 This suggests that the associations of these measures with SES are clinically meaningful when examined across SES tertiles, despite the fact that coefficients from Table 3 did not meet these criteria. This suggests that minimal changes in SES may not account for clinically meaningful differences in disease activity or disability, yet the association is still significant and becomes clinically meaningful when comparing lower and upper SES classes.
However, after stratifying DMARD lag, Sharp score did not show a significant correlation with SES (Table 4). Nevertheless, there is a distinct trend towards greater Sharp scores with longer DMARD lag across all SES strata. On average, Sharp score increased by 19.4 between the shortest and intermediate DMARD lag tertiles, and 13.1 between the intermediate and highest DMARD lag tertiles (Table 4). Given that the minimal clinically important difference in the Sharp score is 4.6,38 the delays in treatment that we observed can result in irreversible damage that is clinically important. This result was expected, since joint damage occurs early in RA, and earlier treatment with DMARDs has been shown to improve long-term outcomes and slow progression of joint damage.2-5
Our study of health care barriers as mediators of RA clinical measures has strengths and limitations. A unique strength of this study is that clinical measures were ascertained by a rheumatologist, who conducted individual exams per patient to examine tender and swollen joint counts, as well as obtain and score hand radiographs to determine joint damage. We also have the benefit of a diverse cohort recruited from a variety of health systems and SES strata. Furthermore, our RA cohort is large enough to provide the power to detect small effects. However, we were unable to ascertain method of transportation at time of baseline, so upon calculating distance to the provider we did not account for those who may have relied upon public transportation, which may impose additional barriers to access, such as longer travel times and inconvenient schedules. Additionally, we lacked information on whether patients had moved between the time of RA symptom onset and the time of recruitment into the study. It is possible patients had moved closer to a rheumatology clinic after symptom onset. We were also unable to ascertain the frequency of visits to the rheumatologist, which could influence outcomes.39 Since patients were recruited consecutively, patients with more frequent visits were more likely to be recruited, which may have biased our sample towards greater severity. We cannot account for this bias since we lack data on visit frequency. Nevertheless it should be noted that all patients were recruited at their respective treatment facilities, suggesting that they have the means to access that facility, though we do not know how often they sought treatment. Finally, there is a possibility of bias with patients with longer duration having longer lag time and overestimating duration of symptoms, which could confound the association found between lag time and Sharp score.
We conclude that lower SES patients may incur longer delays in DMARD treatment and in seeing a rheumatologist, resulting in worse clinical measures in RA. Further research is needed to more fully understand the interactions between SES and disease outcomes in RA.
Significance and Innovation.
We examined the association between socioeconomic status (SES), delay in disease-modifying antirheumatic drug (DMARD) initiation, disease activity, joint damage and disability in a large RA cohort. We considered potential barriers to access to care such as the distance to the rheumatologist.
We found that lower SES patients experience longer delay in DMARD initiation, as well as greater disease activity as measured by DAS28ESR, greater joint damage as measured by hand radiographs and worse physical disability as measured by the modified health assessment questionnaire (MHAQ).
Patients who experience a greater delay in DMARD initiation endure a clinically meaningful increase in joint damage.
Acknowledgments
Supported in part by NIH grants R01-HL-085742, R01-HD-037151, and UL1-RR-025767
References
- 1.Scott D, Wolfe F, Huizinga T. Rheumatoid Arthritis. The Lancet. 2010;376:1094–1108. doi: 10.1016/S0140-6736(10)60826-4. [DOI] [PubMed] [Google Scholar]
- 2.Lard LR, Visser H, Speyer I, vander Horst-Bruinsma IE, Zwinderman AH, Breedveld FC, Hazes JM. Early versus delayed treatment in patients with recent-onset rheumatoid arthritis: comparison of two cohorts who received different treatment strategies. Am J Med. 2001;111:446–451. doi: 10.1016/s0002-9343(01)00872-5. [DOI] [PubMed] [Google Scholar]
- 3.Anderson JJ, Wells G, Verhoeven AC, et al. Factors predicting response to treatment in rheumatoid arthritis: the importance of disease duration. Arthritis Rheum. 2000;43:22–9. doi: 10.1002/1529-0131(200001)43:1<22::AID-ANR4>3.0.CO;2-9. [DOI] [PubMed] [Google Scholar]
- 4.Emery P, Breedveld FC, Dougados M, Kalden JR, Schiff MH, Smolen JS. Early referral recommendation for newly diagnosed rheumatoid arthritis: evidence based development of a clinical guide. Ann Rheum Dis. 2002;61:290–297. doi: 10.1136/ard.61.4.290. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Nell VPK, Machold KP, Eberl G, Stamm TA, Uffmann M, Smolen JS. Benefit of very early referral and very early therapy with disease-modifying anti-rheumatic drugs in patients with early rheumatoid arthritis. Rheumatology. 2004;43:906–914. doi: 10.1093/rheumatology/keh199. [DOI] [PubMed] [Google Scholar]
- 6.Furst DE. Window of opportunity. J Rheumatol. 2004;31(9):1677–1679. [PubMed] [Google Scholar]
- 7.O'Dell JR. Treating rheumatoid arthritis early: a window of opportunity? Arthritis Rheum. 2002;46(2):283–285. doi: 10.1002/art.10092. [DOI] [PubMed] [Google Scholar]
- 8.Burska A, Parmar R, El-Sherbiny Y, El Jawhari J, Emery P, Ponchel F. A3.3 An Immunological Window of Opportunity Defines the Ability of Early RA Patient to Achieve Remission with First Anti-Rheumatic Treatment. Ann Rheum Dis. 2013;72(Suppl 1):A14. [Google Scholar]
- 9.Coles AJ, Cox A, Le Page E, Jones J, Trip SA, Deans J, et al. The window of therapeutic opportunity in multiple sclerosis. J Neurology. 2006;253(1):98–108. doi: 10.1007/s00415-005-0934-5. [DOI] [PubMed] [Google Scholar]
- 10.Feldman DE, Bernatsky S, Haggerty J, Leffondre K, Tousignant P, Roy Y, et al. Delay in consultation with specialists for persons with suspected new-onset rheumatoid arthritis: A population-based study. Arthritis Care Res. 2007;57(8):1419–1425. doi: 10.1002/art.23086. [DOI] [PubMed] [Google Scholar]
- 11.Põlluste K, Kallikorm R, Meiesaar K, Lember M. Use of general practice and rheumatology outpatient services in rheumatoid arthritis. J Fam Pract. 2012;29(4):433–440. doi: 10.1093/fampra/cmr109. [DOI] [PubMed] [Google Scholar]
- 12.Tavares R, Pope JE, Tremblay JL, Thorne C, Bykerk VP, Lazovskis J, et al. Time to disease-modifying antirheumatic drug treatment in rheumatoid arthritis and its predictors: a national, multicenter, retrospective cohort. J Rheumatol. 2012;39(11):2088–2097. doi: 10.3899/jrheum.120100. [DOI] [PubMed] [Google Scholar]
- 13.Jacobi CE, Mol GD, Boshuizen HC, Rupp I, Dinant HJ, Van den Bos GA. Impact of socioeconomic status on the course of rheumatoid arthritis and on related use of health care services. Arthritis Care Res. 2003;49(4):567–573. doi: 10.1002/art.11200. [DOI] [PubMed] [Google Scholar]
- 14.Nemet GF, Bailey AJ. Distance and health care utilization among the rural elderly. Soc Sci Med. 2000;50:1197–1208. doi: 10.1016/s0277-9536(99)00365-2. [DOI] [PubMed] [Google Scholar]
- 15.Arcury TA, Gesler WM, Preisser JS, Sherman J, Spencer J, Perin J. The effects of geography and spatial behavior on health care utilization among the residents of a rural region. J Health Serv Res. 2005;40:135–156. doi: 10.1111/j.1475-6773.2005.00346.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Huang B, Dignan M, Han D, Johnson O. Does distance matter? Distance to mammography facilities and stage at diagnosis of breast cancer in Kentucky. J Rur Health. 2009;25:366–371. doi: 10.1111/j.1748-0361.2009.00245.x. [DOI] [PubMed] [Google Scholar]
- 17.Sant M, Allemani C, Capocaccia R, Hakulinen T, Aareleid T, Coebergh JW, et al. Stage at diagnosis is a key explanation of differences in breast cancer survival across Europe. Int J Cancer. 2003;106:416–422. doi: 10.1002/ijc.11226. [DOI] [PubMed] [Google Scholar]
- 18.Jones SE. Metastatic breast cancer: the treatment challenge. Clin Breast Cancer. 2008;8:224–233. doi: 10.3816/CBC.2008.n.025. [DOI] [PubMed] [Google Scholar]
- 19.Arnett FC, Edworthy SM, Bloch DA, et al. The American Rheumatism Association 1987 revised criteria for the classification of rheumatoid arthritis. Arthritis Care Res. 2000;13:156–167. doi: 10.1002/art.1780310302. [DOI] [PubMed] [Google Scholar]
- 20.Escalante A, del Rincón I. How much disability in rheumatoid arthritis is explained by rheumatoid arthritis? Arthritis Rheum. 1999;42:1712–1721. doi: 10.1002/1529-0131(199908)42:8<1712::AID-ANR21>3.0.CO;2-X. [DOI] [PubMed] [Google Scholar]
- 21.Escalante A, del Rincon I. The disablement process in rheumatoid arthritis. Arthritis Rheum. 2002;47:333–342. doi: 10.1002/art.10418. [DOI] [PubMed] [Google Scholar]
- 22.Escalante A, del Rincón I, Mulrow CD. Symptoms of depression and psychological distress among Hispanics with rheumatoid arthritis. Arthritis Care Res. 2000;13:156–167. doi: 10.1002/1529-0131(200006)13:3<156::aid-anr5>3.0.co;2-0. [DOI] [PubMed] [Google Scholar]
- 23.Nam CB, Powers MG. The Socioeconomic Approach to Status Measurement With a Guide to Occupational and Socioeconomic Status Scores. Cap & Gown Press; Houston, Tex: 1983. [Google Scholar]
- 24.Pincus T, Summey JA, Soraci SA, Jr, Wallston KA, Hummon NP. Assessment of patient satisfaction in activities of daily living using a modified Stanford Health Assessment Questionnaire. Arthritis Rheum. 1983;26:1346–53. doi: 10.1002/art.1780261107. [DOI] [PubMed] [Google Scholar]
- 25.Orces CH, del Rincon I, Abel MP, Escalante A. The number of deformed joints as a surrogate measure of damage in rheumatoid arthritis. Arthritis Care Res. 2002;47:67–72. doi: 10.1002/art1.10160. [DOI] [PubMed] [Google Scholar]
- 26.Prevoo ML, van 't Hof MA, Kuper HH, van Leeuwen MA, van de Putte LB, van Riel PL. Modified disease activity scores that include twenty-eight–joint counts: development and validation in a prospective longitudinal study of patients with rheumatoid arthritis. Arthritis Rheum. 1995;38:44–48. doi: 10.1002/art.1780380107. [DOI] [PubMed] [Google Scholar]
- 27.del Rincon I, Battafarano DF, Arroyo RA, Murphy FT, Escalante A. Heterogeneity between men and women in the influence of the HLA-DRB1 shared epitope on the clinical expression of rheumatoid arthritis. Arthritis Rheum. 2002;46:1480–1488. doi: 10.1002/art.10295. [DOI] [PubMed] [Google Scholar]
- 28.Sharp JT, Young DY, Bluhm GB, Brook A, Brower AC, Corbett M, et al. How many joints in the hands and wrists should be included in a score of radiologic abnormalities used to assess rheumatoid arthritis? Arthritis Rheum. 1985;28:1326–35. doi: 10.1002/art.1780281203. [DOI] [PubMed] [Google Scholar]
- 29.Gillis JZ, Yazdany J, Trupin L, Julian L, Panopalis P, Criswell LA, et al. Medicaid and access to care among persons with systemic lupus erythematosus. Arthritis Care Res. 2007;57:601–607. doi: 10.1002/art.22671. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Pedersen M, Jacobsen S, Klarlund M, Frisch M. Socioeconomic status and risk of rheumatoid arthritis: a Danish case-control study. J Rheumatol. 2006;33:1069–1074. [PubMed] [Google Scholar]
- 31.Begtsson C, Nordmark B, Klareskog L, Lundberg I, Alfredsson L. Socioeconomic status and the risk of developing rheumatoid arthritis: results from the Swedish EIRA study. Ann Rheum Dis. 2005;64:1588–1594. doi: 10.1136/ard.2004.031666. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Pincus T, Callahan LF. Formal education as a marker for increased mortality and morbidity in rheumatoid arthritis. J Chronic Dis. 1985;38:973–984. doi: 10.1016/0021-9681(85)90095-5. [DOI] [PubMed] [Google Scholar]
- 33.Massardo L, Pons-Estel BA, Wojdyla D, Cardiel MH, Galarza-Maldonado CM, Sacnun MP, et al. Early rheumatoid arthritis in Latin America: low socioeconomic status related to high disease activity at baseline. Arthritis Care Res. 2012;64:1135–1143. doi: 10.1002/acr.21680. [DOI] [PubMed] [Google Scholar]
- 34.Brekke M, Hjortdahl P, Thelle DS, Kvien TK. Disease activity and severity in patients with rheumatoid arthritis: relations to socioeconomic inequality. Soc Sci Med. 1999;48:1743–1750. doi: 10.1016/s0277-9536(99)00075-1. [DOI] [PubMed] [Google Scholar]
- 35.Harrison MJ, Tricker KJ, Davies L, Hassell A, Dawes P, Scott DL, et al. The relationship between social deprivation, disease outcome measures, and response to treatment in patients with stable, long-standing rheumatoid arthritis. J Rheumatol. 2005;32:2330–2336. [PubMed] [Google Scholar]
- 36.Aletaha D, Funovits J, Ward MM, Smolen JS, Kvien TK. Perception of improvement in patients with rheumatoid arthritis varies with disease activity levels at baseline. Arthritis Rheum. 2009;61:313–320. doi: 10.1002/art.24282. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Wolfe F, Pincus T. Listening to the patient: a practical guide to self-report questionnaires in clinical care. Arthritis Rheum. 1999;42:1797–1808. doi: 10.1002/1529-0131(199909)42:9<1797::AID-ANR2>3.0.CO;2-Q. [DOI] [PubMed] [Google Scholar]
- 38.Bruynesteyn K, van der Heijde D, Boers M, Saudan A, Peloso P, Paulus H, et al. Determination of the minimal clinically important difference in rheumatoid arthritis joint damage of the Sharp/van der Heijde and Larsen/Scott scoring methods by clinical experts and comparison with the smallest detectable difference. Arthritis Rheum. 2002;46:913–920. doi: 10.1002/art.10190. [DOI] [PubMed] [Google Scholar]
- 39.Grigor C, Capell H, Stirling A, McMahon AD, Lock P, Vallance R, et al. Effect of a treatment strategy of tight control for rheumatoid arthritis (the TICORA study): a single-blind randomised controlled trial. The Lancet. 2004;364:263–269. doi: 10.1016/S0140-6736(04)16676-2. [DOI] [PubMed] [Google Scholar]