SEARCH

SEARCH BY CITATION

Abstract

  1. Top of page
  2. Abstract
  3. PATIENTS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. AUTHOR CONTRIBUTIONS
  7. REFERENCES

Objective

The Systemic Lupus International Collaborating Clinics/American College of Rheumatology (ACR) Damage Index (SDI) is the accepted measure of permanent organ damage in systemic lupus erythematosus (SLE). We analyzed data from a large SLE cohort to identify variables associated with rates of damage accrual as measured by the SDI.

Methods

The study included 2,054 SLE patients (92% female, 56% white, and 37% African American) with a mean age at diagnosis of 33 years. The SDI score was calculated retrospectively at the time of cohort entry and prospectively during followup. The relationships between time-invariant patient characteristics and rates of damage accrual were assessed based on the damage score at the last available followup visit. The relationships between time-varying patient characteristics and damage accrual were assessed based on the timing of damage accrual during cohort participation.

Results

Overall, the SDI score increased at a rate of 0.13 per year. Higher rates of damage were observed for those who were older, male, or African American, had a lower income or education level, were hypertensive, were positive for lupus anticoagulant, or had proteinuria. During followup, the risk of damage was higher for those who were older, had more disease activity, had low complement levels, were positive for anti–double-stranded DNA, satisfied more ACR criteria for SLE, or were receiving corticosteroids. Lower risk was observed among patients receiving hydroxychloroquine. After adjustment for other variables, age, hypertension, and corticosteroid use emerged as the most important predictors of damage accrual.

Conclusion

Our findings indicate that rates of damage vary in demographic subgroups, but much variation appears to be explained by hypertension and corticosteroid use. These data clearly point to the need for tight control of disease activity without reliance on corticosteroids.

Systemic lupus erythematosus (SLE) is a multisystem autoimmune disease characterized by fluctuating disease activity. The survival rate of patients with SLE has improved over the last 40 years, from an estimated 5-year survival rate of 50% to >90%. The 10-year survival rate is nearly 90% (1). In patients who survive longer than 10 years, the major cause of death is not active SLE (2). The management of SLE is aimed not just at immediate control of disease activity, but also at the prevention of organ damage from treatment and comorbidity.

The Systemic Lupus International Collaborating Clinics/American College of Rheumatology (ACR) Damage Index (SDI) is a validated instrument designed to measure irreversible damage in SLE patients, regardless of cause or attribution (3, 4). Multiple cross-sectional studies (5, 6) and several prospective studies (7–9) have examined variables that are predictive of or associated with damage.

The Hopkins Lupus Cohort is a longitudinal study of patients with SLE. Because of its size and unique design, with quarterly followup using a set protocol, it provides an opportunity to assess risk factors for accrual of damage after diagnosis in both white and African American patients.

PATIENTS AND METHODS

  1. Top of page
  2. Abstract
  3. PATIENTS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. AUTHOR CONTRIBUTIONS
  7. REFERENCES

Patients.

Since 1987, patients with SLE presenting at Johns Hopkins University have been invited to participate in the Hopkins Lupus Cohort. The study is approved by the Johns Hopkins University School of Medicine Institutional Review Board. Those who sign an informed consent are entered into the cohort.

At the time of this analysis, there were 2,054 patients in the cohort, including 1,155 white patients (56%), 761 African American patients (37%), and 138 patients of other ethnicities (7%). Of the 2,054 patients, 92% (1,899) were women and 8% (155) were men. The mean age at diagnosis was 33 years. Thirty-eight percent of the patients entered the cohort within 1 year of SLE diagnosis, 35% entered 1–5 years after diagnosis, and the remaining patients entered >5 years after being diagnosed as having SLE.

The patients were followed up by protocol quarterly, or more often if clinically warranted. The average followup time per patient was 6.4 years. At each quarterly visit, clinical, laboratory, and treatment data were collected. The dropout rate was ∼10% per year.

Assessment of damage using the SDI.

The SDI score was calculated based on organ damage that occurred after diagnosis with SLE. Information about damage that occurred prior to cohort entry was obtained from a detailed history and chart review conducted at the time of cohort entry.

Demographic factors.

Demographic factors included age at diagnosis, sex, ethnicity, income, and education level. Income was measured as total annual household income at first visit, and was classified into one of 3 categories: <$30,000, $30,000–65,000, and >$65,000. Education level was assessed in years and was categorized as 0–12 years or >12 years.

Clinical factors.

Clinical factors included average level of disease activity during cohort participation and comorbid conditions. Disease activity was measured by the Safety of Estrogens in Lupus Erythematosus National Assessment (SELENA) version of the SLE Disease Activity Index (SLEDAI). We also compared groups based on the number of ACR revised classification criteria for SLE (10) satisfied at diagnosis (≤5 criteria or >5 criteria). Hypertension was defined as either a systolic blood pressure of >140, a diastolic blood pressure of >90, or use of hypertension medications. A history of proteinuria was defined as the presence of ≥500 mg protein in a 24-hour urine specimen or a protein-to-creatinine ratio of 0.500 in a spot urine specimen, or as 3+ protein or higher by urine dipstick.

Serologic factors.

The quarterly laboratory investigations comprised a complete blood cell count, erythrocyte sedimentation rate, serum creatinine level, complement C3 and C4 levels, autoantibody assays (anti–double-stranded DNA [anti-dsDNA], anticardiolipin, and lupus anticoagulant by Russell's viper venom time with confirmatory testing), urinalysis, and urine protein-to-creatinine ratio. Several autoantibodies (anti-Sm, anti-RNP, anti-Ro, anti-La, and anti–β2-glycoprotein) were assessed, at both cohort entry and more recent visits for some patients and only at more recent visits for other patients.

Therapeutic factors.

Drugs used in the treatment of SLE, including hydroxychloroquine, corticosteroids, and other immunosuppressive drugs, were considered in the analyses.

Statistical analysis.

We constructed plots of the mean damage score by years since diagnosis in subgroups defined by demographic and serologic variables. To assess the relationship between patient characteristics and rates of damage accrual after diagnosis, we postulated that the expected damage score was equal to time since diagnosis times a damage accrual rate. We estimated the rate parameter using Poisson regression, allowing for possible overdispersion. The outcome variable was the SDI score at the last available cohort visit, time was included as an offset, and the accrual rate was allowed to vary by patient characteristics. This resulted in estimates of the rate of damage accrual over time in subgroups defined by patient characteristics, and statistical tests of whether these rates differed significantly between subgroups.

To assess the relationship between time-varying patient characteristics (e.g., current medications, recent disease activity) and damage accrual, we reformatted the data set to consist of one record for each person-month of followup in the cohort. Each person-month record contained current values of predictors of interest for that patient (e.g., current medication, recent measure of disease activity, average past levels of disease activity up until that month), and an indicator of whether a new item of organ damage occurred in that patient during that month. We then analyzed this file using logistic regression where the outcome was binary (accrual of damage), and predictors consisted of the patient characteristics associated with that month. This approach is sometimes referred to as “pooled logistic regression” and has been shown to result in estimates of event rate ratios that are approximately equivalent to those found using a Cox proportional hazards model (9). To account for the fact that the same patient contributed multiple damage events in the analysis, we used a generalized estimating equation approach to fitting the model.

RESULTS

  1. Top of page
  2. Abstract
  3. PATIENTS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. AUTHOR CONTRIBUTIONS
  7. REFERENCES

SDI score over time.

Figure 1 shows plots of the SDI score over time within subgroups of patients defined by sex, ethnicity, income, and lupus anticoagulant status. These plots suggest that there is an approximately linear relationship between time since diagnosis and mean damage score and illustrate different rates of progression in different groups.

thumbnail image

Figure 1. Mean Systemic Lupus International Collaborating Clinics/American College of Rheumatology Damage Index (SDI) score, by years since diagnosis (dx), in subgroups of patients defined by the predictors sex (top left), ethnicity (top right), income level (bottom left), and presence of lupus anticoagulant (bottom right). AA = African American; RVVT = Russell's viper venom time.

Download figure to PowerPoint

Analysis of time-invariant characteristics.

Table 1 shows estimates of the rate of increase in the SDI score in subgroups of patients defined by time-invariant characteristics. The mean rate of increase in the SDI score was 0.13 per year after diagnosis. Faster rates of damage accrual were observed for those who were older at diagnosis, were male, had a lower income or lower education level, or were African American. Hypertension, proteinuria, and a history of being positive for lupus anticoagulant were also associated with faster damage accrual. There was no strong association between damage accrual rates and history of anticardiolipin, anti-β2-glycoprotein I, or anti-Ro positivity.

Table 1. Rate of damage accrual after SLE diagnosis in groups defined by patient characteristics*
CharacteristicRate of increase in SDI score (per year)P
  • *

    Sample sizes for each characteristic do not all total 2,054 due to unknown values for some patients. SLE = systemic lupus erythematosus; SDI = Systemic Lupus International Collaborating Clinics/American College of Rheumatology (ACR) Damage Index.

Total0.13
Age at diagnosis, years  
 0–29 (n = 1,006)0.12Reference group
 30–44 (n = 686)0.140.0881
 45–59 (n = 290)0.20<0.0001
 ≥60 (n = 72)0.31<0.0001
Sex  
 Male (n = 155)0.18Reference group
 Female (n = 1,899)0.130.047
Year of diagnosis  
 Before 1980 (n = 140)0.13Reference group
 1980s (n = 402)0.140.47
 1990s (n = 828)0.130.86
 2000s (n = 684)0.140.65
Ethnicity  
 White (n = 1,155)0.12Reference group
 African American (n = 761)0.160.0046
 Other (n = 138)0.120.90
Annual household income, dollars  
 <30,000 (n = 584)0.16Reference group
 30,000–65,000 (n = 612)0.120.011
 >65,000 (n = 611)0.100.0002
Education, years  
 0–12 (n = 709)0.16Reference group
 ≥13 (n = 1,244)0.120.0028
Number of ACR criteria satisfied at diagnosis  
 ≤5 (n = 1,326)0.12Reference group
 >5 (n = 728)0.160.0003
History of anticardiolipin positivity  
 No (n = 1,447)0.13Reference group
 Yes (n = 542)0.150.096
History of anti–β2-glycoprotein I positivity  
 No (n = 760)0.11Reference group
 Yes (n = 335)0.120.70
History of lupus anticoagulant positivity  
 No (n = 1,701)0.13Reference group
 Yes (n = 292)0.190.0003
History of anti-Ro positivity  
 No (n = 1,386)0.13Reference group
 Yes (n = 602)0.140.58
Hypertension  
 Never (n = 997)0.10Reference group
 Ever (n = 1,054)0.16<0.0001
Proteinuria  
 Never (n = 1,411)0.12Reference group
 Ever (n = 634)0.17<0.0001

Analysis of time-varying characteristics.

Table 2 shows the relationship between a patient's characteristics at or prior to a given month and the risk of developing new organ damage in that month, based on damage experienced throughout the patient's participation in the cohort. The risk of damage did not vary by time since SLE diagnosis, but increased substantially with age. The risk was higher among those with a recent or past history of high disease activity, recent low complement level, or recent anti-dsDNA positivity. It was reduced among those taking hydroxychloroquine, and increased among those taking cyclophosphamide. The highest risk was among those taking an average dosage of corticosteroids of ≥20 mg daily.

Table 2. Association between damage accrual each month in SLE patients and recent or past clinical variables*
SubgroupNumber of months with an increase in damageNumber of person-months observedRate of events per person-yearOR (95% CI)P
  • *

    The numbers of person-months for each characteristic do not all total 164,014 due to missing values for some variables. SLE = systemic lupus erythematosus; OR = odds ratio; 95% CI = 95% confidence interval; SELENA-SLEDAI = Safety of Estrogens in Lupus Erythematosus National Assessment version of the SLE Disease Activity Index; anti-dsDNA = anti–double-stranded DNA.

  • Based on the most recent cohort visit.

  • Based on all prior cohort visits.

Duration of SLE, years     
 <323926,4460.111.0 (reference group) 
 3–624330,4770.100.9 (0.7–1.0)0.14
 6–1029136,4340.100.8 (0.7–1.0)0.11
 10–1526232,2350.100.9 (0.7–1.0)0.22
 ≥1534438,4220.110.9 (0.8–1.1)0.41
Age, years     
 18–3951475,3910.081.0 (reference group) 
 40–4933543,8620.091.1 (0.9–1.3)0.41
 50–5930828,3290.131.5 (1.3–1.8)<0.0001
 60–6915412,3760.151.8 (1.5–2.2)<0.0001
 ≥70694,0560.202.3 (1.7–3.3)<0.0001
Calendar year     
 1987–199217813,0670.161.0 (reference group) 
 1993–199829927,6350.130.8 (0.7–1.0)0.033
 1999–200447650,7820.110.7 (0.6–0.8)0.0002
 2005–201142672,4710.070.4 (0.4–0.5)<0.0001
Recent SELENA–SLEDAI score     
 <247963,3310.091.0 (reference group) 
 2–328738,2320.091.0 (0.8–1.1)0.75
 ≥453845,6350.141.5 (1.3–1.7)<0.0001
Mean SELENA–SLEDAI score     
 <1.528440,3120.091.0 (reference group) 
 1.5–3.536841,7530.111.2 (1.0–1.4)0.036
 >3.546238,4810.141.7 (1.4–2.0)<0.0001
Recent low C3     
 No947114,8620.101.0 (reference group) 
 Yes35031,4570.131.3 (1.2–1.5)<0.0001
Prior low C3     
 No59877,2360.091.0 (reference group) 
 Yes78186,7780.111.1 (1.0–1.3)0.082
Recent low C4     
 No1,046121,3290.101.0 (reference group) 
 Yes25024,9270.121.2 (1.0–1.4)0.044
Prior low C4     
 No74291,0800.101.0 (reference group) 
 Yes63772,9340.101.0 (0.9–1.2)0.81
Recent anti-dsDNA     
 No911108,1650.101.0 (reference group) 
 Yes38537,6560.121.2 (1.1–1.4)0.0034
Prior anti-dsDNA     
 No59973,8770.101.0 (reference group) 
 Yes78090,1370.101.0 (0.9–1.2)0.62
Current dosage of corticosteroids, mg/day     
 043072,5020.071.0 (reference group) 
 1–933740,4780.101.4 (1.2–1.6)<0.0001
 10–1930823,2040.162.2 (1.9–2.6)<0.0001
 ≥2024410,2040.294.0 (3.4–4.8)<0.0001
Mean corticosteroid dosage during cohort participation, mg/day     
 020831,1740.081.0 (reference group) 
 1–945155,3030.101.2 (1.0–1.5)0.025
 10–1927822,3900.151.9 (1.5–2.3)<0.0001
 ≥201585,8810.324.2 (3.3–5.3)<0.0001
Current hydroxychloroquine use     
 No57452,3840.131.0 (reference group) 
 Yes74594,9040.090.7 (0.6–0.8)<0.0001
Proportion of previous cohort months taking hydroxychloroquine     
 None34727,6960.151.0 (reference group) 
 <0.512713,2820.110.7 (0.6–0.9)0.0025
 ≥0.562174,4330.100.6 (0.5–0.7)<0.0001
Current mycophenolate use     
 No1,250148,5980.101.0 (reference group) 
 Yes12915,4160.100.9 (0.7–1.1)0.38
Proportion of previous cohort visits taking mycophenolate     
 None1,171140,2580.101.0 (reference group) 
 <0.511511,7930.121.1 (0.8–1.3)0.64
 ≥0.59311,9630.090.8 (0.6–1.1)0.19
Current cyclophosphamide use     
 No1,343162,1540.101.0 (reference group) 
 Yes361,8600.232.2 (1.5–3.1)<0.0001
Proportion of previous cohort visits taking cyclophosphamide     
 None1,251151,8930.101.0 (reference group) 
 <0.510710,5700.121.1 (0.9–1.4)0.33
 ≥0.5211,5510.161.6 (1.1–2.4)0.022
Current azathioprine use     
 No1,284153,2640.101.0 (reference group) 
 Yes9510,7500.111.0 (0.8–1.3)0.90
Proportion of previous cohort visits taking azathioprine     
 None1,197143,9610.101.0 (reference group) 
 <0.510911,9370.111.1 (0.8–1.3)0.62
 ≥0.5738,1610.111.0 (0.8–1.3)0.80
Current methotrexate use     
 No1,341158,7810.101.0 (reference group) 
 Yes385,2330.090.8 (0.6–1.1)0.16
Proportion of previous cohort visits taking methotrexate     
 None1,293154,3710.101.0 (reference group) 
 <0.5566,2540.111.0 (0.7–1.3)0.82
 ≥0.5303,3890.111.0 (0.7–1.4)0.99

Multivariable model.

We fit a multivariable logistic regression model to the monthly data to assess the association between predictors and damage, while adjusting for other predictors in the model. To decide which variables to include, we fit some preliminary regression models. In this preliminary work we found that income was a stronger predictor than education, mean past SLEDAI was a stronger predictor than most recent SLEDAI, current corticosteroid dosage was a stronger predictor than mean past corticosteroid dosage, low C3 level was a stronger predictor than low C4 level or anti-dsDNA, and the proportion of previous visits at which the patient was receiving hydroxychloroquine was a stronger protector than current hydroxychloroquine use. Based on these findings, we chose variables for the full multivariable model shown in Table 3. After adjustment for other variables in the model, sex, ethnicity, disease activity, and several other variables were no longer associated with damage. The strongest predictors of damage appeared to be age and current corticosteroid dosage. There was some evidence that hydroxychloroquine use was protective (P = 0.060).

Table 3. Association between various predictors and damage accrual each month in SLE patients, controlling for other predictors in a multivariable model*
PredictorOR (95% CI)P
  • *

    SLE = systemic lupus erythematosus; OR = odds ratio; 95% CI = 95% confidence interval; ACR = American College of Rheumatology; SLEDAI = SLE Disease Activity Index.

Age, years  
 <401.0 (reference group) 
 40–491.2 (1.0–1.5)0.018
 50–591.9 (1.5–2.3)<0.0001
 60–692.4 (1.9–3.1)<0.0001
 ≥703.0 (2.0–4.5)<0.0001
Sex  
 Female1.0 (reference group) 
 Male1.0 (0.8–1.3)0.99
Ethnicity  
 White1.0 (reference group) 
 African American0.9 (0.7–1.1)0.16
 Other1.0 (0.7–1.4)0.92
Calendar year  
 1987–19921.0 (reference group) 
 1993–19981.0 (0.8–1.2)0.69
 1999–20040.9 (0.7–1.1)0.18
 2005--20090.6 (0.5–0.8)<0.0001
Annual household income, dollars  
 <30,0001.0 (reference group) 
 30,000–65,0001.0 (0.8–1.2)0.96
 >65,0000.9 (0.7–1.1)0.23
History of hypertension  
 No1.0 (reference group) 
 Yes1.3 (1.1–1.6)0.0011
History of proteinuria  
 No1.0 (reference group) 
 Yes1.0 (0.8–1.1)0.73
Number of ACR criteria satisfied at diagnosis  
 <51.0 (reference group) 
 ≥51.0 (0.9–1.1)0.71
Mean SLEDAI score in prior cohort visits  
 <1.51.0 (reference group) 
 1.5–3.51.1 (0.9–1.3)0.26
 >3.51.2 (1.0–1.4)0.18
History of lupus anticoagulant positivity  
 No1.0 (reference group) 
 Yes1.1 (1.0–1.3)0.15
Current low C3  
 No1.0 (reference group) 
 Yes1.1 (1.0–1.3)0.17
Current corticosteroid dosage, mg/day  
 01.0 (reference group) 
 1–91.2 (1.0–1.4)0.069
 10–191.8 (1.4–2.1)<0.0001
 ≥204.0 (3.2–4.9)<0.0001
Proportion of prior cohort visits taking hydroxychloroquine  
 None1.0 (reference group) 
 <0.50.9 (0.7–1.1)0.20
 ≥0.50.9 (0.7–1.0)0.060
Current cyclophosphamide use  
 No1.0 (reference group) 
 Yes1.3 (0.9–1.9)0.12

Subanalyses based on an inception cohort.

To address concerns that the quality of information about damage for patients whose diagnosis preceded cohort entry might differ from the quality for those who entered the cohort at the time of diagnosis, we performed separate analyses of those who entered the cohort within a year of diagnosis (“inception cohort”) and those who did not. The overall damage accrual rate was virtually the same in both groups (0.140 per year for those in the inception cohort compared to 0.133 per year for those not in the inception cohort).

DISCUSSION

  1. Top of page
  2. Abstract
  3. PATIENTS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. AUTHOR CONTRIBUTIONS
  7. REFERENCES

Many past studies of organ damage in SLE had limitations, such as retrospective assessment (7, 11), inclusion of patients with short disease duration (8, 11), cross-sectional rather than prospective study design (5, 6), or a relatively small number of patients (7). Herein we report results from the largest ongoing prospective study of SLE patients followed up by protocol, comprising 2,054 patients in the Hopkins Lupus Cohort.

The most important demographic predictors of progression in damage were older age at diagnosis, race/ethnicity, and low income. Previous studies have shown divergent results between ethnicity and damage; some found that nonwhite patients were at greater risk (6), specifically that African Americans had greater damage (12), while others did not (9, 11). We observed significantly faster rates of progression among African Americans in our univariate analysis, but not in our multivariate analysis. This suggests that the faster rate of progression in African Americans is explained by other variables in the model, such as income, hypertension, and proteinuria.

Lower income was associated with a higher rate of damage accrual. Some previous studies (11–13) have also shown that low socioeconomic status was associated with a greater degree of damage. Low income is also associated with malnutrition, limited access to quality care, and poor compliance with treatment regimens.

In this study, disease activity (measured by the SELENA-SLEDAI) was associated with an increased rate of progression. Other investigators, using other measures of disease activity (6, 11, 13, 14), have reached the same conclusion. In our analysis, the association between disease activity and damage largely disappeared after adjustment for corticosteroid use, suggesting that the association between disease activity and damage is mediated by increased use of corticosteroids.

The most predictive serologic test was that for lupus anticoagulant, not anti-dsDNA, as was shown in one previous study (9), or other antiphospholipid antibodies. We have previously emphasized that lupus anticoagulant is the antiphospholipid antibody most associated with thrombosis in SLE (15). These data clearly point to the need for effective prophylactic therapy for lupus anticoagulant.

The most notable finding was the strong association between corticosteroid use and damage accrual. This persisted even after adjusting for levels of SLE disease activity, suggesting that the association was not simply due to confounding by indication. In previous studies we have noted the association between corticosteroid use and specific forms of damage, including osteoporotic fractures, coronary artery disease, cataracts, avascular necrosis, and stroke (16).

Previously, an analysis of the Hopkins Lupus Cohort suggested that hydroxychloroquine might have a long-term protective effect on the SLE-related organ damage measured by the SDI (17). Another study found that hydroxychloroquine may protect against renal damage in particular (18). The present study confirmed that hydroxychloroquine use was associated with lower rates of damage accrual.

The Hopkins Lupus Cohort is unique in that each patient is seen at least quarterly by the same rheumatologist, and, thus, the results are not generalizable to all SLE patients. In addition, the analyses focused on the total damage score and not on individual items (which would likely have unique predictors). However, given these limitations, clear findings resulted from the analysis. Rates of damage differed significantly between demographic subgroups. The most important predictor of damage appeared to be corticosteroid use. Prophylactic therapy for lupus anticoagulant and better control of disease activity, without reliance on corticosteroids, may limit future damage.

AUTHOR CONTRIBUTIONS

  1. Top of page
  2. Abstract
  3. PATIENTS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. AUTHOR CONTRIBUTIONS
  7. REFERENCES

All authors were involved in drafting the article or revising it critically for important intellectual content, and all authors approved the final version to be published. Dr. Petri had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study conception and design. Petri, Purvey, Magder.

Acquisition of data. Petri, Fang.

Analysis and interpretation of data. Petri, Purvey, Fang, Magder.

REFERENCES

  1. Top of page
  2. Abstract
  3. PATIENTS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. AUTHOR CONTRIBUTIONS
  7. REFERENCES
  • 1
    Kasitanon N, Magder LS, Petri M. Predictors of survival in systemic lupus erythematosus. Medicine (Baltimore) 2006; 85: 14756.
  • 2
    Rubin LA, Urowitz MB, Gladman DD. Mortality in systemic lupus erythematosus: the bimodal pattern revisited. Q J Med 1985; 55: 8798.
  • 3
    Gladman D, Ginzler E, Goldsmith C, Fortin P, Liang M, Urowitz M, et al. The development and initial validation of the Systemic Lupus International Collaborating Clinics/American College of Rheumatology Damage Index for systemic lupus erythematosus. Arthritis Rheum 1996; 39: 3639.
  • 4
    Gladman DD, Urowitz MB, Goldsmith CH, Fortin P, Ginzler E, Gordon C, et al. The reliability of the Systemic Lupus International Collaborating Clinics/American College of Rheumatology Damage Index in patients with systemic lupus erythematosus. Arthritis Rheum 1997; 40: 80913.
  • 5
    Zonana-Nacach A, Camargo-Coronel A, Yanez P, de Lourdes Sanchez M, Jímenez-Balderas FJ, Aceves-Avila J, et al. Measurement of damage in 210 Mexican patients with systemic lupus erythematosus: relationship with disease duration. Lupus 1998; 7: 11923.
  • 6
    Sutcliffe N, Clarke AE, Gordon C, Farewell V, Isenberg DA. The association of socio-economic status, race, psychosocial factors and outcome in patients with systemic lupus erythematosus. Rheumatology (Oxford) 1999; 38: 11307.
  • 7
    Nossent JC. SLICC/ACR Damage Index in Afro-Caribbean patients with systemic lupus erythematosus: changes in and relationship to disease activity, corticosteroid therapy, and prognosis. J Rheumatol 1998; 25: 6549.
  • 8
    Mok CC, Lee KW, Ho CT, Lau CS, Wong RW. A prospective study of survival and prognostic indicators of systemic lupus erythematosus in a southern Chinese population. Rheumatology (Oxford) 2000; 39: 399406.
  • 9
    Yee CS, Hussein H, Skan J, Bowman S, Situnayake D, Gordon C. Association of damage with autoantibody profile, age, race, sex and disease duration in systemic lupus erythematosus. Rheumatology (Oxford) 2003; 42: 2769.
  • 10
    Tan EM, Cohen AS, Fries JF, Masi AT, McShane DJ, Rothfield NF, et al. The 1982 revised criteria for the classification of systemic lupus erythematosus. Arthritis Rheum 1982; 25: 12717.
  • 11
    Karlson EW, Daltroy LH, Lew RA, Wright EA, Partridge AJ, Fossel AH, et al. The relationship of socioeconomic status, race, and modifiable risk factors to outcomes in patients with systemic lupus erythematosus. Arthritis Rheum 1997; 40: 4756.
  • 12
    Cooper GS, Treadwell EL, St.Clair EW, Gilkeson GS, Dooley MA. Sociodemographic associations with early disease damage in patients with systemic lupus erythematosus. Arthritis Rheum 2007; 57: 9939.
  • 13
    Alarcon GS, McGwin G Jr, Bartolucci AA, Roseman J, Lisse J, Fessler BJ, et al, for the LUMINA Study Group. Systemic lupus erythematosus in three ethnic groups. IX. Differences in damage accrual. Arthritis Rheum 2001; 44: 2797806.
  • 14
    Alarcon GS, Roseman JM, McGwin G Jr, Uribe A, Bastian HM, Fessler BJ, et al. Systemic lupus erythematosus in three ethnic groups. XX. Damage as a predictor of further damage. Rheumatology (Oxford) 2004; 43: 2025.
  • 15
    Somers E, Magder LS, Petri M. Antiphospholipid antibodies and incidence of venous thrombosis in a cohort of patients with systemic lupus erythematosus. J Rheumatol 2002; 29: 25316.
  • 16
    Zonana-Nacach A, Barr SG, Magder LS, Petri M. Damage in systemic lupus erythematosus and its association with corticosteroids. Arthritis Rheum 2000; 43: 18018.
  • 17
    Petri M. Hydroxychloroquine prevents later damage in SLE [abstract]. Arthritis Rheum 2001; 44 Suppl: S280.
  • 18
    Fessler BJ, Alarcon GS, McGwin G Jr, Roseman J, Bastian HM, Friedman AW, et al, for the LUMINA Study Group. Systemic lupus erythematosus in three ethnic groups: XVI. Association of hydroxychloroquine use with reduced risk of damage accrual. Arthritis Rheum 2005; 52: 147380.