Search tips
Search criteria 


Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Arthritis Rheum. Author manuscript; available in PMC 2013 December 1.
Published in final edited form as:
PMCID: PMC3510359

Predictors of Organ Damage in Systemic Lupus Erythematosus: the Hopkins’ Lupus Cohort

Michelle Petri, M.D. M.P.H.,1 Sneha Purvey, M.B.B.S.,1 Hong Fang, M.D. M.S.,1 and Laurence S. Magder, Ph.D. M.P.H.2



The SLICC/ACR Damage Index (SDI) is the accepted measure of permanent organ damage in SLE. We analyzed data from a large SLE cohort to identify variables associated with rates of damage accrual as measured by the SDI.


2054 SLE patients (92% female, 56% Caucasian, 37% African-American, mean age at diagnosis 33 years) were included. The SDI was calculated retrospectively at the time of cohort entry, and prospectively during follow-up. The relationships between time-invariant patient characteristics and rates of damage accrual were assessed based on the damage score at last available follow-up. The relationships between time-varying patient characteristics and damage accrual were assessed based on the timing of damage accrual during cohort participation..


Overall, the SDI increased at a rate of 0.13 per year. Higher rates of damage were observed for those who were older, male, African American, low income, low education, hypertensive, had lupus anticoagulant, or who had proteinuria. During follow-up, the risk of damage was higher for those who were older with more disease activity, low complement, anti-dsDNA, satisfied more ACR-11 criteria, and using corticosteroids. Lower risk was observed among those using hydroxychloroquine. After adjustment for other variables, age, hypertension, and use of corticosteroids emerged as the most important predictors of damage accrual.


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.

Keywords: SLICC/ACR Damage index (SDI), SLE


Systemic lupus erythematosus (SLE) is a multi-system autoimmune disease characterized by fluctuating disease activity. The survival of patients with SLE has improved over the last 40 years from an estimated 5 year survival of 50% to over 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 patients with SLE is aimed not just at immediate control of disease activity, but also at the prevention of organ damage from treatment and co-morbidity.

The Systemic Lupus International Collaborating Clinics/American College of Rheumatology (SLICC/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 [5,6] and several prospective studies [7,8,9] have examined predictors or associates of damage.

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

Patients and Methods

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 2054 patients in the cohort, including 1155 (56%) Caucasian, 761 (37%) African-American, and 138 of other ethnicities (7%). Of these, 92% (1899) were females and 8% (155) males. The mean age at diagnosis was 33 years. 38% of the patients entered the cohort within 1 year of SLE diagnosis, 35% entered 1–5 years after diagnosis, and the remaining patients entered more than 5 years after diagnosis with SLE.

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


The SLICC/ACR Damage Index (SDI)

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

Demographic factors

The demographic factors included age at diagnosis, gender, ethnicity, income and education. Income was measured as total annual household income at first visit, falling into 3 categories <$30,000, $30,000-$65,000 and >$65,000. Education was assessed in years and was categorized into 0–12 years and above 12 years.

Clinical factors

The clinical factors included average level of disease activity during cohort participation and comorbid conditions. The disease activity was measured by the SELENA-SLEDAI score We also compared groups based on the number of revised ACR classification criteria satisfied at diagnosis (divided into ≤5 or >5). Hypertension was defined as either a systolic blood pressure above 140, a diastolic blood pressure above 90, or use of hypertension medications. A history of proteinuria was defined as 500 mg or more by 24 hour urine or spot urine protein to creatinine ratio; or 3+ or higher by urine dipstick.

Serologic factors

The quarterly laboratory investigations comprised the complete blood count, erythrocyte sedimentation rate, serum creatinine, complement levels C3 and C4, autoantibody assays (anti-dsDNA, anticardiolipin, lupus anticoagulant by Russell viper venom time with confirmatory testing), urinalysis and urine protein/creatinine ratio. Several autoantibodies, (anti-Sm, anti-RNP, anti-Ro, anti-La, and anti-β2-glycoprotein were done at cohort entry or only at more recent visits.

Therapeutic factors

Drugs used in the treatment of SLE, including hydroxychloroquine, corticosteroids and other immunosuppressive drugs, were considered in 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 estimate the rate parameter using Poisson regression allowing for possible overdispersion. The outcome variable was the SDI 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 follow-up 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 that patient acquired a new item of organ damage 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 [10]. 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.


Figure 1 shows plots of the SDI over time, within subgroups defined by gender, ethnicity, income, and lupus anticoagulant. They 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.

Figure 1
Mean Damage Index by years since diagnosis, in subgroups defined by selected predictors.

Analysis of time-invariant characteristics

Table 1 shows estimates of the rate of SDI increase in subgroups defined by time-invariant characteristics of the patients. The mean rate of increase in the SDI score was 0.13 per year post diagnosis. Faster rates of damage accrual were observed for those who were older at diagnosis, male, lower income and lower education, and 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.

Table 1
Rate of damage accrual after SLE diagnosis in groups defined by patient characteristics1.

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 during cohort participation. 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, and recent low complement, or anti-dsDNA. It was also reduced among those on hydroxychloroquine, and increased among those on cyclophosphamide. The highest risk was among those with an average dose of corticosteroids of 20mg daily or higher.

Table 2
Association between damage accrual each month and recent or past clinical variables.

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 use was a stronger predictor than mean past corticosteroids, low C3 was a stronger predictor than low C4 or anti-dsDNA, and average past hydroxychloroquine use was a stronger protector than current hydroxychloroquine use. Based on this work 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 dose. There was some evidence (p=.060) that hydroxychloroquine use was protective.

Table 3
Association between various predictors and damage accrual each month controlling for other predictors in a multivariable model.

Sub-analyses based on an inception cohort

To address concerns that the quality of information about damage for those whose diagnosis preceded cohort entry might differ from the quality among those who entered the cohort at the time of diagnosis, we performed separate analyses among 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 vs. 0.133 per year for those not in the inception cohort).


Many past studies of organ damage in SLE had limitations, such as retrospective assessment [7, 11], short disease duration [8, 11], cross-sectional study design rather than prospective [5,6] or having relatively small numbers of patients [7]. In this study, we report the result from the largest ongoing prospective study of SLE patients followed by protocol, comprising 2054 patients in the Hopkins Lupus Cohort.

The most important demographic predictors of progression in damage were high age at diagnosis race/ethnicity, and low income. Previous studies have showed divergent results between ethnicity and damage; some found that non-Caucasians 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 studies [11,12,13] also concluded that low socioeconomic status was associated with greater degree of damage. Low income is also associated with malnutrition, limited access to quality care and poor compliance with medication.

Disease activity (SELENA-SLEDAI) was associated with increased the rate of progression. Other studies, using other measures of disease activity [6,11,13,14], reached the same conclusion. In our analysis, the association between disease activity and damage largely disappears 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 the lupus anticoagulant, not anti-dsDNA as found in one study [9] or other antiphospholipid antibodies. We have previously emphasized that the 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 the lupus anticoagulant.

The most striking 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 is 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 on the SDI [17]. Another study has found that hydroxychloroquine may protect against renal and neurologic damage, in particular. The current study confirmed that hydroxychloroquine use was associated with lower rates of damage accrual.

The cohort is unique, in that all patients are seen by one rheumatologist at least quarterly, 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 messages resulted.. Rates of damage differ significantly between demographic subgroups. The most important predictor of damage appears to be corticosteroid use. Prophylactic therapy for the lupus anticoagulant and better control of disease activity, without reliance on corticosteroids, may limit future damage.


Grant support: The Hopkins Lupus Cohort is supported by NIH R01AR043727.


1. Kasitanon N, Magder LS, Petri M. Predictors of Survival in Systemic Lupus Erythematosus. Medicine. 2006;85:147–156. [PubMed]
2. Rubin LA, Urowitz MB, Gladman DD. Mortality in systemic lupus erythematosus: the bimodal pattern revisited. Q J Med. 1985 Apr;55:87–98. [PubMed]
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;39:363–369. [PubMed]
4. Gladman D, 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;40:809–813. [PubMed]
5. Zonana-Nacach A, Camargo-Coronel A, Yáñez P, de Lourdes Sánchez 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;7:119–123. [PubMed]
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 Nov;38:1130–1137. [PubMed]
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 Apr;25:654–659. [PubMed]
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 Apr;39:399–406. [PubMed]
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 Feb;42:276–279. [PubMed]
10. 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 Feb;42:276–279. [PubMed]
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 Jan;40:47–56. [PubMed]
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 Aug 15;57:993–999. [PubMed]
13. Alarcón GS, McGwin G, Jr, Bartolucci AA, Roseman J, Lisse J, Fessler BJ, et al. Systemic lupus erythematosus in three ethnic groups. IX. Differences in damage accrual. Arthritis Rheum. 2001 Dec;44:2797–806. [PubMed]
14. Alarcón 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 Feb;43:202–205. [PubMed]
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;29:2531–2536. [PubMed]
16. Zonana-Nacach A, Barr SG, Magder LS, Petri M. Damage in systemic lupus erythematosus and its association with corticosteroids. Arthritis Rheum. 2000 Aug;43:1801–1808. [PubMed]
17. Petri M. Hydroxychloroquine prevents later damage in SLE. Arthritis Rheum. 2001;44:S280.