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Keywords:

  • Systemic lupus erythematosus;
  • Ethnicity;
  • Disparities;
  • LUMINA

Abstract

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

Objective

To examine health disparities as a function of ethnicity using data from LUpus in MInorities, NAture versus nurture (LUMINA), a longitudinal study of patients with systemic lupus erythematosus (SLE); to build an explanatory model of how ethnic disparities occur in this setting; and to suggest appropriate interventions.

Methods

LUMINA patients (meeting American College of Rheumatology criteria for SLE) ages ≥16 years of African American, Hispanic (from Texas), Hispanic (from Puerto Rico), or Caucasian ethnicity were studied. In addition to examining the basic features of the cohort, we examined, by univariable and multivariable analyses, the factors associated with disease activity, damage accrual, lupus nephritis, and mortality. An empiric model based on the data presented (and the literature reviewed) was derived to explain the disparities observed.

Results

There were substantial differences in the socioeconomic/demographic, clinical, and genetic features among patients from the different ethnic groups, with Texan Hispanic and African American patients exhibiting overall a lower socioeconomic status, different genetic associations, more serious disease at a younger age, and worse intermediate and final outcomes than the Caucasian and Puerto Rican Hispanic patients. A model of disease outcome as a function of the disparities observed was created.

Conclusion

Ethnic disparities occur in SLE. Environmental, socioeconomic/demographic, psychosocial, genetic, and clinical factors play an important role as determinants of the ethnic differences observed. Measures aimed at eliminating these disparities are suggested while further research is conducted to elucidate the basis of these disparities and their changes at the societal level and to eliminate the gap between the rich and the poor.


INTRODUCTION

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

Health disparities, as defined by the National Institute of Health (NIH) Working Group on Health Disparities, denote differences in the incidence, prevalence, mortality, and burden of disease and other health conditions that exist among distinct population groups in the US (by virtue of their age, race/ethnicity, sex, sexual orientation, or other characteristics) (1). Health disparities within different ethnic groups have been observed in musculoskeletal disorders (2–6), but whether these disparities relate to genetic or environmental factors or a combination of both has yet to be defined. Systemic lupus erythematosus (SLE), a disease that preferentially and more seriously affects women, ethnic minorities, and young persons, can serve to study the basis of these health disparities. Utilizing data from LUMINA (LUpus in MInorities, NAture versus nurture), a longitudinal study of outcome in patients with SLE, we built an explanatory model of how ethnic disparities occur and suggested points at which interventions can be developed; such interventions may result in effectively minimizing and even eliminating these disparities. To better understand this model, we will first briefly describe some salient features of this cohort.

PATIENTS AND METHODS

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

LUMINA is a multiethnic (Hispanic [Mexican or Puerto Rican ancestry], African American, or Caucasian ethnicity), multicenter (the University of Alabama at Birmingham, the University of Texas Health Science Center at Houston, and the University of Puerto Rico Medical Sciences Campus) cohort of patients with SLE (meeting the American College of Rheumatology [ACR] criteria [7, 8]), ages ≥16 years, with ≤5 years of disease duration (9, 10). LUMINA recruitment started in 1994 except in Puerto Rico, where recruitment started in 2001. The institutional review boards of all centers approved the study; written informed consent was obtained from each patient according to the declaration of Helsinki.

Visits are conducted at entry into the cohort (T0), every 6 months for the first year, and yearly thereafter. Time of diagnosis (TD) is the time at which patients meet 4 ACR SLE classification criteria (7). Disease duration is the interval between TD and T0. The cohort includes prevalent cases (≥6 months since TD) and incident cases (<6 months since TD) in a 2:1 proportion (9). The LUMINA database is comprehensive and includes socioeconomic/demographic, clinical, immunologic, genetic, psychological, and behavioral variables. Disease activity and damage accrual are assessed using the revised Systemic Lupus Activity Measure (SLAM-R) (11) and the Systemic Lupus International Collaborating Clinics/American College of Rheumatology Damage Index (SDI) (12), respectively.

RESULTS

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

Characteristics of the cohort.

As of January 2006, the LUMINA cohort consisted of 617 patients: 117 (19%) were Hispanics from Texas (primarily of Mexican ancestry), 103 (17%) were Hispanics from Puerto Rico, 221 (36%) were African American, and 176 (28%) were Caucasian. The majority of the patients were women (90%). As shown in Table 1, Hispanics from Puerto Rico and Caucasians were older at T0 and had an overall better socioeconomic status (education, income, housing, marital status, and health insurance) than the Hispanics from Texas and the African Americans. These socioeconomic/demographic data were comparable with those reported in previous publications (9, 10, 13).

Table 1. Selected baseline socioeconomic/demographic features of LUMINA (LUpus in MInorities, NAture versus nurture) patients*
VariableHispanicAfrican American (n = 221)Caucasian (n = 176)P
Texan (n = 117)Puerto Rican (n = 103)
  • *

    Values are the percentage unless otherwise indicated.

  • As defined by the US federal government guidelines (57).

Female sex939589850.032
Age, mean ± SD years32.8 ± 12.036.7 ± 11.234.8 ± 11.241.0 ± 13.3< 0.001
Education, mean ± SD years10.5 ± 3.214.7 ± 2.912.8 ± 2.213.7 ± 2.8< 0.001
Married/living together54593373< 0.001
Health insurance50998187< 0.001
Poverty42304515< 0.001
Home ownership53785071< 0.001
Exercise402946430.041
Smoking12614200.010
Drinking939160.004

Salient clinical features.

Selected clinical features are summarized in Table 2. As published previously (14, 15) and confirmed in the present study, African Americans and Texan Hispanics tend to have more serious disease compared with Caucasians and Puerto Rican Hispanics. For example, African Americans and Texan Hispanics exhibit acute disease onset and renal involvement more frequently. They also exhibit shorter disease duration and a shorter time to the accrual of 4 ACR criteria.

Table 2. Selected baseline clinical features of LUMINA (LUpus in MInorities, NAture versus nurture) patients*
VariableHispanicAfrican American (n = 221)Caucasian (n = 176)P
Texan (n = 117)Puerto Rican (n = 103)
  • *

    Values are the percentage unless otherwise indicated. ACR = American College of Rheumatology.

  • P values ≤0.05 are noted.

  • From diagnosis to enrollment.

  • §

    Cumulative frequency.

  • At any time before baseline.

Disease duration, mean ± SD months16.4 ± 16.019.2 ± 15.716.3 ± 16.517.7 ± 15.6 
Number of ACR criteria, mean ± SD5.6 ± 1.35.0 ± 0.95.7 ± 1.55.2 ± 1.1< 0.001
Time to accrual of 4 ACR criteria, months     
 Mean ± SD17.7 ± 39.926.9 ± 36.929.1 ± 63.742.9 ± 61.70.001
 Median (range)5.0 (0.0–245.0)9.0 (0.0–181.0)6.9 (0.0–543.1)21 (0.0–352.0) 
Acute onset274179< 0.001
Renal involvement§62266225< 0.001
Glucocorticoid average dose, mean ± SD mg10.6 ± 19.210.4 ± 14.112.9 ± 18.55.9 ± 11.7< 0.001
Glucocorticoid use918495860.005
Hydroxychloroquine use61846283< 0.001
Azathioprine use10191713 
Cyclophosphamide use21818130.025

Medication use is depicted in Table 2. Differences in medication use were noted, with Puerto Rican Hispanics and Caucasians using hydroxychloroquine more frequently than Texan Hispanics and African Americans (84%, 83%, 61%, and 62%, respectively; P ≤ 0.001); the reverse occurred with glucocorticoids and cyclophosphamide.

Genetic features.

The frequency distribution of HLADR and HLADQ alleles was reexamined, and results were consistent with previously published data (9, 16). In short, when compared with local controls, HLADRB1*0301 was found to be increased only in Caucasian patients, whereas HLADRB1*1503 was found to be increased only in African American patients. HLADRB1*08 was found to be increased in Hispanic patients from Texas, but not Hispanic patients from Puerto Rico; HLADQB1*0201 was found to be more frequent in Caucasians and HLADQB1*0602 more frequent in African Americans. These data confirm the genetic difference between the 2 Hispanic subgroups, and between the Hispanic subgroups and patients from the other 2 ethnic groups.

The frequency distribution of the Fc gamma receptor (FCGR) alleles was examined. Caucasian patients tended to exhibit the homozygous high-affinity FCGR3A gene polymorphism (FCGR3A*GG) more frequently compared with all other ethnic groups (16.1% versus 4.8% for Texan Hispanics, 5.8% for Puerto Rican Hispanics, and 8.4% for African Americans; P < 0.001); however, no differences were found in the distribution of FCR2A between the different ethnic groups. The FCGR3B gene NA2 homozygous polymorphism was found to be less frequent among Texan Hispanics than the other ethnic groups (15.7% versus 38.7% for African Americans, 38.7% for Caucasians, and 25.5% for Puerto Rican Hispanics; P = 0.001).

We also examined admixture using ancestral informative markers (AIMs), or genes that are differentially expressed among founding populations (African, European/ Caucasian, and Amerindian for the US) (17), and we found substantial heterogeneity within ethnic groups. For example, Texan Hispanics exhibit a much larger proportion of Amerindian ancestry (48%), followed by Puerto Rican Hispanics (20%) who also have a large African ancestry (45%); this is not the case for Texan Hispanics (18%). Caucasians and African Americans exhibit ∼20% of ancestral genes from the other founding population; therefore, categorizing patients by ethnic group, even when requiring all 4 grandparents to be of the same group, is an imperfect manner to account for the role genetic factors may exert in the expression of the disease in patients from different ethnic groups. Admixture should, therefore, be considered an adjustment variable in all analyses.

Disease activity.

As noted in Table 3, Texan Hispanic and African American patients exhibited higher disease activity than Caucasian and Puerto Rican Hispanic patients as measured by the SLAM-R and the physician global assessment. In contrast, African Americans and Caucasians assessed their disease as being more active compared with both Hispanic groups, although the differences were not significant. The discrepant perception of disease activity between patients and physicians may influence patients' behaviors.

Table 3. Disease activity and damage accrual in LUMINA (LUpus in MInorities, NAture versus nurture) patients*
VariableHispanicAfrican American (n = 221)Caucasian (n = 176)P
Texan (n = 117)Puerto Rican (n = 103)
  • *

    Values are the mean ± SD unless otherwise indicated. SLAM-R = Systemic Lupus Activity Measure revised; SDI = Systemic Lupus International Collaborating Clinics/American College of Rheumatology Damage Index.

  • P values ≤0.05 are noted.

  • Using a 10-cm visual analog scale.

  • §

    Between patient and physician global assessments visual analog scale.

SLAM-R score at baseline visit11.1 ± 6.46.8 ± 4.011.1 ± 6.57.7 ± 4.1< 0.001
SLAM-R score at last visit9.4 ± 6.05.4 ± 3.38.5 ± 5.85.5 ± 4.4< 0.001
SLAM-R score over time7.6 ± 4.47.6 ± 3.98.4 ± 5.18.1 ± 4.3 
Physician global assessment of disease activity at baseline2.6 ± 2.41.1 ± 1.13.1 ± 2.32.1 ± 1.6< 0.001
Patient global assessment of disease activity at baseline3.4 ± 3.03.5 ± 2.83.9 ± 3.03.8 ± 2.6 
Discrepancy at baseline§0.8 ± 2.82.3 ± 2.60.8 ± 3.01.7 ± 2.7< 0.001
SDI >0 at baseline visit, %37234940< 0.001
SDI >0 at last visit, %70357458< 0.001
SDI at baseline0.6 ± 1.00.3 ± 0.61.0 ± 1.40.7 ± 1.1< 0.001
SDI at last visit2.2 ± 2.60.5 ± 0.92.3 ± 2.51.4 ± 1.7< 0.001

Recently, we examined the factors predictive of persistently high disease activity (18). A total of 2,066 patient visits were examined. Younger age, African American and Texan Hispanic ethnicities, abnormal illness-related behaviors, poor social support, lack of health insurance, and high levels of disease activity in the previous visit emerged as variables predictive of subsequent high disease activity. Interestingly, genetic markers (HLA, FCGR, and AIMs) were not associated with this outcome even when previous disease activity was excluded from the original model (because disease activity early in the disease had been found to be negatively associated with HLADRB1*0301).

Lupus nephritis.

As noted in Table 2, renal involvement at T0 (and during the disease course) occurred more frequently in the African American patients (62%) and Texan Hispanic patients (62%) than in the Caucasian patients (25%) and Puerto Rican Hispanic patients (26%). In multivariable analyses, after adjusting for total disease duration, these 2 ethnicities were of borderline statistical significance whereas not being married, the number of ACR criteria, the presence of thrombocytopenia, and the presence of anti–double-stranded DNA and anti-Smith antibodies were found to predict the occurrence of nephritis (data not shown). These analyses are consistent with those performed prior to the inclusion of Puerto Rican Hispanic patients in LUMINA (19), the exception being that the Puerto Rican Hispanics became the reference group in the present analysis.

To further examine the role that genetic factors may have in the occurrence of nephritis, we recently included the admixture data in the model. A total of 150 patients with renal involvement were compared with 309 patients who did not have renal involvement. Patients with renal involvement had larger proportions of African and Amerindian ancestral genes than patients without renal involvement. In multivariable models, 36.8% of the variance was accounted for by admixture, 14.5% by socioeconomic status, and 12.2% by admixture and socioeconomic status combined. However, 45.9% of the variance in the model remained unexplained (20). These data suggest that genetic factors are more important determinants of renal involvement than the socioeconomic factors.

Damage.

As reported earlier (n = 258 patients) (21), half of the current cohort of patients had yet to accrue any damage at T0. As shown in Table 3, the SDI score was higher at T0 in the African Americans compared with all other ethnic groups; however, at the last visit the Texan Hispanics had caught up with the African Americans and both groups had accrued more damage than patients in the other 2 ethnic groups. In fact, when only patients who had yet to accrue any damage were examined, the Texan Hispanics, followed by the African Americans, were the ones accruing any damage at a faster pace (22).

We examined the variables predictive of damage accrual and compared these results with data from analyses performed prior to the inclusion of the Puerto Rican Hispanics (21). Given the distribution of the damage scores, a Poisson multivariable analysis was performed, adjusting for total disease duration. Variables found in both sets of analyses included age, Texan Hispanic ethnicity, poverty, number of ACR criteria met, disease activity at TD, and the mean dose of glucocorticoids (P < 0.001 for all). Additionally, African American and Caucasian ethnicities were significantly associated with increased risk of damage accrual (P < 0.001) when compared with the Puerto Rican Hispanics.

Mortality.

Five- and 10-year survival analyses have recently been performed (10-year rates are not available for the Puerto Rican Hispanics due to their late recruitment). As shown in Figure 1, the 5-year survival rates were lower for Texan Hispanics (86.9%) and African Americans (89.8%) than for Caucasians (93.6%) and Puerto Rican Hispanics (97.2%); these differences were significant (log rank = 9.687, P = 0.021). As noted in Table 4, ethnicity was not retained in the multivariable Cox regression analysis but disease activity damage, poverty, and older age were found to significantly predict mortality; these results are consistent with those of our previously published analyses (23).

thumbnail image

Figure 1. Kaplan-Meier survival curves for LUMINA (LUpus in MInorities, NAture versus nurture) patients as a function of ethnic group (log rank = 9.687; P = 0.021). * Recruited at different times over the life of the LUMINA cohort.

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Table 4. Multivariable Cox proportional hazard regression analysis of mortality at 10 years in LUMINA (LUpus in MInorities, NAture versus nurture) patients*
VariableOdds ratio95% confidence intervalP
  • *

    SLAM-R = Systemic Lupus Activity Measure revised; SDI = Systemic Lupus International Collaborating Clinics/American College of Rheumatology Damage Index.

  • P values ≤0.05 are noted.

  • Caucasian is the reference group.

  • §

    As per US federal government guidelines.

Age1.0241.003–1.0460.023
Male sex1.2790.572–2.858 
Ethnicity   
 Texan Hispanic1.1930.536–2.657 
 Puerto Rican Hispanic0.3290.041–2.536 
 African American0.8790.415–1.863 
Poverty§2.1091.236–3.5170.006
SLAM-R score at baseline visit1.1441.103–1.186< 0.001
SDI score at baseline visit1.1861.016–1.3860.031

DISCUSSION

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

SLE is undoubtedly a disease in which health disparities, as defined by the NIH (1), are clearly present because it affects primarily one sex (women), young persons (reproductive age), and less-privileged individuals (ethnic minorities) in the US and around the world. Any of these areas could be elaborated further, but we have chosen to emphasize primarily health disparities in lupus in relation to ethnicity. Given that LUMINA is a multiethnic cohort we had the opportunity to compare and contrast data from patients of the 3 main US ethnic groups: Caucasians, African Americans, and Hispanics; in addition, we provide data for 2 Hispanic subgroups, those inhabiting the island of Puerto Rico and those of Mexican origin (the most frequent country of origin for all US Hispanics) recruited primarily in Texas. Inclusion of Hispanics when examining health disparities is quite relevant because they constitute the nation's largest (14% of the total population not including the 3.9 million residents of Puerto Rico) and fastest growing ethnic minority. In fact, by July 2004 there were more than 41 million Hispanics; by the year 2020 this figure is expected to reach 60 million (24).

As the data from the literature (25–28) and from the LUMINA cohort illustrate (9, 10, 13, 19, 21), there are substantial differences in disease onset, features, course, and outcome among patients with SLE from the major US ethnic groups, with Hispanic patients (particularly of Mexican ancestry [residents of Texas], but not of Puerto Rican ancestry) and African American patients exhibiting, overall, more serious disease at a younger age and with worse intermediate and final outcomes. Given that these 2 groups are also more socially disadvantaged, a clear picture as to what the underlying causes for these disparities are is difficult to draw. We attempted, based on the data presented, to build an explanatory model for the discrepancies observed (Figure 2); this model could be regarded as a template in which additional factors or variables are identified as further research is conducted and in which strategies that can modify these factors are built.

thumbnail image

Figure 2. Disease course and outcome in systemic lupus erythematosus (SLE): genetic and nongenetic factors account for differences observed between ethnic groups. * Nongenetic factors (and to a lesser extent genetic factors) are also operative during the course of the disease (see text).

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In its most simplistic manner, the natural course of SLE can be regarded as a continuum in which as the disease begins, the patient will experience different clinical manifestations; as time goes on, the patient will undergo periods of disease activity that may or may not be followed by damage in different organ systems (due to either the disease or treatments). Ultimately, the patient may succumb earlier than if lupus had not supervened.

For those that regard race as a purely biologic construct, the basis for the disparate outcomes observed are due to the genetic differences between ethnic groups. However, as pointed out by Lander et al (29), we now know that there is marked genetic homogeneity within humans; in fact, 99.9% of DNA is identical among all humans with the remaining 0.01% accounting for their differences. In contrast, ethnicity is not only a biologic construct, but also a social construct. An ethnic group is not defined by its anthropomorphic features (included in the now discredited notion of race), but rather by its common geography, history, language, culture, and values (30–34); furthermore, the ethnic groups inhabiting the US are not entirely homogenous in terms of their genetic features as our admixture data clearly show (17, 20). Therefore, the variance that is explained by ethnicity in multivariable models of outcome has a clear socioeconomic (nongenetic) component and a biologic (genetic) component, which influence each other, as shown in Figure 2. The tight relationship between genetic and nongenetic factors occurs throughout the course of the disease, although Figure 2 depicts their impact as occurring only at disease onset. Early in the disease, purely genetic factors appear quite important, whereas as time goes on that is not the case; socioeconomic factors, on their broadest sense, achieve prominence. We have consistently shown, for example, that disease activity, whether at disease onset, at enrollment into the cohort, or over the disease course, is of greater magnitude in Texan Hispanics and African Americans. Early in the disease, a purely genetic component explains to a certain extent the greater levels of disease activity among these ethnic groups (13). As time passes, the purely genetic factors initially identified are no longer singled out; instead, maladaptive coping strategies, lack of health insurance, and inadequate social support emerge as important contributors of this intermediate disease outcome (18).

African Americans and Texan Hispanics also tend to experience renal disease more frequently than Caucasians and Puerto Rican Hispanics (19). Although environmental factors can trigger the onset of renal involvement, the fact that once it occurs these 2 groups also tend to progress to permanent renal damage more frequently than the other 2 groups supports the biologic (genetic) basis for such progression (35–37). It is, however, increasingly recognized that the progression to renal damage may be accelerated by purely socioeconomic factors (inequalities in access and adherence to care) (19, 38, 39), which may result from the social environment in which patients experience their disease, as well as from psychosocial factors that may lead some patients to inadequate coping strategies and pernicious health behaviors.

In multivariable models of damage, poverty emerges as an important added factor to ethnicity; having more severe lupus (for example, in terms of more disease activity) places minority individuals in a precarious position from the outset. Their overall poor socioeconomic status including less structured families, fewer years of formal education, higher levels of poverty, and inadequate health insurance may act not in an additive manner but in a synergistic manner over the years to account for the negative intermediate and final disease outcomes we observe among these patients. The Puerto Rican Hispanics offer an interesting experience that distinguishes them from the Texan Hispanics. Despite their high proportions of Amerindian and African ancestries and their high levels of exposure to ultraviolet B light (40), Puerto Rican Hispanics tend to have a less serious disease; they also have a higher socioeconomic status than the Texan Hispanics, with nearly universal federally mandated access to health care and more years of formal education than the Caucasian majority in the continental US. Moreover, even though Puerto Rico is a US commonwealth, it is also a country in its own right. Many of the Texan Hispanics are recent immigrants (and probably many of them also illegal), which is not the case for the Puerto Ricans; having an illegal immigrant status is, with all probability, an additional factor negatively affecting the outcome of lupus among the Texan Hispanics. Unfortunately, we have not been able to explore this construct. However, low levels of acculturation per se, as would be the case with illegal immigrants, was not found to be associated with higher levels of disease activity (41). Furthermore, given that Puerto Ricans are residing in their place of origin and are not immigrants, they are probably less likely to feel discriminated against than the Texan Hispanics, particularly when dealing with the health care system. Overall, the odds are in favor of the Puerto Rican Hispanics to experience better intermediate and long-term outcomes; in fact, with their inclusion in LUMINA they have become, in many cases, the reference group in different multivariable exploratory analyses because they distinguish themselves from all other groups, Caucasians included. Finally, it goes without saying that the data generated from our LUMINA Hispanic patients cannot be generalized to all other Hispanic subgroups within or outside the US because their characteristics, both genetic and nongenetic, may substantially differ from the groups we have studied.

Further supporting the important role of environmental, socioeconomic/demographic, and psychosocial factors as determinants of the ethnic differences in SLE outcome is our mortality data. As noted in Figure 1, the difference between survival curves as a function of ethnicity is statistically significant. However, in multivariable models, poverty (and not ethnicity) consistently emerges as an independent contributor of this ultimate outcome. Of course, it is possible that in some patients the biologic component of ethnicity, rather than its socioeconomic component, may be the most important. All things considered, poverty and, to a lesser extent, inadequate coping strategies, damage accrued, disease activity, and age drive the mortality outcome. Furthermore, the biologic and nonbiologic basis of poverty including chronic stress, associated depression, and access and adherence to health care should be considered and explored (42–45).

As valuable as we believe the LUMINA cohort is, it is by no means perfect. First, some of the LUMINA patients have been recruited from tertiary referral centers; therefore, the data generated may not be fully applicable to community lupus patients. It should be pointed out, however, that at least for the African American and Caucasian patients, the LUMINA data are consistent with data reported in the literature (6, 46, 47). Second, the retention rate of LUMINA cohort members has not been uniform across the different ethnic groups, with African Americans having the highest rate of being lost to followup, which may differentially compromise the assumptions made about the longitudinal data (48). Finally, because the LUMINA protocol has evolved over a number of years, some constructs that had not been initially explored have been added (self-efficacy for example) (49); however, because data on these constructs are not available in all patients from the outset, they have been of limited use in multivariable models of outcome, because a significant number of patients are excluded when these constructs are part of the analyses. Measures to include a higher proportion of community-based patients and to improve the retention rates of those at risk of being lost to followup are now being implemented.

In the explanatory model depicted in Figure 2, are there specific points for the development of effective interventions aimed at modifying these disparities? Primary prevention is not yet possible in SLE, given its poorly understood etiology. Once the disease begins, however, where can we intervene to substantially alter the poor outcomes observed among ethnic minority patients? From a clinical viewpoint, African American and Hispanic patients, particularly those in the continental US, with an overall poor socioeconomic status should be considered at very high risk of having poor outcomes. As important as genetic factors are throughout the course of the disease, no interventions are yet available to modify them. Improving a patient's income or improving health care access in the current sociopolitical environment is not possible. Therefore, efforts should be directed at intervening on modifiable socioeconomic/demographic and psychosocial factors (50). The primary focus should be on educating these high-risk patients about the nature of their disease and the importance of adequately controlling the disease, while at the same time attempting to improve the patient's social network and his or her coping strategies. The charge should not be for the patients alone, but rather a team effort in which physicians, patients, and patients' families work together to maintain the disease in remission, so that premature death or undesirable organ system damage that may ultimately affect the patients' quality of life do not supervene.

As to which is the best method to deliver these educational and psychosocial interventions is not settled. In fact, regardless of whether such interventions have been delivered via telephone, the Internet, or other method, the intervention group has always exhibited a better outcome than the control group (51–55). Printed materials available from different sources may also be used, but they may not be tailored to the targeted population (language, literary level) (56), limiting their usefulness. Although the World Wide Web has information that is readily accessible, it is of varying quality and, often times, misleading; moreover, high-risk patients may have limited access to the World Wide Web or limited abilities to comprehend what they may find there. Therefore, improving outcomes among these patients with lupus has to be achieved one patient at a time; this can only be done in the context of the physician-patient encounter. Of course, these measures may be insufficient to achieve the desired outcome, unless simultaneous actions aimed at closing the gap between the rich and the poor are also implemented. As clinicians, however, we cannot wait for changes to occur at the societal or political levels, but those preventive and educational activities are certainly within our reach. Taking these actions, we would assist our patients at risk of losing years of life and/or important organ function.

Further research into the interplay of genetic and nongenetic factors is a priority if the basis for the disparities observed among patients with lupus is to be understood. To further examine the biologic component of ethnicity, admixture should be considered in multivariable models of outcome; furthermore, admixture can now be ascertained in a more accurate manner than in the past, given the strides made in both genotyping (many more ancestral markers can now be examined) and in computational genetics. LUMINA investigators are committed to pursuing these studies searching for the logical explanations and the proper solutions for the health disparities observed.

AUTHOR CONTRIBUTIONS

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

Dr. Alarcón 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 design. Fernández, Calvo-Alén, Andrade, Reveille, Alarcón.

Acquisition of data. Fernández, Vilá, Reveille, Alarcón.

Analysis and interpretation of data. Fernández, McGwin, Reveille, Alarcón.

Manuscript preparation. Fernández, Calvo-Alén, Reveille, Alarcón.

Acknowledgements

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

The authors would like to acknowledge all LUMINA patients, without whom this study would have not been possible; our supporting staff (Martha L. Sanchez, MD, MPH, Mandar Apte, MD, and Ellen Sowell at the University of Alabama at Birmingham; Carmine Pinilla-Diaz, MT, at the University of Puerto Rico; and Robert Sandoval, BA, and Binh Vu, BS, at the University of Texas at Houston) for their efforts in securing our patients' followup and performing other LUMINA-related tasks; and Mrs. Maria Tyson, AA, for her expert assistance in the preparation of this manuscript. Special thanks to Jeffrey M. Roseman, MD, PhD, MPH, Isabel Scarinci, PhD, José R. Fernández, PhD, and our reviewers and editors for their most helpful comments.

REFERENCES

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