A Multiethnic, Multicenter Cohort of Patients WithSystemic Lupus Erythematosus (SLE) as aModel for the Study of Ethnic Disparities in SLEMONICA FERNANDEZ,1 GRACIELA S. ALARCON,1 JAIME CALVO-ALEN,1 ROSA ANDRADE,1

GERALD McGWIN, JR.,1 LUIS M. VILA,2 AND JOHN D. REVEILLE,3 FOR THE LUMINA STUDY GROUP

Objective. To examine health disparities as a function of ethnicity using data from LUpus in MInorities, NAture versusnurture (LUMINA), a longitudinal study of patients with systemic lupus erythematosus (SLE); to build an explanatorymodel 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 AfricanAmerican, Hispanic (from Texas), Hispanic (from Puerto Rico), or Caucasian ethnicity were studied. In addition toexamining the basic features of the cohort, we examined, by univariable and multivariable analyses, the factorsassociated with disease activity, damage accrual, lupus nephritis, and mortality. An empiric model based on the datapresented (and the literature reviewed) was derived to explain the disparities observed.Results. There were substantial differences in the socioeconomic/demographic, clinical, and genetic features amongpatients from the different ethnic groups, with Texan Hispanic and African American patients exhibiting overall a lowersocioeconomic status, different genetic associations, more serious disease at a younger age, and worse intermediate andfinal outcomes than the Caucasian and Puerto Rican Hispanic patients. A model of disease outcome as a function of thedisparities observed was created.Conclusion. Ethnic disparities occur in SLE. Environmental, socioeconomic/demographic, psychosocial, genetic, andclinical factors play an important role as determinants of the ethnic differences observed. Measures aimed at eliminatingthese disparities are suggested while further research is conducted to elucidate the basis of these disparities and theirchanges at the societal level and to eliminate the gap between the rich and the poor.

KEY WORDS. Systemic lupus erythematosus; Ethnicity; Disparities; LUMINA.

INTRODUCTION

Health disparities, as defined by the National Institute ofHealth (NIH) Working Group on Health Disparities, denotedifferences in the incidence, prevalence, mortality, andburden of disease and other health conditions that existamong distinct population groups in the US (by virtue oftheir age, race/ethnicity, sex, sexual orientation, or othercharacteristics) (1). Health disparities within different

ethnic groups have been observed in musculoskeletal dis-orders (2–6), but whether these disparities relate to geneticor environmental factors or a combination of both has yetto be defined. Systemic lupus erythematosus (SLE), a dis-ease that preferentially and more seriously affects women,ethnic minorities, and young persons, can serve to studythe basis of these health disparities. Utilizing data fromLUMINA (LUpus in MInorities, NAture versus nurture), alongitudinal study of outcome in patients with SLE, we

Supported by the NIH (grants R01-AR42503 from the Na-tional Institute of Arthritis and Musculoskeletal and SkinDiseases, M01-RR02558 from the General clinical ResearchCenters to the University of Texas Health Science Center atHouston, and M01-RR00032 to the University of Alabama atBirmingham), an RCMI Clinical Research InfrastructureInitiative (award 1-P20-RR-11126 to the University ofPuerto Rico), the Mary Kirkland Scholar Award Program,and Fellowships from Rheuminations, Inc. (University ofAlabama at Birmingham).

1Monica Fernandez, MD, ScD, Graciela S. Alarcon, MD,

MPH, Jaime Calvo-Alen, MD, Rosa Andrade, MD, GeraldMcGwin, Jr., MS, PhD; The University of Alabama at Bir-mingham; 2Luis M. Vila, MD: University of Puerto RicoMedical Sciences Campus, San Juan; 3John D. Reveille, MD:University of Texas Health Science Center at Houston.

Address correspondence to Graciela S. Alarcon, MD,MPH, 830 Faculty Office Tower, 510 20th Street South, Bir-mingham, AL 35294-3408. E-mail: graciela.alarcon@ccc.uab.edu.

Submitted for publication April 28, 2006; accepted inrevised form August 23, 2006.

Arthritis & Rheumatism (Arthritis Care & Research)Vol. 57, No. 4, May 15, 2007, pp 576–584DOI 10.1002/art.22672© 2007, American College of Rheumatology

SPECIAL ARTICLE: DISPARITIES IN RHEUMATIC DISEASES

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built an explanatory model of how ethnic disparities occurand suggested points at which interventions can be devel-oped; such interventions may result in effectively mini-mizing and even eliminating these disparities. To betterunderstand this model, we will first briefly describe somesalient features of this cohort.

PATIENTS AND METHODS

LUMINA is a multiethnic (Hispanic [Mexican or PuertoRican ancestry], African American, or Caucasian ethnic-ity), multicenter (the University of Alabama at Birming-ham, the University of Texas Health Science Center atHouston, and the University of Puerto Rico Medical Sci-ences Campus) cohort of patients with SLE (meeting theAmerican 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 PuertoRico, where recruitment started in 2001. The institutionalreview boards of all centers approved the study; writteninformed consent was obtained from each patient accord-ing to the declaration of Helsinki.

Visits are conducted at entry into the cohort (T0), every6 months for the first year, and yearly thereafter. Time ofdiagnosis (TD) is the time at which patients meet 4 ACRSLE classification criteria (7). Disease duration is the in-terval between TD and T0. The cohort includes prevalentcases (�6 months since TD) and incident cases (�6months since TD) in a 2:1 proportion (9). The LUMINAdatabase is comprehensive and includes socioeconomic/demographic, clinical, immunologic, genetic, psychologi-cal, and behavioral variables. Disease activity and damageaccrual are assessed using the revised Systemic LupusActivity Measure (SLAM-R) (11) and the Systemic LupusInternational Collaborating Clinics/American College ofRheumatology Damage Index (SDI) (12), respectively.

RESULTS

Characteristics of the cohort. As of January 2006, theLUMINA cohort consisted of 617 patients: 117 (19%) were

Hispanics from Texas (primarily of Mexican ancestry), 103(17%) were Hispanics from Puerto Rico, 221 (36%) wereAfrican American, and 176 (28%) were Caucasian. Themajority of the patients were women (90%). As shown inTable 1, Hispanics from Puerto Rico and Caucasians wereolder at T0 and had an overall better socioeconomic status(education, income, housing, marital status, and healthinsurance) than the Hispanics from Texas and the AfricanAmericans. These socioeconomic/demographic data werecomparable with those reported in previous publications(9,10,13).

Salient clinical features. Selected clinical features aresummarized in Table 2. As published previously (14,15)and confirmed in the present study, African Americansand Texan Hispanics tend to have more serious diseasecompared with Caucasians and Puerto Rican Hispanics.For example, African Americans and Texan Hispanics ex-hibit acute disease onset and renal involvement more fre-quently. They also exhibit shorter disease duration and ashorter time to the accrual of 4 ACR criteria.

Medication use is depicted in Table 2. Differences inmedication use were noted, with Puerto Rican Hispanicsand Caucasians using hydroxychloroquine more fre-quently than Texan Hispanics and African Americans(84%, 83%, 61%, and 62%, respectively; P � 0.001); thereverse occurred with glucocorticoids and cyclophospha-mide.

Genetic features. The frequency distribution ofHLA–DR and HLA–DQ alleles was reexamined, and re-sults were consistent with previously published data(9,16). In short, when compared with local controls, HLA–DRB1*0301 was found to be increased only in Caucasianpatients, whereas HLA–DRB1*1503 was found to be in-creased only in African American patients. HLA–DRB1*08was found to be increased in Hispanic patients from Texas,but not Hispanic patients from Puerto Rico; HLA–DQB1*0201 was found to be more frequent in Caucasiansand HLA–DQB1*0602 more frequent in African Ameri-cans. These data confirm the genetic difference between

Table 1. Selected baseline socioeconomic/demographic features of LUMINA (LUpus in MInorities, NAture versusnurture) patients*

Variable

Hispanic

African American(n � 221)

Caucasian(n � 176) P

Texan(n � 117)

Puerto Rican(n � 103)

Female sex 93 95 89 85 0.032Age, mean � SD years 32.8 � 12.0 36.7 � 11.2 34.8 � 11.2 41.0 � 13.3 � 0.001Education, mean � SD years 10.5 � 3.2 14.7 � 2.9 12.8 � 2.2 13.7 � 2.8 � 0.001Married/living together 54 59 33 73 � 0.001Health insurance 50 99 81 87 � 0.001Poverty† 42 30 45 15 � 0.001Home ownership 53 78 50 71 � 0.001Exercise 40 29 46 43 0.041Smoking 12 6 14 20 0.010Drinking 9 3 9 16 0.004

* Values are the percentage unless otherwise indicated.† As defined by the US federal government guidelines (57).

Disparities in SLE 577

the 2 Hispanic subgroups, and between the Hispanic sub-groups and patients from the other 2 ethnic groups.

The frequency distribution of the Fc gamma receptor(FCGR) alleles was examined. Caucasian patients tendedto exhibit the homozygous high-affinity FCGR3A genepolymorphism (FCGR3A*GG) more frequently comparedwith all other ethnic groups (16.1% versus 4.8% for TexanHispanics, 5.8% for Puerto Rican Hispanics, and 8.4% forAfrican Americans; P � 0.001); however, no differenceswere found in the distribution of FCR2A between thedifferent ethnic groups. The FCGR3B gene NA2 homozy-gous polymorphism was found to be less frequent amongTexan Hispanics than the other ethnic groups (15.7% ver-sus 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 informa-tive markers (AIMs), or genes that are differentially ex-pressed among founding populations (African, European/Caucasian, and Amerindian for the US) (17), and we foundsubstantial heterogeneity within ethnic groups. For exam-ple, Texan Hispanics exhibit a much larger proportion ofAmerindian ancestry (48%), followed by Puerto Rican His-panics (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 an-cestral genes from the other founding population; there-fore, categorizing patients by ethnic group, even whenrequiring all 4 grandparents to be of the same group, is animperfect manner to account for the role genetic factorsmay exert in the expression of the disease in patients fromdifferent ethnic groups. Admixture should, therefore, beconsidered an adjustment variable in all analyses.

Disease activity. As noted in Table 3, Texan Hispanicand African American patients exhibited higher diseaseactivity than Caucasian and Puerto Rican Hispanic pa-

tients as measured by the SLAM-R and the physicianglobal assessment. In contrast, African Americans andCaucasians assessed their disease as being more activecompared with both Hispanic groups, although the differ-ences were not significant. The discrepant perception ofdisease activity between patients and physicians may in-fluence patients’ behaviors.

Recently, we examined the factors predictive of persis-tently high disease activity (18). A total of 2,066 patientvisits were examined. Younger age, African American andTexan Hispanic ethnicities, abnormal illness-related be-haviors, poor social support, lack of health insurance, andhigh levels of disease activity in the previous visit emergedas variables predictive of subsequent high disease activity.Interestingly, genetic markers (HLA, FCGR, and AIMs)were not associated with this outcome even when previ-ous disease activity was excluded from the original model(because disease activity early in the disease had beenfound to be negatively associated with HLA–DRB1*0301).

Lupus nephritis. As noted in Table 2, renal involve-ment at T0 (and during the disease course) occurred morefrequently in the African American patients (62%) andTexan Hispanic patients (62%) than in the Caucasian pa-tients (25%) and Puerto Rican Hispanic patients (26%). Inmultivariable analyses, after adjusting for total disease du-ration, these 2 ethnicities were of borderline statisticalsignificance whereas not being married, the number ofACR criteria, the presence of thrombocytopenia, and thepresence of anti–double-stranded DNA and anti-Smith an-tibodies were found to predict the occurrence of nephritis(data not shown). These analyses are consistent with thoseperformed prior to the inclusion of Puerto Rican Hispanicpatients in LUMINA (19), the exception being that thePuerto Rican Hispanics became the reference group in thepresent analysis.

Table 2. Selected baseline clinical features of LUMINA (LUpus in MInorities, NAture versus nurture) patients*

Variable

Hispanic

African American(n � 221)

Caucasian(n � 176) P†

Texan(n � 117)

Puerto Rican(n � 103)

Disease duration, mean � SD months‡ 16.4 � 16.0 19.2 � 15.7 16.3 � 16.5 17.7 � 15.6Number of ACR criteria, mean � SD 5.6 � 1.3 5.0 � 0.9 5.7 � 1.5 5.2 � 1.1 � 0.001Time to accrual of 4 ACR criteria,

monthsMean � SD 17.7 � 39.9 26.9 � 36.9 29.1 � 63.7 42.9 � 61.7 0.001Median (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 onset 27 4 17 9 � 0.001Renal involvement§ 62 26 62 25 � 0.001Glucocorticoid average dose,

mean � SD mg10.6 � 19.2 10.4 � 14.1 12.9 � 18.5 5.9 � 11.7 � 0.001

Glucocorticoid use¶ 91 84 95 86 0.005Hydroxychloroquine use¶ 61 84 62 83 � 0.001Azathioprine use¶ 10 19 17 13Cyclophosphamide use¶ 21 8 18 13 0.025

* 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.

578 Fernandez et al

To further examine the role that genetic factors mayhave in the occurrence of nephritis, we recently includedthe admixture data in the model. A total of 150 patientswith renal involvement were compared with 309 patientswho did not have renal involvement. Patients with renalinvolvement had larger proportions of African and Amer-indian ancestral genes than patients without renal involve-ment. In multivariable models, 36.8% of the variance wasaccounted for by admixture, 14.5% by socioeconomic sta-tus, and 12.2% by admixture and socioeconomic statuscombined. However, 45.9% of the variance in the modelremained unexplained (20). These data suggest that ge-netic factors are more important determinants of renalinvolvement than the socioeconomic factors.

Damage. As reported earlier (n � 258 patients) (21), halfof the current cohort of patients had yet to accrue anydamage at T0. As shown in Table 3, the SDI score washigher at T0 in the African Americans compared with allother ethnic groups; however, at the last visit the TexanHispanics had caught up with the African Americans andboth groups had accrued more damage than patients in theother 2 ethnic groups. In fact, when only patients who hadyet to accrue any damage were examined, the Texan His-panics, followed by the African Americans, were the onesaccruing any damage at a faster pace (22).

We examined the variables predictive of damage accrualand compared these results with data from analyses per-formed prior to the inclusion of the Puerto Rican Hispan-ics (21). Given the distribution of the damage scores, aPoisson multivariable analysis was performed, adjustingfor total disease duration. Variables found in both sets ofanalyses included age, Texan Hispanic ethnicity, poverty,number of ACR criteria met, disease activity at TD, and themean dose of glucocorticoids (P � 0.001 for all). Addition-ally, African American and Caucasian ethnicities weresignificantly associated with increased risk of damage ac-

crual (P � 0.001) when compared with the Puerto RicanHispanics.

Mortality. Five- and 10-year survival analyses have re-cently been performed (10-year rates are not available forthe Puerto Rican Hispanics due to their late recruitment).As shown in Figure 1, the 5-year survival rates were lowerfor Texan Hispanics (86.9%) and African Americans(89.8%) than for Caucasians (93.6%) and Puerto RicanHispanics (97.2%); these differences were significant (logrank � 9.687, P � 0.021). As noted in Table 4, ethnicitywas not retained in the multivariable Cox regression ana-lysis but disease activity damage, poverty, and older agewere found to significantly predict mortality; these resultsare consistent with those of our previously published ana-lyses (23).

DISCUSSION

SLE is undoubtedly a disease in which health disparities,as defined by the NIH (1), are clearly present because itaffects primarily one sex (women), young persons (repro-ductive age), and less-privileged individuals (ethnic mi-norities) in the US and around the world. Any of theseareas could be elaborated further, but we have chosen toemphasize primarily health disparities in lupus in relationto ethnicity. Given that LUMINA is a multiethnic cohortwe had the opportunity to compare and contrast data frompatients of the 3 main US ethnic groups: Caucasians, Af-rican Americans, and Hispanics; in addition, we providedata for 2 Hispanic subgroups, those inhabiting the islandof Puerto Rico and those of Mexican origin (the mostfrequent country of origin for all US Hispanics) recruitedprimarily in Texas. Inclusion of Hispanics when examin-ing health disparities is quite relevant because they con-stitute the nation’s largest (14% of the total population notincluding the 3.9 million residents of Puerto Rico) and

Table 3. Disease activity and damage accrual in LUMINA (LUpus in MInorities, NAture versus nurture) patients*

Variable

Hispanic

African American(n � 221)

Caucasian(n � 176) P†

Texan(n � 117)

Puerto Rican(n � 103)

SLAM-R score at baseline visit 11.1 � 6.4 6.8 � 4.0 11.1 � 6.5 7.7 � 4.1 � 0.001SLAM-R score at last visit 9.4 � 6.0 5.4 � 3.3 8.5 � 5.8 5.5 � 4.4 � 0.001SLAM-R score over time 7.6 � 4.4 7.6 � 3.9 8.4 � 5.1 8.1 � 4.3Physician global assessment of disease

activity at baseline‡2.6 � 2.4 1.1 � 1.1 3.1 � 2.3 2.1 � 1.6 � 0.001

Patient global assessment of diseaseactivity at baseline‡

3.4 � 3.0 3.5 � 2.8 3.9 � 3.0 3.8 � 2.6

Discrepancy at baseline§ 0.8 � 2.8 2.3 � 2.6 0.8 � 3.0 1.7 � 2.7 � 0.001SDI �0 at baseline visit, % 37 23 49 40 � 0.001SDI �0 at last visit, % 70 35 74 58 � 0.001SDI at baseline 0.6 � 1.0 0.3 � 0.6 1.0 � 1.4 0.7 � 1.1 � 0.001SDI at last visit 2.2 � 2.6 0.5 � 0.9 2.3 � 2.5 1.4 � 1.7 � 0.001

* Values are the mean � SD unless otherwise indicated. SLAM-R � Systemic Lupus Activity Measure revised; SDI � Systemic Lupus InternationalCollaborating 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.

Disparities in SLE 579

fastest growing ethnic minority. In fact, by July 2004 therewere more than 41 million Hispanics; by the year 2020 thisfigure is expected to reach 60 million (24).

As the data from the literature (25–28) and from theLUMINA cohort illustrate (9,10,13,19,21), there are sub-stantial differences in disease onset, features, course, andoutcome among patients with SLE from the major USethnic groups, with Hispanic patients (particularly of Mex-ican ancestry [residents of Texas], but not of Puerto Ricanancestry) and African American patients exhibiting, over-all, more serious disease at a younger age and with worseintermediate and final outcomes. Given that these 2 groupsare also more socially disadvantaged, a clear picture as towhat the underlying causes for these disparities are is

difficult to draw. We attempted, based on the data pre-sented, to build an explanatory model for the discrepan-cies observed (Figure 2); this model could be regarded as atemplate in which additional factors or variables are iden-tified as further research is conducted and in which strat-egies that can modify these factors are built.

In its most simplistic manner, the natural course of SLEcan be regarded as a continuum in which as the diseasebegins, the patient will experience different clinical man-ifestations; as time goes on, the patient will undergo peri-ods of disease activity that may or may not be followed bydamage in different organ systems (due to either the dis-ease or treatments). Ultimately, the patient may succumbearlier than if lupus had not supervened.

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

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

VariableOddsratio

95%confidence

interval P†

Age 1.024 1.003–1.046 0.023Male sex 1.279 0.572–2.858Ethnicity‡

Texan Hispanic 1.193 0.536–2.657Puerto Rican Hispanic 0.329 0.041–2.536African American 0.879 0.415–1.863

Poverty§ 2.109 1.236–3.517 0.006SLAM-R score at baseline

visit1.144 1.103–1.186 � 0.001

SDI score at baseline visit 1.186 1.016–1.386 0.031

* SLAM-R � Systemic Lupus Activity Measure revised; SDI � Systemic Lupus International Collaborat-ing Clinics/American College of Rheumatology Damage Index.† P values �0.05 are noted.‡ Caucasian is the reference group.§ As per US federal government guidelines.

580 Fernandez et al

For those that regard race as a purely biologic construct,the basis for the disparate outcomes observed are due tothe genetic differences between ethnic groups. However,as pointed out by Lander et al (29), we now know thatthere is marked genetic homogeneity within humans; infact, 99.9% of DNA is identical among all humans with theremaining 0.01% accounting for their differences. In con-trast, ethnicity is not only a biologic construct, but also asocial construct. An ethnic group is not defined by itsanthropomorphic features (included in the now discred-ited notion of race), but rather by its common geography,history, language, culture, and values (30–34); further-more, the ethnic groups inhabiting the US are not entirelyhomogenous in terms of their genetic features as our ad-mixture data clearly show (17,20). Therefore, the variancethat is explained by ethnicity in multivariable models ofoutcome has a clear socioeconomic (nongenetic) compo-nent and a biologic (genetic) component, which influenceeach other, as shown in Figure 2. The tight relationshipbetween genetic and nongenetic factors occurs throughoutthe course of the disease, although Figure 2 depicts theirimpact as occurring only at disease onset. Early in thedisease, purely genetic factors appear quite important,whereas as time goes on that is not the case; socioeco-nomic factors, on their broadest sense, achieve promi-nence. We have consistently shown, for example, thatdisease activity, whether at disease onset, at enrollmentinto the cohort, or over the disease course, is of greatermagnitude in Texan Hispanics and African Americans.Early in the disease, a purely genetic component explainsto a certain extent the greater levels of disease activityamong these ethnic groups (13). As time passes, the purelygenetic factors initially identified are no longer singledout; instead, maladaptive coping strategies, lack of healthinsurance, and inadequate social support emerge as impor-tant contributors of this intermediate disease outcome(18).

African Americans and Texan Hispanics also tend toexperience renal disease more frequently than Caucasiansand Puerto Rican Hispanics (19). Although environmental

factors can trigger the onset of renal involvement, the factthat once it occurs these 2 groups also tend to progress topermanent renal damage more frequently than the other 2groups supports the biologic (genetic) basis for such pro-gression (35–37). It is, however, increasingly recognizedthat the progression to renal damage may be accelerated bypurely socioeconomic factors (inequalities in access andadherence to care) (19,38,39), which may result from thesocial environment in which patients experience their dis-ease, as well as from psychosocial factors that may leadsome patients to inadequate coping strategies and perni-cious health behaviors.

In multivariable models of damage, poverty emerges asan important added factor to ethnicity; having more severelupus (for example, in terms of more disease activity)places minority individuals in a precarious position fromthe outset. Their overall poor socioeconomic status includ-ing less structured families, fewer years of formal educa-tion, higher levels of poverty, and inadequate health in-surance may act not in an additive manner but in asynergistic manner over the years to account for the neg-ative intermediate and final disease outcomes we observeamong these patients. The Puerto Rican Hispanics offer aninteresting experience that distinguishes them from theTexan Hispanics. Despite their high proportions of Amer-indian and African ancestries and their high levels ofexposure to ultraviolet B light (40), Puerto Rican Hispanicstend to have a less serious disease; they also have a highersocioeconomic status than the Texan Hispanics, withnearly universal federally mandated access to health careand more years of formal education than the Caucasianmajority in the continental US. Moreover, even thoughPuerto Rico is a US commonwealth, it is also a country inits own right. Many of the Texan Hispanics are recentimmigrants (and probably many of them also illegal),which is not the case for the Puerto Ricans; having anillegal immigrant status is, with all probability, an addi-tional factor negatively affecting the outcome of lupusamong the Texan Hispanics. Unfortunately, we have notbeen able to explore this construct. However, low levels ofacculturation per se, as would be the case with illegalimmigrants, was not found to be associated with higherlevels of disease activity (41). Furthermore, given thatPuerto Ricans are residing in their place of origin and arenot immigrants, they are probably less likely to feel dis-criminated against than the Texan Hispanics, particularlywhen dealing with the health care system. Overall, theodds are in favor of the Puerto Rican Hispanics to experi-ence better intermediate and long-term outcomes; in fact,with their inclusion in LUMINA they have become, inmany cases, the reference group in different multivariableexploratory analyses because they distinguish themselvesfrom all other groups, Caucasians included. Finally, it goeswithout saying that the data generated from our LUMINAHispanic patients cannot be generalized to all other His-panic subgroups within or outside the US because theircharacteristics, both genetic and nongenetic, may substan-tially differ from the groups we have studied.

Further supporting the important role of environmental,socioeconomic/demographic, and psychosocial factors asdeterminants of the ethnic differences in SLE outcome is

Figure 2. Disease course and outcome in systemic lupus erythem-atosus (SLE): genetic and nongenetic factors account for differ-ences observed between ethnic groups. * Nongenetic factors (andto a lesser extent genetic factors) are also operative during thecourse of the disease (see text).

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our mortality data. As noted in Figure 1, the differencebetween survival curves as a function of ethnicity is sta-tistically significant. However, in multivariable models,poverty (and not ethnicity) consistently emerges as anindependent contributor of this ultimate outcome. Ofcourse, it is possible that in some patients the biologiccomponent of ethnicity, rather than its socioeconomiccomponent, may be the most important. All things consid-ered, poverty and, to a lesser extent, inadequate copingstrategies, damage accrued, disease activity, and age drivethe mortality outcome. Furthermore, the biologic and non-biologic basis of poverty including chronic stress, associ-ated depression, and access and adherence to health careshould be considered and explored (42–45).

As valuable as we believe the LUMINA cohort is, it is byno means perfect. First, some of the LUMINA patientshave been recruited from tertiary referral centers; there-fore, the data generated may not be fully applicable tocommunity lupus patients. It should be pointed out, how-ever, that at least for the African American and Caucasianpatients, the LUMINA data are consistent with data re-ported in the literature (6,46,47). Second, the retention rateof LUMINA cohort members has not been uniform acrossthe different ethnic groups, with African Americans hav-ing the highest rate of being lost to followup, which maydifferentially compromise the assumptions made aboutthe longitudinal data (48). Finally, because the LUMINAprotocol has evolved over a number of years, some con-structs that had not been initially explored have beenadded (self-efficacy for example) (49); however, becausedata on these constructs are not available in all patientsfrom the outset, they have been of limited use in multiva-riable models of outcome, because a significant number ofpatients are excluded when these constructs are part of theanalyses. Measures to include a higher proportion of com-munity-based patients and to improve the retention ratesof those at risk of being lost to followup are now beingimplemented.

In the explanatory model depicted in Figure 2, are therespecific points for the development of effective interven-tions aimed at modifying these disparities? Primary pre-vention is not yet possible in SLE, given its poorly under-stood etiology. Once the disease begins, however, wherecan we intervene to substantially alter the poor outcomesobserved among ethnic minority patients? From a clinicalviewpoint, African American and Hispanic patients, par-ticularly those in the continental US, with an overall poorsocioeconomic status should be considered at very highrisk of having poor outcomes. As important as geneticfactors are throughout the course of the disease, no inter-ventions are yet available to modify them. Improving apatient’s income or improving health care access in thecurrent sociopolitical environment is not possible. There-fore, efforts should be directed at intervening on modifi-able socioeconomic/demographic and psychosocial fac-tors (50). The primary focus should be on educating thesehigh-risk patients about the nature of their disease and theimportance of adequately controlling the disease, while atthe same time attempting to improve the patient’s socialnetwork and his or her coping strategies. The chargeshould not be for the patients alone, but rather a team

effort in which physicians, patients, and patients’ familieswork together to maintain the disease in remission, so thatpremature death or undesirable organ system damage thatmay ultimately affect the patients’ quality of life do notsupervene.

As to which is the best method to deliver these educa-tional and psychosocial interventions is not settled. Infact, regardless of whether such interventions have beendelivered via telephone, the Internet, or other method, theintervention group has always exhibited a better outcomethan the control group (51–55). Printed materials availablefrom different sources may also be used, but they may notbe tailored to the targeted population (language, literarylevel) (56), limiting their usefulness. Although the WorldWide Web has information that is readily accessible, it isof varying quality and, often times, misleading; moreover,high-risk patients may have limited access to the WorldWide Web or limited abilities to comprehend what theymay find there. Therefore, improving outcomes amongthese patients with lupus has to be achieved one patient ata time; this can only be done in the context of the physi-cian-patient encounter. Of course, these measures may beinsufficient to achieve the desired outcome, unless simul-taneous actions aimed at closing the gap between the richand the poor are also implemented. As clinicians, how-ever, we cannot wait for changes to occur at the societal orpolitical levels, but those preventive and educational ac-tivities are certainly within our reach. Taking these ac-tions, we would assist our patients at risk of losing years oflife and/or important organ function.

Further research into the interplay of genetic and non-genetic factors is a priority if the basis for the disparitiesobserved among patients with lupus is to be understood.To further examine the biologic component of ethnicity,admixture should be considered in multivariable modelsof outcome; furthermore, admixture can now be ascer-tained in a more accurate manner than in the past, giventhe strides made in both genotyping (many more ancestralmarkers can now be examined) and in computational ge-netics. LUMINA investigators are committed to pursuingthese studies searching for the logical explanations and theproper solutions for the health disparities observed.

ACKNOWLEDGMENTSThe authors would like to acknowledge all LUMINA pa-tients, without whom this study would have not beenpossible; our supporting staff (Martha L. Sanchez, MD,MPH, Mandar Apte, MD, and Ellen Sowell at the Univer-sity 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) fortheir efforts in securing our patients’ followup and per-forming other LUMINA-related tasks; and Mrs. Maria Ty-son, AA, for her expert assistance in the preparation of thismanuscript. Special thanks to Jeffrey M. Roseman, MD,PhD, MPH, Isabel Scarinci, PhD, Jose R. Fernandez, PhD,and our reviewers and editors for their most helpful com-ments.

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AUTHOR CONTRIBUTIONS

Dr. Alarcon had full access to all of the data in the study andtakes responsibility for the integrity of the data and the accuracyof the data analysis.Study design. Fernandez, Calvo-Alen, Andrade, Reveille, Alar-con.Acquisition of data. Fernandez, Vila, Reveille, Alarcon.Analysis and interpretation of data. Fernandez, McGwin, Rev-eille, Alarcon.Manuscript preparation. Fernandez, Calvo-Alen, Reveille, Alar-con.

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