Abbreviations: ACR = American College of Rheumatology, ALA = African-Latin American, SLE = systemic lupus erythematosus
Systemic lupus erythematosus (SLE) is a complex auto-immune disease that may result from the interplay of genetic, hormonal, and environmental factors 12. Although its prognosis has improved remarkably in the past decades 22,23,30, it remains a potentially serious condition. Several studies have shown that some sociodemographic characteristics such as ethnicity, gender, age, income, education, and access to health care are important variables associated with the outcome of SLE 21,29,35,43,44,56,63,68,72,75,80,82. Disease activity, organ damage, infection, and treatment have also been identified as factors influencing the prognosis 2,3,13,14,19,20,39,54,57,61,71,76,77,83.
The LUMINA study has compared clinical, socioeconomic status, and disease-related variables in 3 ethnic groups in clinical centers in the United States 4–8,10,11,15,27,64,84. Important differences were detected in clinical and immunogenetic variables that could help identify associations with clinical manifestations, disease activity, and physician’s global scores. The epidemiology of SLE has been evaluated mainly in North America 2–11,21,27,29,48,54–56,64,76,77,81,84 and in some European countries 17,19,20,38–40,42,46, but little information is available from Latin America 1,16,22,23,26,36,37,41,47,49,51,52,65,79. For obvious reasons, the Latin American studies make few comparisons between ethnic groups, although some have shown a poor prognosis and a high prevalence of infections in African-Latin American (ALA) SLE patients, both of which may relate to socioeconomic variables.
Several studies from the United States have included Latin American patients, usually referring to them as “Hispanics”5–7,9–11,27,39,60,64,81,84, a term that is mainly derived from their language rather than their ethnic background, which can vary between and within Latin American countries. Notwithstanding, the so-called Hispanics in the United States have been shown to have more severe disease and poorer outcomes than whites, often equating African Americans, whose lupus tends to have poor prognosis 11,64.
Interpreting and comparing those studies has also been difficult due to the inclusion of diverse proportions of hospital patients with varying degrees of disease duration. Using a prospective cohort enables researchers to avoid under-registry of information, evaluate characteristics both at baseline and throughout the clinical course of the disease, and ascertain the influence of diverse treatment strategies and comorbid states. The incorporation of patients early after diagnosis also minimizes the exclusion of early deaths, an important variable in a chronic disease such as SLE.
These considerations were taken into account in the development of the Grupo Latinoamericano de Estudio del Lupus (GLADEL) cohort, started in 1997 as a multinational inception prospective cohort in Latin American centers having expertise in the diagnosis and management of SLE. For this task we used a computer database available to all groups and interconnected among them.
Herein we describe the cohort and the general characteristics of the first 1,214 Latin American SLE patients with recent-onset SLE incorporated into the predetermined database and followed prospectively for a mean of 20 months. We analyze the potential differences by ethnic, national, and sociodemographic variables.
PATIENTS AND METHODS
The GLADEL study held an investigator meeting in 1997 in Mexico City. During 4 days, participants developed a common protocol, consensus definitions, and selected outcome measures, and received direct training in the database software.
The 34 centers participating in the GLADEL cohort are distributed among 9 Latin American countries. To be included, they had to meet the following criteria: have experience in SLE (referral centers with a lupus clinic, an academic profile, and a rheumatology training program); have a genuine interest in the research project; and have an identified leader, as well as adequate human, technical, and communication facilities.
In order to have a balanced representation of centers in the initial cohort, each center was asked to incorporate a minimum of 20 and a maximum of 30 randomly selected patients. Randomization was done locally in each center. The first patients were entered in October 1997, and to insure their recent onset they could only be included if the diagnosis of SLE had been made after 1 January 1996 by a rheumatologist or a qualified internist with experience in SLE. Fulfillment of 4 American College of Rheumatology (ACR) 1982 SLE criteria 73 at the time of diagnosis was not mandatory. After incorporating the initial 30 patients, each group continued to include 1 new randomly selected patient per month diagnosed within the previous 2 years.
All groups started using ARTHROS 2.0 58 as a common database for collection of information and moved on to the new version ARTHROS 6.0. This is a user-friendly rheumatology database developed by Argentine rheumatologists using a Windows platform. One of its many advantages is the lack of language barriers: for example, data collected in Spanish can be retrieved by an English-speaking investigator since all characteristics are coded.
In order to obtain reliable information all investigators were trained in a similar fashion. Patient data were collected by a clinician trained in the program in small groups and personalized sessions with 1 of the developers of the program. At a coordinator center, strict control and supervision of the data received was undertaken, with permanent communication with the submitting center for any queries arising.
Each patient was interviewed and her or his clinical chart information was validated. Investigators were asked to establish precisely the dates of disease onset, diagnosis, and fulfillment of ACR SLE criteria. They also were asked to capture all relevant clinical and laboratory evaluations as clinically indicated. Disease features were defined according to ACR or other well-accepted criteria 62. The clinical course can be described as seen by both patient and physician at the time of each visit (that is, same, better, worse). Disease activity using both SLEDAI 18 and MEX-SLEDAI 34 were measured in all patients at the time of entry and every 6 months thereafter. Systemic Lupus International Collaborating Clinics/American College of Rheumatology (SLICC/ACR) Damage Index for systemic lupus erythematosus 31,32 was measured yearly. All researchers followed local regulations according to their institutional review boards.
Definition of Demographic Variables
Ethnic groups: An operational definition was necessary. It was developed by consensus including an expert in immunogenetics. These definitions were determined according to the parents’ and all 4 grandparents’ self-reported ethnicity 5. Patients were questioned as to their place of birth, as well as to that of their parents and grandparents. They were thus classified as the following:
- White: individuals with all white European ancestors;
- Mestizo: individuals born in Latin America who had both Amerindian and white ancestors;
- African-Latin Americans (ALA): individuals born in Latin America with at least 1 African ancestor irrespective of whether other ancestors were white or Amerindian.
Pure Amerindians were those individuals who had all autochthonous ancestors.
Final assignment of patients was the prerogative of the clinician, who considered anthropomorphic characteristics for this.
Socioeconomic status: Socioeconomic status was evaluated using the Graffar method 33, a validated scale previously used in Latin America 78. The Graffar scale takes into account 5 variables: parent’s occupation, parent’s level of education, main source of income, housing, and neighborhood quality. Each variable has 5 categories with independent and progressive scores. A final score classifies subjects in 5 categories: high, medium-high, medium, medium-low, and low.
Type of medical care was divided into the following categories:
- Institutional: patients treated primarily in public institutions. Partial coverage: patients who receive limited support toward medical care expenses. Complete coverage: patients who have all expenses paid for. Without coverage: patients who have no economic support and have to pay for all their expenses for medical care.
- Private: patients cared for in private institutions or practice. With coverage: patients with prepaid or insurance-paid support. Without coverage: patients who pay for their private care.
Education: we considered from 0 (illiterate) up to 20 years of formal education.
Studies were done in the standard routine laboratory at each center. Autoantibodies and complement tests were performed at each center and the cutoff values were considered valid. Standardization of immunologic tests between centers is being incorporated but was not yet available at the time of the current study.
Overall comparisons of the clinical, sociodemographic, and immunologic categorical variables among the major ethnic groups (white, mestizo, ALA, and other) were performed using cross tabulations, and their significance assessed by means of the chi-square statistic. When a significant result was found, bivariated comparisons were performed to identify groups that were statistically different by the Fisher exact test. A similar analysis was applied when comparing the 3 selected ethnic groups: Argentine white, Argentine mestizo, and Mexican mestizo.
For continuous variables (age at onset; age at diagnosis; delay to diagnosis—defined as time between onset of disease and diagnosis; disease duration; follow-up; positive results in immunologic tests; and scores of SLEDAI, MEX-SLEDAI, and SLICC) the comparison between ethnic groups was established by Kruskal-Wallis test, and the comparison for 2 samples was done using Mann-Whitney U test. Thus, ethnic group was considered the main independent variable. To test the main effect of this variable over clinical outcomes, we factorized it in 2 ways. In the first, we built 3 dummy variables taking the major categories of the variable ethnic group: white vs. mestizo, white vs. ALA, and white vs. other. In the second, we established the comparison between 2 dummy variables: Argentine white vs. Argentine mestizo, and Argentine white vs. Mexican mestizo. The multivariate models were adjusted by gender (female vs. male), education (<10 yr vs. ≥10 yr), medical coverage (partial or no coverage vs. full medical coverage), age at SLE diagnosis (>27 yr vs. ≤27 yr), delay to SLE diagnosis (≥6 mo vs. <6 mo), follow-up (≥20 mo vs. <20 mo), number of hospitalizations (≥1 vs. 0), marital status (single vs. all others), socioeconomic status (lower middle/lower vs. all others), and country (Argentina vs. the rest). All these variables were entered into the models to diminish differences in the heterogeneity in both clinical and sociodemographic variables of our populations. The criterion to stratify the continuous variables was based in the median value. Clinical outcomes as dependent variables were built and tested in the different multivariate models. We showed selected models. All the multivariate analyses were conducted by means of unconditional logistic regression analysis to derive the odds ratio as association measure of the exponential of beta coefficients adjusted by multiple covariates. Multicollinearity was probed in all models by means of the covariance matrix. All statistical analyses were performed separately with SAS v. 8 70, and with SPSS/PC v. 10.0 69, and the data then compared.
Composition of the GLADEL Cohort
At the defined cutoff date of 1 January 2000, the GLADEL cohort included 1,214 patients from 34 centers from 9 Latin American countries. Table 1 shows the gender and ethnic distribution by country of origin. Ninety percent of the patients were female, without differences between countries or ethnic groups. There were 537 mestizos (44%), 507 whites (42%) and 152 ALA (13%). There were small numbers of pure Amerindian and oriental individuals. Whites predominated in Argentina and Cuba and to a lesser degree in Brazil. Mestizos predominated in Guatemala, Mexico, and Peru. ALA patients were more prevalent in Venezuela, Brazil, and Colombia.
Table 2 shows the sociodemographic characteristics of the GLADEL cohort as found in the 3 major ethnic groups. Although most patients lived in urban areas, mestizos lived significantly more frequently in rural areas than did whites (13.5% vs. 5.3%; p = 0.0001) or ALA. There were no differences in marital status between groups. Significant differences were detected in socioeconomic status, type of medical care, and level of formal education favoring white patients. Mestizos showed better socioeconomic status and medical coverage than ALA.
Selected Epidemiologic Data
Analysis of the 3 major ethnic groups by decade of age at diagnosis is shown in Figure 1. In all 3 ethnic groups the majority was between 11 and 40 years of age. Table 3 shows that for the entire group, the mean age at disease onset was 28 years, and that at diagnosis was 30. The median delay to diagnosis was 6 months. The median disease duration was 32 months, and the median follow-up to cutoff date was 20 months.
Mestizos and ALA were significantly younger at onset than whites. Similarly, age at diagnosis was significantly lower in ALA and mestizos than in whites. Delay to diagnosis was significantly shorter in ALA than in mestizos and whites. Disease duration (onset to last visit) was significantly shorter for ALA. However, this could reflect the later entrance of Brazil and Cuba, 2 countries with a large ALA population, into the study. Mestizos had shorter follow-up than whites, but again, this could reflect the earlier entrance of several Argentine groups.
Table 4 shows the clinical manifestations of the entire cohort both at onset and cumulative to cutoff time. All manifestations analyzed increased in frequency with follow-up. Analysis between ethnic groups was performed with the cumulative data. There were interesting differences. Fever was significantly more frequent in whites than in mestizos. Weight loss was less frequent in mestizos than in whites and ALA. Of the cutaneous manifestations, photosensitivity was less frequent in mestizos, while discoid lesions were significantly more frequent in ALA than in either whites or mestizos. On the other hand, livedo reticularis was significantly more frequent in mestizos than in ALA. Xerophthalmia and sicca syndrome were less frequent in ALA than in the other 2 groups.
Renal disease was significantly more frequent in mestizos and ALA than in whites. Other consequences of lupus nephropathy such as acute or chronic renal failure and hypertension were more frequent in mestizos than in whites, and consequently the sum of renal manifestations was also more frequent in mestizos. We observed that ALA had a significantly higher frequency of nephrotic syndrome than did whites. Interestingly, nephrotic syndrome was not significantly more frequent in mestizos than in whites.
Ethnic group was probed as a main effect in 7 different models by logistic regression multivariate analysis (Table 5). After controlling for clinical and sociodemographic variables as well as for country of origin (Argentina vs. the rest), both mestizos and ALA were statistically associated with a higher probability of lymphopenia, and renal damage mestizos, than whites. In a similar comparison, cumulative clinical damage as measured by SLICC and the probability of achieving 6 or more ACR criteria were less probable in mestizos than in whites, although without statistical significance.
Comparison of Whites and Mestizos from Argentina and Mestizos from Mexico
Because of the aforementioned clinical differences observed in the 3 major ethnic groups included in the whole cohort where we controlled by country by comparing Argentina to the rest, we decided to compare whites and mestizos from a country whose participating centers included an important proportion of both ethnic groups. Also, to determine possible differences between a major ethnic group from 2 different countries, we compared mestizos from Argentina and Mexico. The data are shown in Table 6, where sociodemographic differences of the 3 ethnic/national groups also can be seen. There were differences in some of the variables analyzed between Mexican and Argentine mestizos. Renal involvement and lymphopenia were again found to be significantly more frequent in mestizos from either country than in Argentine whites.
Multivariate models were obtained, and their results are shown in Table 7. It is interesting that mestizos had similar findings independent of their country of origin. Mestizos of either country had more renal disease and lymphopenia and lower SLEDAI, damage scores, and cumulated ACR criteria than did Argentine whites. Contradictory findings were seen in death prediction and MEX-SLEDAI scores.
A trend for higher disease activity indices was observed from ALA, to mestizos, to whites (Table 8). While there were significant differences in SLEDAI among all groups, the MEX-SLEDAI did not reach significance between mestizo and ALA patients. Stepwise multiple regression analysis produced a large predictive model for disease activity, defined as a score higher than 12 in SLEDAI and 8 in MEX-SLEDAI. Results were similar with both indices, and therefore we present only the SLEDAI data. Variables associated with higher disease activity were formal education of less than 10 years odds ratio [OR], 1.5; 95% confidence interval [CI], 1.1–1.9); partial or no medical coverage (OR, 1.4; 95% CI, 1.1–1.8), age older than 27 years (OR, 1.6; 95% CI, 1.2–2.1), time of follow-up ≥20 months (OR, 1.6; 95% CI, 1.2–2.2), delay to diagnosis ≥6 months (OR, 0.6; 95% CI, 0.5–0.8), and disease duration ≥32 months (OR, 0.7; 95% CI, 0.5–0.9).
Despite the higher frequency of renal disease and higher mean maximum disease activity indices in ALA, these patients achieved significantly lower damage scores than both mestizos and whites. In the stepwise multiple logistic analysis, damage defined as SLICC/ACR ≥ 1 was associated with medium socioeconomic status in comparison with high socioeconomic status (OR, 1.4; 95% CI, 1.1–1.9); partial or no medical coverage (OR, 1.6; 95% CI, 1.2–2.1); and disease duration (OR, 1.5; 95% CI, 1.2–2). On the other hand, urban residence was protective (OR, 0.6; 95% CI, 0.4–0.9).
Autoantibodies and Complement
Although autoantibodies and complement levels have not been tested systematically within the cohort up to now, and the results have not been subjected yet to interlaboratory control, the results give some insight into potential differences between the 3 major ethnic groups (Table 9). These should, however, be taken with caution. Antinuclear antibodies were significantly less prevalent in mestizos than in whites and ALA. Antidouble-stranded DNA antibodies were significantly more frequent in mestizos than in whites, and IgM anticardiolipin antibodies were significantly less frequent in ALA than in whites and mestizos. Both ALA and whites had low complement levels, including C3 and C4, more frequently than mestizos.
Cumulative treatment regimens are described in Table 10. Steroids were used in 92% and antimalarials in 75% of patients in the cohort. Immunosuppressive agents were received by 47% of patients with intravenous cyclophosphamide predominating, followed by azathioprine. Forty-two (3.45%) patients entered dialysis and 2 received renal transplants. When this was analyzed for the different ethnic groups, differences appeared in the use of antimalarials and immunosuppressive agents. Chloroquine was significantly more frequently used in mestizos and ALA compared with whites, and the reverse was true for hydroxychloroquine. Some of these differences may reflect cost and drug availability in our countries (ie, chloroquine is less costly). Overall immunosuppressive use was more frequent in nonwhites, particularly significant when compared with mestizos.
Thirty-four patients (2.8%) died within the GLADEL cohort. Their general characteristics are presented in Table 11. The survival rate at 4 years was 95%. Because of the small number of patients who died, we compared survival rates between whites and the rest of the cohort (nonwhites) rather than between the 3 major ethnic groups. There were no significant differences in survival rates between whites and nonwhites. However, nonwhites who died had lower age at disease onset and lower age at the time of death than whites (p = 0.05 and p = 0.03, respectively). Patients who died had lower education level, lower socioeconomic status, and poorer medical coverage. Obviously they had higher mean activity indices and SLICC/ACR scores than those who survived. The causes of death are presented in Table 12.
Mortality could be predicted in a stepwise logistic regression model by the following: education (<10 yr vs. ≥10 yr; OR, 3.2; 95% CI, 1.3–7.6), SLICC score (≥1 vs. 0; OR, 2.8; 95% CI, 1.2–6.4), time of follow-up (≥20 mo vs. <20 mo; OR, 0.26; 95% CI, 0.10–0.65), marital status (single vs. others; OR, 2.4; 95% CI, 1.0–5.7), medical coverage (partial or no coverage vs. full medical coverage; OR, 2.7; 95% CI, 1.1–6.5), and country (Argentina vs. the rest; OR, 3.0; 95% CI, 1.3–7.1).
We describe the GLADEL cohort, a multicenter, multinational, prospective inception cohort of Latin American SLE patients seen in their countries of origin and treated by their local physicians. Both the size and origin of this cohort make it unique. An effort was made to keep equilibrium so no single group with a large number of patients would predominate and introduce a bias. Data were entered into a user-friendly database that requires no writing and crosses language barriers, thus allowing participation of Portuguese-speaking groups. Throughout the study, a supervising group conducted quality control of the data entered, facilitated by built-in characteristics of the database that detect contradictions. In addition, individuals coordinating the cohort were in regular communication and had periodic meetings to set policies and define variables and terms. The ultimate size of the cohort will now be predetermined in order to have patient representation from each country according to its population.
Latin America is a large subcontinent rich in the variety of racial admixtures between and within countries. In addition, socioeconomic, educational, and demographic variations are prominent, and these sometimes are related to ethnic groups through their economic predominance. Thus, the apparent homogeneity of Latin Americans is a myth, and within the subcontinent lies great diversity. The reason for the apparent homogeneity is the predominance of 2 related languages, Spanish and Portuguese, which has resulted in the unfortunate terminology of “Hispanic” based mainly on the former language being spoken by many Latin Americans and their descendants now living in English- speaking North America.
The influences of ethnic, social, and demographic variables on the clinical characteristics of SLE patients have already been demonstrated by other studies. Thus, in series from both the United States and Europe, more severe disease was noticed in nonwhite patients 5,10,28,29,45,56,63,72,74,75,80. In our study, both ALA and mestizos had more severe disease than did whites, as evidenced by a higher frequency of renal disease, pericarditis, polyadenopathy, and discoid lesions in ALA. In addition, both ALA and mestizos had higher maximum disease activity indices than whites, but this was lost when controlled by country. However, damage scores tended to be lower in ALA than in both mestizos and whites, a surprising finding that might be explained by shorter disease duration or by the more recent incorporation of Brazilian and Cuban groups into the study. Longer follow-up in the GLADEL cohort may help determine if ethnicity does actually play a role in the resulting damage from SLE.
A peculiar observation was that of a significantly lower frequency of both xerophthalmia and sicca syndrome (both xerophthalmia and xerostomia) in ALA than in mestizos and, particularly, in whites. This was not apparently related to a lower frequency of anti-Ro and anti-La in ALA.
Mestizos and ALA had lower socioeconomic status, fewer years of formal education, and less accessibility to medical care than did whites, and these socioeconomic factors may have a bearing on the more severe disease found in nonwhites. The possible association of more severe disease and social inequalities has also been recorded in “Hispanics” in the United States 10 and North American Indians 50,53.
Possible genetic factors associated with ethnicity such as FcγRIIA gene alleles could be influencing this, since these may be a risk factor for lupus nephritis in African Americans 67. The finding made here that ALA have significantly shorter delay to diagnosis than both mestizos and whites may indicate that they have an inherently more severe disease from early onset, thus prompting earlier diagnoses despite their aforementioned deficiencies in accessibility to medical care and socioeconomic status.
Health disparities in SLE have led to the analysis of the interplay of socioeconomic status, ethnicity, education, and psychosocial and behavioral variables in contributing to poor outcome 10,25,29,43,44,56,72,82. A proposal has been made to identify mediators to target interventions designed to reduce such health disparities in SLE, and the observations recorded here and more yet to arise from the continued follow-up of the GLADEL cohort may contribute to this goal.
Physicians and health authorities in Latin America, as well as those of the United States, Canada, and European countries where Latin American individuals live, should be aware that social inequities may result in increased severity of a disease that, due to its pathogenic complexity, might seem remote from these seemingly mundane factors. It is already a well-known fact that an epidemiologic transition has occurred in Latin America, where infectious and parasitic diseases, once commonly thought to be more prevalent, have been surpassed by chronic diseases such as SLE. Interest in SLE by Latin American physicians and investigators thus is not gratuitous and is supported by the findings presented herein.
An interesting observation was obtained from the comparison between Argentine mestizos and whites and their comparison with Mexican mestizos. The geographic distance between the 2 countries and the lack of a significant migration between the 2 indicate that their resulting similarities may be truly ethnic and probably of an ancient origin, albeit influenced by socioeconomic similarities. Except for lower frequencies of polyadenopathy, serositis, and hemolytic anemia in Mexican mestizos, these tended to be more akin to Argentine mestizos than to Argentine whites.
Another interesting observation from our study resulted from multiple logistic analysis that provided a model for maximal disease activity in SLE. It included lesser formal education, partial or lack of medical coverage, older age at onset, and longer follow-up. Conversely, longer delay to diagnosis and longer disease duration seemed to have a protective effect, possibly by reflecting milder disease and a decrease in disease activity with time, respectively.
Although our cohort is still young, it is thought provoking that patients who died within the GLADEL cohort had both poorer education and poorer medical coverage than those who are still alive. As in other series 2,3,24,57,66,76,77,82, infection was an important cause of death of lupus patients in the GLADEL cohort. A bimodal mortality pattern has been shown in systemic lupus erythematosus 76. Our inception cohort has a median follow-up of 32 months. This was a limiting factor for reporting events that occur later in the disease course (second peak of mortality) such as cardiovascular mortality. The study of this would be among the objectives of continued follow-up of this cohort. In addition, SLE is a paradigm of complex disease where predisposing disease-modifying and pharmacodynamic-influencing genes interplay with environmental and hormonal factors to cause an extraordinary heterogeneity 12. Continued analysis of a cohort with the characteristics described herein, ideally with the concurrent study of participating genes, may help us to dissect and, in time, understand the role of each in its diversity. A recent observation of the association with SLE of allele A of the SNP PD-1.3 of the PD-1 gene in the 2q37.3 chromosome region in Europeans, less frequent in Mexicans and practically absent in African-Americans, suggests it to be a recent mutation affecting mostly Europeans and, to a lesser extent, populations admixed with them 59. Analyses of European populations and their admixtures within the Latin American subcontinent as included in the GLADEL cohort for associations with this and other genetic markers may help determine the role of the various lupus-predisposing genes in the clinical spectrum of SLE.
Our analysis of 3 major ethnic groups in this Latin American lupus cohort gives us further insight into the role of ethnicity and the associated social inequalities on the clinical manifestations and outcomes of lupus. We also see clearly that, at least as pertaining to SLE, “Hispanics” is not a homogenous group.
The differences between Hispanic whites, mestizos, and ALA are well recognized in patients living in Latin America. However the differences should be of particular relevance for Latin American patients living in North America or Europe, where most of these patients would be grouped together as Hispanics. The differences found in the GLADEL cohort should be helpful for diagnosis and treatment of these patients, since their clinical behavior may be different. When a physician encounters a “Hispanics” patient with SLE, further efforts to characterize his or her country of origin and ethnic background should provide useful information.
The authors express their gratitude to Daniel Wojdyla for assistance in handling the database and statistical analysis of the GLADEL cohort and to Daniel Villalba and Leonardo Grasso for assistance with the software ARTHROS 6.0.
APPENDIX: GLADEL CO-AUTHORS
Coordinators: Bernardo A. Pons-Estel and Donato Alarcón-Segovia. The following participants are members of Grupo Latinoamericano de Estudio del Lupus (GLADEL) and have incorporated at least 20 patients into the database.
ARGENTINA: Patricia M. Imamura, Sección Reumatología, Servicio de Clínica Médica Hospital Italiano, Buenos Aires; Jorge A. Manni, Sebastián Grimaudo, and Judith Sarano, Departamento de Inmunología, Instituto de Investigaciones Médicas “Alfredo Lanari”, Buenos Aires; José A. Maldonado-Cocco, Maria S. Arriola, and Graciela Gómez, Servicio de Reumatología, Instituto de Rehabilitación Psicofísica, Buenos Aires; Mercedes A. García, Ana Inés Marcos, and Juan Carlos Marcos, Servicio de Reumatología, Hospital Interzonal General de Agudos General San Martín, La Plata; Hugo R. Scherbarth, Pilar C. Marino, and Estela L. Motta, Servicio de Reumatología, Hospital Interzonal General de Agudos “Dr. Oscar Alende” Mar del Plata; Cristina Drenkard, Susana Gamron, and Carlos M. Onetti, Servicio de Reumatología, UHMI1, Hospital Nacional de Clínicas, Córdoba; Verónica Saurit, Servicio de Reumatología, Hospital Privado, Centro Medico de Córdoba, Córdoba; Norberto Quagliatto, Alberto A. Gentiletti, and Daniel Machado, Servicio de Reumatología, Hospital Provincial de Rosario, Rosario; Marcelo Abdala and Simón Palatnik, Servicio de Reumatología, Hospital Provincial del Centenario, Rosario; Guillermo Berbotto and Carlos A. Battagliotti, Servicio de Reumatología Hospital Escuela Eva Perón, Granadero Baigorria, Rosario, Argentina.
BRAZIL: Emilia Sato, Elaine M. C. Sella, and Alexandre W. S. Souza, Disciplina de Reumatología, Universidade Federal da São Paulo (UNIFESP), São Paulo; Lilian T. Lavras Costallat, Manoel Barros Bertolo, and Ibsen Bellini Coimbra, Divisao de Reumatología, Faculdade de Ciencias Medicas, Universidade Estadual da Campinas, Campinas; Eduardo Ferreira Borba Neto and Eloisa Bonfá, Divisao de Reumatología, Faculdade da Medicina, Universidade da São Paulo, São Paulo; João Carlos Tavares Brenol, Ricardo Xavier, and João Marasca, Serviço de Reumatología, Hospital da Clinicas da Porto Alegre, Universidade Federal do Rio Grande do Sul; Fernando de Souza Cavalcanti, Ângela Luzia Branco Duarte, and Cláudia Diniz Lopes Marques, Disciplina de Reumatología, Centro de Ciencias da Saúde, Universidade Federal da Pernambuco, Pernambuco; Nilzio Antonio Da Silva, Ana Carolina de O. e Silva, and Tatiana Ferracine Pacheco, Serviço da Reumatología, Faculdade de Medicina, Universidade Federal de Goias, Goiania.
COLOMBIA: José Fernando Molina-Restrepo, Servicio de Reumatología, Hospital Pablo Tobon Uribe, and Javier Molina-López, Sección de Reumatología, Universidad de Antioquia, Hospital Universitario San Vicente de Paul, Medellín; Antonio Iglesias-Gamarra, Facultad de Medicina, Universidad Nacional de Colombia, and Antonio Iglesias-Rodríguez, Servicio de Reumatología, Hospital San Juan de Dios, Facultad de Medicina, Universidad Nacional, Bogotá; Eduardo Egea-Bermejo, Departamento de Inmunología, Universidad del Norte, Barranquilla; Oscar Uribe-Uribe, Luis A. Ramírez, and Oscar Felipe, Sección de Reumatología, Universidad de Antioquia, Hospital Universitario San Vicente de Paul, Medellín; Renato A. Guzmán-Moreno and José F. Restrepo-Suárez, Departamento de Medicina Interna e Inmuno-Reumatología, Clínica Saludcoop 104 y Hospital San Juan de Dios, Facultad de Medicina, Universidad Nacional de Colombia, Bogotá.
CUBA: Marlene Guibert-Toledano, Gil Alberto Reyes-Llerena, and Alfredo Hernández-Martínez, Servicio de Reumatología, Centro de Investigaciones Médico Quirúrgicas (CIMEQ), La Habana.
CHILE: Loreto Massardo, Néstor Gareca, and Sergio Jacobelli, Departamento de Inmunología Clínica y Reumatología, Escuela de Medicina, Pontificia Universidad Católica de Chile, Santiago; Oscar J. Neira, Leonardo R. Guzmán, and María A. Alvarado, Sección Reumatología, Hospital del Salvador, Facultad de Medicina, Universidad de Chile, Santiago.
GUATEMALA: Abraham García-Kutzbach, Ivette Castro-Ampie, and Cesar Garcia, Servicio de Reumatología, Hospital Universitario Esperanza, Ciudad de Guatemala.
MÉXICO: Virginia Pascual-Ramos, Departamento de Inmunología y Reumatología, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, México DF; Leonor A. Barile-Fabris and Juan Manuel Miranda-Limón, Departamento de Reumatología, Hospital de Especialidades, Centro Médico Nacional La Raza, Instituto Mexicano de Seguro Social, México DF; Mary-Carmen Amigo and Luis H. Silveira, Departamento de Reumatología y Departamento de Bioquímica, Instituto Nacional de Cardiología Ignacio Chávez, México DF; Ignacio García De La Torre, Gerardo Orozco-Barocio, and Magali L. Estrada-Contreras, Departamento de Inmunología y Reumatología, Hospital General de Occidente de la Secretaría de Salud, Guadalajara, Jalisco; Maria Josefina Sauza del Pozo, Laura E. Aranda Baca, and Adelfia Urenda Quezada, Servicio de Reumatología, Instituto Mexicano de Seguro Social, Hospital de Especialidades No 25, Monterrey, NL; Guillermo F. Huerta-Yáñez, Servicio de Reumatología, Hospital de Especialidades Miguel Hidalgo, Aguascalientes.
PERU: Eduardo M. Acevedo-Vásquez, José Luis Alfaro-Lozano, and Jorge M. Cucho-Venegas, Servicio de Reumatología, Hospital Nacional Guillermo Almenara Irigoyen, ESSALUD, Lima; Maria Inés Segami, Cesar A. Ugarte, and Felipe E. Becerra, Servicio de Reumatología, Hospital Nacional Edgardo Rebagliatti Martins, ESSALUD, Lima.
VENEZUELA: Rosa Chacón-Díaz and Soham Al Snih Al Snih, Servicio de Reumatología, Centro Nacional de Enfermedades Reumáticas, Hospital Universitario de Caracas, Caracas; Maria H. Esteva-Spinetti and Jorge Vivas, Unidad de Reumatología, Hospital Central de San Cristóbal, San Cristóbal.
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