1Division of General Medicine, Department of Medicine, 4Division of Nephrology, Department of Medicine, and 6Department of Pathology, College of Physicians and Surgeons of Columbia University, New York, NY, 2General Medicine Division, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 3Division of Nephrology, Department of Medicine, University of Washington, Seattle, WA, 5Department of Internal Medicine, Division of Rheumatology and Clinical Immunology, University of Arkansas for Medical Sciences, Little Rock, AR and 7Division of Rheumatology, Department of Medicine, Hospital for Special Surgery, Weill Medical College of Cornell University, New York, NY, USA
Correspondence and offprint requests to: Jai Radhakrishnan, MD, PH-4124, Columbia Presbyterian Medical Center, 622 West 168th Street, New York, NY 10032, USA. Email: jr55{at}columbia.edu
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Abstract |
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Methods. A retrospective cohort study was carried out using individual and census-based neighbourhood data. Consecutive patients in urban tertiary care centres with biopsy-proven PLN were studied. The main outcome was time to doubling of serum creatinine.
Results. Among 128 patients with PLN, the percentage of patients who did not double their serum creatinine at 5 years was 67.0% (±4.8%) and at 10 years was 58.9% (±5.7%). In bivariate analyses, residence in a poor neighbourhood was positively associated with progression (P = 0.03), as was African-American and Hispanic race/ethnicity (P = 0.01). Residence in a poor neighbourhood remained associated with progression of disease after adjustment for age, sex, creatinine, hypertension, cyclophosphamide treatment and race/ethnicity [relative risk (RR) 3.5, 95% confidence interval (CI) 1.211, P = 0.03]. After adjustment for poverty and insurance, the RR for African-American race/ethnicity was reduced from 3.5 to 2.7 and was not statistically associated with progression of disease in the full model (P = 0.10). A similar reduction in RR from 5.5 to 3.6 was seen for Hispanic race/ethnicity, but this retained statistical significance (P = 0.03).
Conclusions. Poverty is an important risk factor for progression of PLN, independent of race/ethnicity. Hispanics have an elevated risk similar to or greater than African-Americans. Given these findings, some of the poorer prognosis of African-American patients with PLN may result from socio-economic rather than biological or genetic factors.
Keywords: poverty; prognosis; proliferative lupus nephritis; race/ethnicity; socio-economic status; systemic lupus erythematosus
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Introduction |
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In addition, African-American race/ethnicity has predicted poor long-term outcome in PLN in two studies [7,8]. Biological factors, e.g. genetic polymorphisms more prevalent among African-Americans, have been hypothesized to affect renal survival in PLN [9]. However, the role that socio-economic status (SES) may play in the prognosis of patients with PLN was not considered in these trials. Prior studies in PLN have used insurance status as a surrogate measure of SES [1014]; however, insurance is a poor proxy for SES [15], particularly among these patients who are likely to have government insurance for SLE-related disability. Such lack of adjustment for SES may be an important omission. In the case of survival of patients with SLE, multiple studies suggested that African-Americans had a higher mortality rate than Whites, and various genetic factors were posited [6]. However, SES was found to account for these differences [16], suggesting that social and economic forces, not major underlying genetic differences, caused the observed disparities.
In the present study, we examined the effects of SES on prognosis of PLN, hypothesizing that patients with lower SES would have a worse renal outcome independent of race/ethnicity. In addition, we hypothesized that the poorer outcome among African-Americans was principally due to social and economic influences, rather than biological effects. To test this hypothesis, we compared renal outcomes among African-Americans and Hispanicsgroups with similar economic conditions in our populationwith Whites, and approximated individual SES by using census-based measures of neighbourhood poverty.
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Subjects and methods |
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Socio-economic variables
Individual-level SES data were not available for the cases in this cohort except for insurance status. As a proxy for individual-level data, we used neighbourhood-based measures of SES from census data [15]. Each case was geo-coded to a census-defined neighbourhood, based on the subjects address at the time of initial biopsy. These census-defined neighbourhoods, termed block groups, consist of 1000 residents each. Age, gender and race/ethnic-specific socio-economic data were extracted from the 1980 and 1990 US census, and variables were dichotomized. High poverty was defined as >10% of neighbourhood residents living below the Federal poverty line. Low median household income was defined as a median household income <$25 000. Low education attainment was defined as >45% of residents not completing high school, and low assets was defined as <10% of residents reporting any income from interest or dividends. This method of using neighbourhood-based SES measurements as a proxy for individual measures of SES has been validated in previous studies [15,17].
Statistical analysis
The baseline clinical, histological and demographic variables were compared across categories of race/ethnicity and tested with 2, Fischers exact test and Wilcoxon rank sum test, as appropriate. The proportion of participants reaching the end point of doubling of creatinine was compared with
2 or, when data were sparse, Fischers exact test. KaplanMeier plots were constructed, and differences by race/ethnicity and poverty were tested with the log-rank test. In addition, age-adjusted hazard ratios were calculated using a Cox proportional hazards model, stratified by centre.
Three multivariate Cox proportional hazards models were constructed. The first Socio-economic model evaluated the influence of socio-economic and insurance factors on outcome from PLN without regard to race/ethnicity. A stepwise deletion approach was employed to evaluate reproducibly all covariates, except for race/ethnicity, for inclusion into the model. In addition, age and sex were forced into the model. In a second Race/ethnicity model, race/ethnicity was substituted for socio-economic variables to evaluate the influence of race/ethnicity after adjustment for the same set of variables. In a third Combined model, socio-economic and race/ethnicity variables were included. Results of all three models are shown. Changes in standard errors were checked to evaluate for collinearity.
Hazard ratios, or relative risks (RRs), are presented with 95% confidence intervals (CIs). All P-values are two-tailed, with P < 0.05 considered statistically significant. Analyses were performed using SAS 8 (SAS Institute, Cary, NC).
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Results |
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The final cohort consisted of 128 patients, of whom 22 (17%) were African-American, 51 (40%) were Hispanic and 55 (43%) were White. Eighty-two percent of patients were female and 34% came from neighbourhoods defined as high poverty. Table 1 describes the baseline clinical and demographic characteristics of this cohort stratified by race/ethnicity. Clinical variables were generally similar across categories of race/ethnicity, but SES measures and insurance differed markedly by race/ethnicity. Neighbourhood poverty was highest and median income lowest among Hispanics. Educational attainment, measured by lack of a high school degree, was lowest among Hispanics; measures of educational attainment, however, are often unreliable among immigrant groups. Assets were lowest among African-Americans, reflecting national trends in the USA.
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Among the socio-economic variables derived from census-based neighbourhood values, high poverty was predictive of progression of PLN (RR 2.9, 95% CI 1.55.8, and Figure 2). Other socio-economic variables showed a trend towards poorer outcomes; however, none were statistically significant (Table 2).
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Multivariate analysis
Results of the Socio-economic model are shown in Table 3, first column. After adjustment for age, sex, hypertension and baseline creatinine, but without regard for race/ethnicity, living in a poor neighbourhood was associated with a 6-fold increased risk of progression of PLN (P < 0.001). Insurance status also predicted renal outcome.
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In the Combined model (Table 3, third column), living in poverty was associated with increased risk of progression of PLN, independent of race/ethnicity. However, the magnitude of the association was considerably reduced by adjustment for race/ethnicity. Insurance status was similarly associated with poor outcome, and was not affected by adjustment for race/ethnicity. In contrast, after adjustment for socio-economic factors, the magnitude of the association of African-American race/ethnicity was reduced and was no longer statistically significant (RR 2.7, 95% CI 0.98.7, P = 0.10). A similar pattern was seen for Hispanic race/ethnicity, except that it remained statistically associated with progression of PLN (RR 3.6, 95% CI 1.111, P = 0.03). Alternative models to the Combined modelincluding intravenous cyclophosphamide, including proteinuria and removing baseline creatinineproduced quantitatively similar results for socio-economic and race/ethnic variables (data not shown). Variables in the study were not severely collinear.
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Discussion |
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A strong, independent association ties low SES to morbidity and mortality from multiple diseases [18] and, in general, SES is a stronger predictor of mortality than race [19]. Among patients with SLE, several studies have found SES to be an independent predictor of morbidity and mortality, after adjustment for the effects of race/ethnicity [1014]. Therefore, the observation that poverty is associated with greater progression of PLN is consistent with a large prior literature on socio-economic influences of other diseases. Possible mechanisms may relate to differences in nutritional habits, greater stress and resultant hyper-adrenergic state [20], subsequent development of co-morbid disease and differential access to care. For example, poor patients may have greater difficulty affording all the necessary medications for treatment of SLE, and the resultant non-compliance is associated with a higher incidence of clinical nephritis in a cohort of SLE patients [21].
Despite studies suggesting that African-American race/ethnicity is associated with a poor prognosis in PLN [6,7,22], only one of these studies adjusted for any measure of SES. That study used insurance status as a marker of SES [23]. However, insurance status is not a reliable marker for SES, particularly among patients likely to have disabilities, and may change frequently over the course of time. In contrast, in the present study, we used neighbourhood-based measurements of SES derived from census data, which have been demonstrated in earlier studies to approximate individual measures of SES [15] and are predictive of multiple other diseases [17]. After adjustment for these neighbourhood measures, this study found that neither insurance status nor African-American race/ethnicity was independently associated with an adverse outcome in multivariate models.
Prior studies have hypothesized heritable genetic and biological factors related to selective pressures in Africa or between Africa and America that are more prevalent among African-Americans than Whites. For instance, Salmon et al. demonstrated that specific low binding alleles of receptors for immunoglobulin are more common in African-Americans with PLN [9], suggesting that these patients may have genetically determined deficiencies in clearing antigenantibody complexes. Other studies have demonstrated specific association between complement component deficiencies, major histocompatibility complex (MHC) class molecule alleles and SLE among various ethnic groups [24,25].
Hispanic patients with SLE have been reported to have a worse prognosis than Caucasians [16]. However, the finding that Hispanics have a similar or greater risk of progression of PLN than African-Americans has not been reported previously, to our knowledge, and requires modification of the above hypotheses. An alternative hypothesis is that African-Americans and Hispanics share the same harmful genetic and biological factors, with respect to PLN, that Whites do not harbour. Recently, Zuniga et al. found an increased frequency of low binding alleles for immunoglobulin receptors in Hispanic patients developing PLN [26]. However, Hispanics were not subject to the same environmental pressures that African slaves were, and no similar founder effect or genetic drift should be present among Hispanics in America. A second, alternative explanation is that race/ethnicity was misclassified in this study and that many persons labelled as Hispanic in this study were actually African-American. This explanation would suggest that Hispanics would have a risk intermediate between Whites and African-Americans; however, our results show that Hispanics had the highest risk of progression of PLN in bivariate and multivariate analyses. A third alternative is that African-Americans and Hispanics in this population shared social and economic conditions that predisposed to progression in PLN. Measures of SES were generally similar between African-Americans and Hispanics in this study and were much higher among Whites, consistent with this hypothesis.
Also consistent with the socio-economic hypothesis is the observation of the reductions in risks associated with both African-American and Hispanic race/ethnicities in multivariate analyses. The reductions suggest that associations of race/ethnicity with progression of PLN were confounded by poverty. Although not statistically significant, relative risks for African-Americans in the combined model still remained above the null. Because we relied on neighbourhood-level rather than individual-level data for poverty, poverty was less well measured than other variables in the analysis. Multivariate adjustment for poverty may therefore be incomplete, and it is possible that the observed multivariate risks for African-Americans and Hispanics resulted from this incomplete adjustment for poverty rather than a true association with race/ethnicity. That said, caution should be exercized when interpreting these models as causal due to the observational nature of the data, the relatively small number of subjects and the complex relationships mediating SES and race/ethnicity [27]. Cycles of poverty and their relationship to race/ethnicity suggest that treating poverty as a confounder of the relationship between race/ethnicity and diseaseor treating race/ethnicity as a confounder of the relationship between poverty and diseasemay be an oversimplification.
As a retrospective cohort analysis, the study may be biased by differential follow-up. However, less frequent follow-up among minorities or patients living in poor neighbourhoods would tend to bias estimates for these groups toward the null due to delays in or missed diagnoses of creatinine elevations. Although we selected consecutively biopsied patients at our institutions, many patients are not biopsied and not all patients in the New York area receive care at our institutions. The study was therefore not population based. This attribute may affect the generalizability of our results if biological and social factors affect progression differently among studied and non-studied patients, but should not, per se, affect the validity of the study. Changes in patterns of care over the study period may also introduce bias, although use of intravenous cyclophosphamide was included in multivariate models. Definitions of race/ethnicity are complex, and we relied on self-report or physicians report. As discussed above, misclassification, particularly of Hispanics, should bias results in the opposite direction, as observed in this study. The effect of poverty influencing disease outcome via impaired access to health care may not be valid in other industrialized countries with universal health care. The findings of this study with respect to other multiracial countries is particulary important where inhomogeneties in access to health care and poverty may influence outcome of chronic diseases such as lupus.
As with many other diseases, SES is an important risk factor for progression of PLN, independent of race/ethnicity. Given that Hispanics have an elevated risk of progression similar to African-Americans and given the results of multivariate analyses, much of the poorer prognosis of African-American patients with PLN may be due to socio-economic rather than biological or genetic factors. Indeed, the relative importance of genetic factors may be amplified by environmental factors that are associated with poverty. We believe that social and economic causes of inequity across income and race/ethnicity should be aggressively investigated and that studies that aim to find putative major genes or haplotypes to explain race/ethnic disparities should consider SES.
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Acknowledgments |
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Conflict of interest statement. None declared.
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References |
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