Income and Other Contributors to Poor Outcomes in U.S. Patients with Sarcoidosis

Abstract

Rationale: Socioeconomic factors are associated with worse disease severity at presentation in sarcoidosis, but the relative importance of socioeconomic variables on morbidity and disease burden has not been fully elucidated.Objectives: To determine the association between income and sarcoidosis outcomes after controlling for socioeconomic and disease-related factors.Methods: Using the Sarcoidosis Advanced Registry for Cures database, we analyzed data from 2,318 patients with sarcoidosis in the United States to determine the effect of income and other variables on outcomes. We divided comorbidities arising after diagnosis into those likely related to steroid use and those likely related to sarcoidosis. We assessed the development of health-related, functional, and socioeconomic outcomes following the diagnosis of sarcoidosis.Measurements and Main Results: In multivariate analysis, low-income patients had significantly higher rates of new sarcoidosis-related comorbidities (<$35,000, odds ratio [OR], 2.4 [1.7-3.3]; $35,000-84,999, OR, 1.4 [1.1-1.9]; and ≥$85,000 [reference (Ref)]) and new steroid-related comorbidities (<$35,000, OR, 1.3 [0.9-2.0]; $35,000-84,999, OR, 1.5 [1.1-2.1]; and ≥$85,000 [Ref]), had lower health-related quality of life as assessed by the Sarcoidosis Health Questionnaire (P < 0.001), and experienced more impact on family finances (<$35,000, OR, 7.9 [4.9-12.7]; $35,000-84,999, OR, 2.7 [1.9-3.9]; and ≥$85,000 [Ref]). The use of supplemental oxygen, need for assistive devices, and job loss were more common in lower income patients. Development of comorbidities after diagnosis of sarcoidosis occurred in 63% of patients and were strong independent predictors of poor outcomes. In random forest modeling, income was consistently a leading predictor of outcome.Conclusions: These results suggest the burden from sarcoidosis preferentially impacts the economically disadvantaged.

Keywords: comorbidity; healthcare disparities; sarcoidosis; socioeconomic factors.

Figure 1.

Random forest model: development of new sarcoidosis-related comorbidity. Random forest plots of analysis of variables are included in a multivariate model selected by least absolute shrinkage and selection operator for prediction of development of new sarcoidosis-related comorbidity. Higher values of “Mean Decrease Gini” reflect the increasing proportional importance of the individual variables for predicting this categorical outcome.

Figure 2.

Random forest model: development of new steroid-related comorbidity. Random forest plots of analysis of variables are included in a multivariate model selected by least absolute shrinkage and selection operator for prediction of development of new steroid-related comorbidity. Higher values of “Mean Decrease Gini” reflect the increasing proportional importance of the individual variables for predicting this categorical outcome.

Figure 3.

Random forest model: hospitalization. Random forest plots of analysis of variables are included in a multivariate model selected by least absolute shrinkage and selection operator for prediction of a patient ever being hospitalized for sarcoidosis. Higher values of “Mean Decrease Gini” reflect the increasing proportional importance of the individual variables for predicting this categorical outcome.

Figure 4.

Random forest model: Sarcoidosis Health Questionnaire (SHQ). Random forest plots of analysis of variables are included in a multivariate model selected by least absolute shrinkage and selection operator for prediction of SHQ score. Higher values of “Node Purity Increase” reflect the increasing proportional importance of the individual variables for predicting this continuous outcome.

Figure 5.

Random forest model: greatly impacts family finances. Random forest plots of analysis of variables are included in a multivariate model selected by least absolute shrinkage and selection operator for prediction of family finances being greatly or severely impacted by sarcoidosis. Higher values of “Mean Decrease Gini” reflect the increasing proportional importance of the individual variables for predicting this categorical outcome.