Introduction: Sarcoidosis is a granulomatous disease primarily affecting the lungs and thoracic lymph nodes. Many patients experience disease progression with associated morbidity and mortality. Clinical management is variable and typically initiated for progressive disease. Understanding progression and mortality patterns may help support risk-stratified care.
Objectives: The proportion of incident sarcoidosis cases with disease progression and death was determined, and the time-to-progression (TTP) from diagnosis and survival time from diagnosis was estimated.
Materials and Methods: This retrospective cohort study used Optum Clinformatics® Data Mart (2016–2023). Eligible individuals had ≥1 day of enrollment during the identification period and ≥12 months of continuous enrollment (≤30 day gap allowed). Incident cases required ≥1 inpatient diagnosis or ≥2 outpatient diagnoses of sarcoidosis on separate days within 12 months, with no prior sarcoidosis diagnosis. Controls were frequency matched 1:1 to cases by age, gender and diagnosis year and month. Disease progression was identified using claims based proxies (e.g. related tests, lung transplant, etc.); TTP was measured from the second diagnosis date to progression. Survival time from second diagnosis date was evaluated using Kaplan Meier (KM) methods. Multivariable Cox models were used to identify predictors of progression and mortality.
Results: Among 16,065 incident sarcoidosis cases, 29.80% had evidence of disease progression and 12.13% died during follow-up. Median TTP and survival time from diagnosis were not reached; KM means are reported. Mean TTP was: 54.1 months (95% CI: 53.40–54.80) (Figure 1).; mean survival time from diagnosis was 69.70 months (95% CI: 69.20–70.20) (Figure 2). Higher comorbidity burden was a significant predictor for progression (HR: 3.51, 95% CI: 3.20-3.84); progression was the strongest predictor of mortality (HR: 8.27, 95% CI: 7.46–9.17).
Conclusions: Although progression of sarcoidosis was not rapid in this real-world cohort, it strongly predicted mortality. Findings support the need for early identification of patients at risk of progression and risk-stratified clinical management.