Defining prognosis in sarcoidosis.

Sarcoidosis is a multi-systemic granulomatous disease. Affected individuals can show spontaneous healing, develop remission with drug treatment within 2 years, or become chronically ill. Our main goal was to identify features that are related to prognosis.The study consisted of 101 patients, recruited at a single center, who were already diagnosed with sarcoidosis at the start of the study or were diagnosed within 48 months. Ninety individuals were followed-up for at least 24 months and were classified according to clinical outcome status (COS 1 to 9). Those with COS 1-4 and COS 5-9 were classified as having favorable and unfavorable outcomes, respectively. Unconditional logistic regression analyses were conducted to define which variables were associated with sarcoidosis outcomes. Subsequently, we established a scoring system to help predict the likelihood of a favorable or unfavorable outcome.Of our patients, 48% developed a chronic form of the disease (COS 5-9). Three clinical features were predictive of prognosis in sarcoidosis. We built a score-based model where the absence of rheumatological markers (1 point), normal pulmonary functions (2 points), and the presence of early respiratory symptoms manifestations (2 points) were associated with a favorable prognosis. We predicted that a patient with a score of 5 had an 86% (95% confidence interval [CI] 74%-98%) probability of having a favorable prognosis, while those with scores of 4, 3, 2, 1, and 0 had probabilities of 72% (95% CI 59-85%), 52% (95% CI 40-63%), 31% (95% CI 17-44%), 15% (95% CI 2-28%), and 7% (95% CI 0-16%) of having a favorable prognosis, respectively. Thus, our easy-to-compute algorithm can help to predict prognosis of sarcoidosis patients, facilitating their management.

Identification of Active Sarcoidosis Using Chitotriosidase and Angiotensin-Converting Enzyme.

PURPOSE: Activity/remission differentiation is a great challenge in the follow-up and treatment of sarcoidosis patients. Angiotensin-converting enzyme (ACE) and high sensitivity C-reactive protein (hs-CRP) were proposed as sarcoidosis biomarkers. More recently, chitotriosidase (CHITO) has been described as a better alternative. This study has the aim to evaluate the association of CHITO activity, ACE, hs-CRP or a combination of these biomarkers and to construct a clinical algorithm to differentiate between sarcoidosis activity/remission status. METHODS: Forty-six patients with either active sarcoidosis or sarcoidosis in remission and 21 healthy individuals were included. ACE, hs-CRP, and CHITO were evaluated in serum samples. Comparisons of the laboratory variable means among groups were performed by linear models. The cutoff points of the biomarkers for activity/remission differentiation were calculated using the Youden's index. Biomarker cutoff points and decision tree classifier (DTC) performance were estimated by their leave-one-out cross-validation (LOOCV) accuracy (Acc), sensitivity (Se), and specificity (Sp). RESULTS: A 55% mean Se and a 100% mean Sp were found for CHITO, while an 88% Se and a 47% Sp were found for ACE, and a 66% Se and a 68% Sp for hs-CRP cutoff points for activity/remission differentiation. The DTC algorithm with CHITO, hs-CRP, and ACE information had an LOOCV mean Acc of 82%, Se of 78%, and Sp of 89% for sarcoidosis activity/remission differentiation. CONCLUSIONS: The algorithm involving CHITO, hs-CRP, and ACE could be a suitable strategy for differentiation between sarcoidosis activity/remission status.