Background: Tuberculosis (TB) and sarcoidosis are two common granulomatous diseases involving lymph nodes. Differential diagnosis is not always easy because pathogen demonstration in tuberculosis is not always possible and both diseases share clinical, radiological and histological patterns. The aim of our study was to identify factors associated with each diagnosis and set up a predictive score for TB. Methods: All cases of lymph node tuberculosis and sarcoidosis were retrospectively reviewed. Demographics, clinical characteristics, laboratory and imaging data, and microbiological and histological results were collected and compared. Results: Among 441 patients screened, 192 patients were included in the final analysis. The multivariate analysis showed that weight loss, necrotic granuloma, normal serum lysozyme level and hypergammaglobulinemia were significantly associated with TB. A risk score of TB was built based on these variables and was able to discriminate TB versus sarcoidosis with an AUC of 0.85 (95% CI: 0.79-0.91). Using the Youden\'s J statistic, its most discriminant value (-0.36) was associated with a sensitivity of 80% and a specificity of 75%. Conclusions: We developed a score based on weight loss, necrotic granuloma, normal serum lysozyme level and hypergammaglobulinemia with an excellent capacity to discriminate TB versus sarcoidosis. This score needs still to be validated in a multicentric prospective study.

A patient was referred to the oral medicine department with redness and swelling of the lips and cheek, and an intra-oral lesion. Biopsy and laboratory investigations suggested a diagnosis of sarcoidosis. In this study we discuss oral findings associated with sarcoidosis.

Rationale: The Sarcoidosis Diagnostic Score (SDS) has been established to quantitate the clinical features consistent with sarcoidosis in a monocentric study. Objectives: We aimed to confirm the diagnostic value of SDS in a large, multicontinental study and to assess the utility of SDS in differentiating sarcoidosis from alternative diagnoses, including infectious and noninfectious granulomatous diseases. Methods: We included patients with biopsy-confirmed sarcoidosis at nine centers across the world. Patients without sarcoidosis seen at the same sites served as control patients. Using a modified World Association of Sarcoidosis and Other Granulomatous Disorders organ assessment instrument, we scored all patients for the presence of granuloma on biopsy, highly probable symptoms, and least probable symptoms for each area. Two sarcoidosis scores were generated: SDS Biopsy (with biopsy) and SDS Clinical (without biopsy). SDS Clinical and Biopsy were calculated for all patients. We calculated and compared the area under the curve (AUC) for SDS Clinical and Biopsy according to different diagnosis scenarios. Results: A total of 1,041 patients with sarcoidosis and 1,035 without sarcoidosis were included. The results for SDS Clinical (AUC, 0.888; 95% confidence interval [CI], 0.874-0.902) and SDS Biopsy (AUC, 0.979; 95% CI, 0.973-0.985) according to AUC were good to excellent for differentiating sarcoidosis from alternative diagnosis. SDS Clinical was less discriminatory in males (P = 0.01) and in high tuberculosis prevalence centers (P < 0.001). However, SDS Clinical (AUC, 0.684; 95% CI, 0.602-0.766) and SDS Biopsy (AUC, 0.754; 95% CI, 0.673-0.835) were not sufficiently discriminative for noninfectious granulomatous diseases, but both SDSs could differentiate sarcoidosis from infectious granulomatous diseases. Algorithms were proposed for the SDS Clinical and SDS Biopsy to assist the clinician in the diagnostic process, and cutoff values were proposed for the SDS Clinical and SDS Biopsy, allowing the diagnosis of sarcoidosis to be safely confirmed or rejected in most cases except for noninfectious granulomatous disease. Conclusions: This multicontinental study confirms that both SDS Clinical and SDS Biopsy have good to excellent performance in discriminating sarcoidosis from alternative diagnoses. Differences in the AUC were seen for high tuberculosis prevalence versus low tuberculosis prevalence centers and for males versus females. Both SDSs had good discriminatory function for infectious granulomatous disease but failed in cases of noninfectious granulomatous disease such as berylliosis.