# Development and Internal Validation of the Yuvarajan Sarcoidosis Diagnostic Score (YSDS): A Retrospective Cohort Study

## TL;DR

This study created a new scoring system to help doctors diagnose sarcoidosis more accurately, especially in regions where it's hard to tell apart from tuberculosis.

## Contribution

The Yuvarajan Sarcoidosis Diagnostic Score (YSDS) is a novel clinical tool developed and validated for diagnosing sarcoidosis using common clinical parameters.

## Key findings

- The YSDS score achieved 87.3% sensitivity and 83.9% specificity in diagnosing sarcoidosis.
- Five key predictors were identified, including non-caseating granulomas and elevated ACE levels.
- The score demonstrated excellent discriminatory power with an area under the ROC curve of 0.90.

## Abstract

Background: Sarcoidosis is a complex, multisystem granulomatous disease of unknown etiology, often presenting a diagnostic challenge due to its highly variable clinical manifestations and its overlap with infectious and neoplastic diseases. This is especially problematic in regions with a high burden of tuberculosis (TB), such as India, where the clinical and radiological features of sarcoidosis and TB can be remarkably similar. Early, accurate diagnosis is imperative to guide treatment and avoid inappropriate therapy, yet no universally accepted diagnostic scoring system exists.

Objective: The objective of this study was to develop and internally validate a novel, composite clinical scoring tool named the Yuvarajan Sarcoidosis Diagnostic Score (YSDS) to aid in the diagnosis of sarcoidosis using routinely available clinical, radiologic, laboratory, and histopathologic parameters.

Methods: A retrospective observational study was conducted at a tertiary care hospital in South India. Medical records of 94 patients evaluated for suspected sarcoidosis between January 2022 and January 2025 were reviewed. Patients were categorized into sarcoidosis (n = 63) and non-sarcoidosis groups (n = 31) based on histopathological confirmation, radiological features, and exclusion of differential diagnoses. Multivariate logistic regression was used to identify significant independent predictors of sarcoidosis. These predictors were used to create a weighted diagnostic score, and their diagnostic accuracy was assessed using receiver operating characteristic (ROC) curve analysis.

Results: Five independent predictors were identified: bilateral hilar lymphadenopathy (BHL) on chest imaging, elevated serum angiotensin-converting enzyme (ACE) levels, histologic presence of non-caseating granulomas, negative Mantoux test, and characteristic extrapulmonary manifestations such as uveitis, parotid gland enlargement, or lupus pernio. Each parameter was assigned a score based on the regression coefficient. The YSDS score ranged from 0 to 13, with a cutoff ≥8 yielding a sensitivity of 87.3% (55/63), specificity of 83.9% (26/31), positive predictive value (PPV) of 89.6% (55/61), negative predictive value (NPV) of 80.6% (26/33), and an overall accuracy of 85.9% (81/94). The area under the ROC curve was 0.90, indicating excellent discriminatory power.

Conclusion: The YSDS is a statistically robust, easy-to-implement clinical tool that enhances diagnostic confidence in sarcoidosis, particularly in settings where TB and other granulomatous diseases are prevalent. It offers a promising strategy for standardized diagnostic assessment and warrants external validation in larger, prospective cohorts.