Value of neutrophil/lymphocyte ratio in the differential diagnosis of sarcoidosis and tuberculosis.
Iliaz Sinem,Iliaz Raim,Ortakoylu Gonenc,Bahadir Ayse,Bagci Belma Akbaba,Caglar Emel
Annals of thoracic medicine
INTRODUCTION:The differential diagnosis of sarcoidosis creates a challange due to tuberculosis also having lung and lymph node involvement. Because both diseases show granulomatous inflammation, it may not be possible to distinguish tuberculosis and sarcoidosis in pathological specimens. As a result of the complexity in the differential diagnosis of sarcoidosis and tuberculosis, new markers for differentiation are being investigated. OBJECTIVE:The aim of our study is to investigate the value of neutrophil/lymphocyte ratio (NLR) as a possible marker in differentiating sarcoidosis and tuberculosis. MATERIALS AND METHODS:In our study, 51 acid-fast bacilli (AFB) positive and/or culture-positive patients with pulmonary tuberculosis, 40 patients with biopsy-proven sarcoidosis and a control group consisting of 43 patients were included. In our study, information was collected retrospectively based on hospital records. RESULTS:Leukocyte and neutrophil counts, NLR, erythrocyte sedimentation rate (ESR), C-reactive protein (CRP) were significantly higher, and albumin was significantly lower in the tuberculosis group compared with sarcoidosis (for all parameters P < 0.001). The most appropriate cut-off value of NLR to distinguish tuberculosis from sarcoidosis was determined as 2.55. For this cut-off value of NLR there was 79% sensitivity, 69% specificity, 73% positive predictive value (PPV), 75% negative predictive value (NPV), and area under the curve (AUC) was 0.788. For differentiation of sarcoidosis from tuberculosis, accuracy of the NLR test according to this cut-off value was found as 76%. CONCLUSION:NLR as a little known marker in respiratory medicine was found to be supportive in differentiation of tuberculosis and sarcoidosis. More studies on this issue is needed.
Quantifying the relationship between symptoms at presentation and the prognosis of sarcoidosis.
Judson Marc A,Preston Sara,Hu Kurt,Zhang Robert,Jou Stephanie,Modi Aakash,Sukhu Indrawattie,Ilyas Furqan,Rosoklija Gavril,Yucel Recai
BACKGROUND:Although it is the general consensus that sarcoidosis patients who present with sarcoidosis-related symptoms have a worse outcome than patients whose disease is detected incidentally without symptoms, this premise has not been rigorously examined. METHODS:Consecutive patients followed longitudinally at one US university sarcoidosis clinic were questioned concerning the onset and description of sarcoidosis-related symptoms at disease presentation. The patients were classified into those with no sarcoidosis-related symptoms at presentation (NSP group) and those with symptoms at presentation (SP group). The following outcomes were examined in the NSP and SP groups: most recent spirometry, organ involvement, need for sarcoidosis therapy, most recent health related quality of life (HRQOL) as measured by the Sarcoidosis Assessment Tool (SAT), most recent chest imaging Scadding stage results. RESULTS:660 sarcoidosis patients were analyzed, with 175 in the NSP group and 485 in the SP group. Compared to the NSP group, the SP group had a more frequent requirement for any sarcoidosis treatment, corticosteroid treatment, and non-corticosteroid treatment at some time and within the most recent year of follow up (at least 50% more than the NP group with strong statistical differences with p values all 0.01 or less). In addition, the SP group had significantly more organ involvement (p < 0.001) and several worse SAT domains (p < 0.022) than the NP group. There were no differences between the groups in terms of final spirometry or development of Scadding stage 4 chest radiographs. These findings held even after adjusting for age, sex, race, and time between presentation and the most recent follow-up visit using a multivariable logistic regression framework. CONCLUSIONS:In our sarcoidosis cohort, compared to the absence of symptoms at presentation, the presence of symptoms was associated with a greater need for treatment, more organ involvement, and worse HRQOL.
Defining prognosis in sarcoidosis.
Lopes Mariana Carneiro,Amadeu Thaís Porto,Ribeiro-Alves Marcelo,Costa Claudia Henrique da,Silva Bruno Rangel Antunes,Rodrigues Luciana Silva,Bessa Elisabeth Jauhar Cardoso,Bruno Leonardo Palermo,Lopes Agnaldo José,Rufino Rogerio
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.