Role of serum angiotensin-converting enzyme (sACE) level as a biomarker for predicting steroid response in patients with sarcoidosis

Role of serum angiotensin-converting enzyme (sACE) level as a biomarker for predicting steroid response in patients with sarcoidosis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Role of serum angiotensin-converting enzyme (sACE) level as a biomarker for predicting steroid response in patients with sarcoidosis Asmita A Mehta, Lakshmi Priya VP, Gokulakrishnan G, Liya Anil This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6560786/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Sarcoidosis is a systemic inflammatory disease characterized by non-caseating granulomas in multiple organs, predominantly the lungs. Corticosteroids are the first-line treatment; however, steroid resistance remains a significant challenge. This study aims to evaluate serum angiotensin-converting enzyme (sACE) levels as a biomarker for predicting steroid resistance in sarcoidosis patients. Methods: This prospective study was conducted at a tertiary care center and included patients with biopsy-confirmed sarcoidosis. Serum ACE levels were measured after 4 to 6 weeks of corticosteroid therapy using the Kasahara colorimetric technique. The association between sACE levels and steroid resistance was evaluated. Statistical analysis was performed using SPSS version 20, with a significance threshold set at p < 0.05. Results: A total of 188 sarcoidosis patients (mean age: 54 years, 62% women) were included. Common symptoms included cough, dyspnea, fatigue, fever, chest pain, and arthralgia. Hypercalcemia was observed in 11% of patients. ROC analysis revealed that sACE >64 U/L had 83% sensitivity and 73% specificity in predicting steroid resistance. Univariate analysis identified fatigue, hypercalcemia, fibrosis on chest CT, and elevated sACE levels as associated factors, while multivariate analysis confirmed elevated serum ACE levels (p 54 years (p 64 U/L are a potential biomarker for steroid resistance in sarcoidosis. However, further research and a multidisciplinary approach are needed to validate these findings and improve clinical management. sarcoidosis angiotensin-converting enzyme level corticosteroids steroid resistance immunomodulators Figures Figure 1 Figure 2 1. Introduction Sarcoidosis is a multi-system inflammatory disorder characterized by non-caseating granulomas, primarily affecting the lungs and intrathoracic lymph nodes but can involve the skin, eyes, liver, spleen, heart, nervous system, kidneys, bones, and salivary glands [1]. Pulmonary sarcoidosis often presents with cough, dyspnea, chest discomfort, fatigue, and fever. Other manifestations include uveitis, cardiac arrhythmias, cranial neuropathies, erythema nodosum, hepatomegaly, and joint pain. Diagnosis is based on clinical, radiographic, and histopathological findings, with biopsy confirmation being essential. High-resolution computed tomography (HRCT) helps assess pulmonary involvement, while serum biomarkers like sACE support monitoring and treatment decisions [2,3] Elevated sACE levels (> 64 U/L) indicate steroid resistance with 83% sensitivity and 73% specificity, but caution is needed due to variability from genetic factors and comorbidities [4,5]. Pulmonary sarcoidosis therapy follows a structured six-step approach. Initially, corticosteroids are introduced and maintained for 6 weeks to 6 months. This is followed by a tapering phase, gradually reducing the dose to a maintenance level of 20–40 mg daily for 2–6 weeks. Subsequently, the dose is lowered to 5–15 mg per day for 5–9 months. The taper-off phase lasts 1–6 months, with progressive dose reduction, after which patients enter a monitoring phase without ongoing medication. In case of relapse, the corticosteroid dose is reduced to less than 10 mg/day, and corticosteroid-sparing medications may be considered [6]. Prolonged corticosteroid use, especially doses above 10 mg/day, can lead to serious adverse effects [7]. Steroid resistance in sarcoidosis refers to the failure to achieve clinical or radiographic improvement despite adequate corticosteroid therapy. It is characterized by persistent symptoms, radiographic abnormalities, or functional impairment after receiving high doses (20–40 mg/day) for 4–6 weeks. Relapse or worsening while on maintenance therapy also suggests resistance, as does persistent inflammation on imaging or lab markers. Contributing factors may include fibrosis, inadequate dosing, genetic factors, or comorbidities. In such cases, immunosuppressive agents or biologics may be necessary[5]. Steroid resistance in sarcoidosis remains poorly defined and challenging to manage. While patients requiring second-line agents such as methotrexate, azathioprine, or TNF-α inhibitors are often considered steroid-resistant, the response to corticosteroids is more nuanced than a simple binary classification [8]. Jeny et al. emphasize the need for clear criteria to identify steroid-resistant cases, as the absence of standardized definitions complicates both clinical management and research interpretations [9]. Sarcoidosis treatment presents several challenges due to its unpredictable nature, multi organ involvement, and variability in patient response. The heterogeneity of the disease further complicates management, as no FDA-approved treatments exist specifically for sarcoidosis, and most therapies are used off-label, necessitating individualized treatment strategies [10]. Additionally, the impact of sarcoidosis on quality of life (QoL) varies widely, highlighting the need for personalized care approaches [11]. Serum angiotensin-converting enzyme (sACE) has long been considered a poten-tial biomarker for sarcoidosis, given that it is produced by epithelioid cells within granulomas and reflects disease activity [12]. However, its clinical utility was initially questioned due to inconsistent sensitivity and specificity across studies. Early research reported wide variations in sACE sensitivity (41–100%) and specificity (83–99%), which led to skepticism about its value as a standalone diagnostic marker [3]. Moreover, elevated sACE levels were observed not only in sarcoidosis but also in other granulomatous and non-granulomatous conditions, including tuberculosis, silicosis, hyperthyroidism, and diabetes, further complicating its interpretation [13]. Despite these limitations, the role of sACE has recently been revisited due to emerging evidence supporting its utility in identifying patients at risk of steroid resis-tance and predicting relapse. Recent studies have shown that elevated sACE levels, particularly those exceeding 64 U/L, are significantly associated with poor response to corticosteroids and an increased need for second-line immunosuppressive therapy [4]. In addition to its prognostic value, serial sACE measurements have been proposed as a means to monitor disease activity and relapse, as fluctuations in sACE levels often cor-relate with changes in clinical status and treatment response [14]. This renewed interest in sACE as a biomarker has been driven by a better understanding of its dynamic nature and its role in reflecting active granulomatous inflammation rather than merely indicating disease presence. Furthermore, sACE levels have demonstrated the ability to stratify patients who may not adequately respond to steroids alone, guiding clinicians towards early initiation of steroid-sparing agents, thereby minimizing prolonged corticosteroid exposure and its associated adverse effects [4]. As a result, while sACE should not be used as the sole indicator for diagnosis or management, its role as part of a multimodal assessment strategy has gained considerable traction, particularly in predicting relapse and identifying steroid-resistant sarcoidosis [15]. This study aims to tackle the challenges of sarcoidosis management by investigating the relationship between sACE levels and steroid responsiveness. The goal is to identify reliable biomarkers that can guide treatment strategies, helping clinicians make more informed decisions. By establishing accurate predictors of treatment response, this research has the potential to minimize unnecessary corticosteroid use and enhance overall disease management, ultimately leading to improved patient outcomes. 2. Materials and Methods This prospective study was conducted at a tertiary care hospital in South India and in-cluded 188 patients diagnosed with sarcoidosis between June 2021 and June 2022. The diagnosis was established through clinical presentation and histopathological confirmation of non-necrotizing granulomas. 2.1. Patient selection and Patient involvement A total of 191 patients were initially enrolled in the study. Three patients were excluded due to the use of angiotensin-converting enzyme (ACE) inhibitors, which could potentially confound serum ACE (sACE) measurements. The final cohort comprised 188 patients with biopsy-proven sarcoidosis, confirmed by the histopathological presence of non-caseating granulomas. 2.2. Study Definitions and Outcome Measures Steroid responsiveness was defined as significant clinical and radiological im-provement observed during follow-up after corticosteroid therapy. Persistent disease was characterized by the absence of clinical or radiological improvement or by worsening features despite ongoing treatment. Steroid resistance in sarcoidosis was defined as the lack of a significant clinical or radiological response despite receiving adequate doses of corticosteroids (typically 20–40 mg/day) for at least 4–6 weeks. Additionally, relapse or worsening of the disease while on maintenance corticosteroid therapy, or persistent inflammation on imaging or laboratory markers, was considered indicative of resistance. In this study, the primary outcome measure was the requirement for disease-modifying agents (DMAs) beyond corticosteroids. The study cohort was divided into two outcome groups based on their therapeutic needs: Steroid-Responsive Group: These patients demonstrated significant clinical and radiological improvement with corticosteroid therapy alone (typically prednisone 20–40 mg/day), and did not require additional disease-modifying agents. They remained stable on maintenance corticosteroid doses (5–15 mg/day) without relapse or worsening symptoms. Steroid-Resistant Group: These patients exhibited persistent symptoms, radiographic abnormalities, or disease progression despite adequate corticosteroid therapy. This group required additional immunosuppressive or steroid-sparing agents, such as methotrexate, azathioprine, mycophenolate mofetil, or biologics (e.g., TNF-α inhibitors), to achieve disease control. Outcome Assessment The distinction between the two groups was based on: Clinical Response: Improvement in symptoms such as cough, dyspnea, or chest discomfort. Radiological Response: Resolution or significant reduction of granulomatous inflammation on HRCT. Laboratory Markers: sACE levels post-therapy. 2.3. Laboratory Biomarker Assessment Venous blood samples were collected from all patients diagnosed with sarcoidosis. After 4 to 6 weeks of corticosteroid therapy, serum angiotensin-converting enzyme (sACE) levels were measured using the Kasahara colorimetric method. The method employed p-hydroxyhippuryl-l-histidyl-l-leucine as the substrate, and the normal reference range for sACE in the laboratory was 8–65 units per liter. An sACE level of 64 units per liter was selected as the cut-off value based on prior studies and clinical relevance. The measurement of serum angiotensin-converting enzyme (sACE) levels was performed 4 to 6 weeks after initiating corticosteroid therapy to evaluate their potential role as predictive markers of steroid resistance. Baseline sACE levels were not included as the primary objective was to assess post-treatment levels rather than initial diagnostic values. Furthermore, reduction trends in sACE post-therapy were not analyzed due to logistical constraints. An sACE level greater than 64 U/L was used as the cut-off value for predicting steroid resistance, based on prior studies demonstrating its sensitivity (83%) and specificity (73%) in identifying patients with poor corticosteroid responsiveness. 2.5. Statistical Analysis Descriptive statistics were employed to summarize demographic and clinical cha-racteristics. Continuous variables were reported as mean ± standard deviation for normally distributed data and as median with interquartile range for non-normally distributed data. Categorical variables were expressed as frequencies and percentages. For statistical comparisons, a range of tests was employed depending on the variable type. Categorical variables were analyzed using the Chi-square test to assess associations with the need for disease-modifying agents. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using a univariate logistic regression model. A p-value of less than 0.05 was considered statistically significant. Receiver operating characteristic (ROC) analysis was performed to determine the sensitivity, specificity, and optimal cut-off value for sACE in predicting steroid resis-tance. To identify independent predictors of steroid resistance, multivariate logistic re-gression analysis was conducted. All statistical analyses were performed using SPSS software version 22.0. 3. Results A study involving 191 patients with biopsy-confirmed sarcoidosis was conducted, with 3 patients excluded due to their use of serum angiotensin-converting enzyme inhibitors that can affect serum angiotensin converting enzyme levels. The mean age of participants was 54 years (± 13.8), and 116 (61.7%) of them were female. The majority of patients (116, 61.7%) had pulmonary involvement, while 18 (9.6%) had gastrointestinal involvement, 18 (9.6%) presented with uveitis, 16 (8.5%) had generalized lymphadenopathy, and smaller proportions had erythemanodosum (6, 3.2%), salivary gland involvement (6, 3.2%), cardiac involvement (4, 2.1%), kidney involvement (2, 1.1%), and facial nerve involvement (2, 1.1%). 3.1. Clinical Characteristics The most common presenting symptoms were cough (106 patients, 56%), dyspnea (105 patients, 55%), fatigue (23 patients, 12%), fever (36 patients, 19%), chest pain (31 patients, 16%), and arthralgia (48 patients, 26%). A total of 17 patients (9%) were asymptomatic asymptomatic at time of presentation in view of respiratory symptoms.The most frequent comorbidities were diabetes mellitus (62 patients, 33%), hypertension (55 patients, 29%), and hypothyroidism (22 patients, 12%). 3.2. Radiological Findings and Hypercalcemia Radiological findings indicated that the majority of patients were diagnosed with Stage I as shown in Table 1 . Table 1 Baseline characteristics of study population. Character N = 188, Median (Percentage/Range) Age 53 ± 13.8 Gender Male Female 72 (38.3%) 116 (61.7%) Smokers 18 (9.6%) Patient history of ATT 25 (13.3%) Co-morbidities: Diabetes mellitus Hypertension Hypothyroid 62 (33.0%) 55 (29.3%) 22 (11.7%) Hypercalcemia 20 (10.6%) Mantoux Positive Negative 25 (13.3%) 133 (76.7%) Chest X-ray stage Stage I Stage II Stage III Stage IV 59 (31.4%) 54 (28.7%) 16 (8.5%) 6 (3.2%) CECT Mediastinal lymph node Interseptal thickening ground glass opacity Fibrosis 89 (47.3%) 52 (27.7%) 12 (6.4%) Mode of diagnosis c TBNA EBUS-TBNA EBB TBLB Biopsy from other site 6 (3.1%) 72 (38.2%) 4 (2.1%) 34 (18.1%) 72 (38.2%) ANA positive 27 (14.4%) s ACE > 64 U/L 77(41%) Need for additional immunomodulators 47 (25%) *N = total number of samples Hypercalcemia was observed in 20 patients (10.6%) and showed a significant association with the requirement for disease-modifying agents as shown in Table 2 . Table 2 Association of Clinical and Radiological Variables with the Requirement for Disease-Modifying Agents in Sarcoidosis Patients. Variables Disease Modifying-agent required Disease Modifying-agent not required Odds ratio 95% Confidence interval P value Gender Male Female 15(20.8%) 32(27.6%) 57(79.2%) 84(72.4%) 1.448 0.719–2.914 0.299 Smoking 4(22.2%) 14(77.8%) 0.844 0.264–2.702 0.775 Patient history of ATT 6(24%) 19(76%) 0.940 0.351–2.513 0.901 Cough 30(28.3%) 76(71.7%) 1.509 0.764–2.982 0.235 Fatigue 11(47.8%) 12(52.2%) 3.285 1.339–8.060 0.007 Hypercalcemia 10(50.0%) 10(50.0%) 3.514 1.359–9.081 0.007 CECT Mediastinal lymph node Ground glass opacities Fibrosis 20(22.5%) 18(34.6%) 5(41.7%) 69(77.5%) 34(65.4%) 7(58.3%) - - 0.044 Thorax 35(30.2%) 81(69.8%) 2.160 1.035–4.509 0.038 Gastrointestinal 5(27.8%) 13(72.2%) 1.172 0.395–3.482 0.775 Kidney 1(50%) 1(50.0%) 3.022 0.185–49.285 0.415 Uveitis 6(33.3%) 12(66.7%) 1.573 0.555–4.456 0.391 Erythema nodosum 1(16.7%) 5(83.3%) 0.591 0.067–5.194 0.632 Cardiac 1(25.0%) 3(75.0%) 1.000 0.102–9.852 1.000 Salivary 3(50.0%) 3(50.0%) 3.136 0.611–16.102 0.151 Generalized lymph node 7(43.8%) 9(56.2%) 2.567 0.899–7.329 0.070 ACE level < 64 U/L 13(10.7%) 109(89.3%) 8.909 4.205–18.876 < 0.001 3.3 Need for Immunomodulatory Therapy A total of 47 patients (25%) required disease-modifying agents, while 141 patients (75%) did not. Within the group requiring immunomodulatory therapy, 32 patients (27.6%) were female, and 15 (20.8%) were male. In the group that did not require immunomodulatory therapy, 84 patients (72.4%) were female, and 57 (79.2%) were male. Gender differences between the two groups were statistically significant. 3.4 Serum ACE Levels The mean serum ACE level for the entire cohort was 64 ± 61 IU/L, with levels ranging from 1 to 490 IU/L. Elevated serum ACE levels (> 64 IU/L) were observed in 77 patients (41%) [Figure 1 ]. 3.5 ROC Curve Analysis The ROC curve analysis confirmed that a serum ACE level of 64 IU/L was the optimal cut-off for distinguishing patients requiring immunomodulatory therapy. The area under the curve (AUC) was significant, with a sensitivity of 83% and specificity of 73%, supporting the potential of serum ACE as a predictive biomarker for steroid resistance in sarcoidosis [Figure 2 ]. 3.6 Factors Associated with Steroid Resistance Univariate analysis identified several factors significantly associated with steroid resistance, including elevated serum ACE levels (p < 0.001), fatigue (p = 0.002), hypercalcemia (p = 0.007), thoracic involvement (p = 0.038), and ground-glass opacities on HRCT (p = 0.044) [Table 2 ]. The study utilized multivariate binary logistic regression was used to analyze factors influencing the requirement of disease-modifying agents (DMAs) in sarcoidosis .It revealed that elevated serum ACE levels (p 54 years (p < 0.001), fatigue (p = 0.002), hypercalcemia (p = 0.019), and specific radiological findings (e.g., CECT showing mediastinal lymph node involvement, p = 0.036) were independent risk factors for requiring immunomodulatory therapy [Table 3 ]. Table 3 Logistic regression analysis of factors influencing disease-modifying agent requirement in sarcoidosis Variable B Wald 95% Confidence interval p-value Age 53 ± 13.8 years < 0.001 Dyspnea -1.330 3.719 0.068–1.022 0.054 Fatigue 2.663 9.141 2.551–80.552 0.002 Calcium 1.709 5.520 1.328–22.988 0.019 CECT 2.357 4.387 1.163–95.771 0.036 Thorax -0.982 1.998 0.096–1.461 0.157 Erythema nodosum 0.164 0.011 0.054–25.463 0.917 Cardiac 1.550 0.835 0.170–130.984 0.361 Salivary 3.491 3.787 0.975–1104.034 0.052 ACE level 3.997 24.132 11.050–268.276 < 0.001 4. Discussion This study evaluated the role of serum angiotensin-converting enzyme (sACE) le-vels as a predictive biomarker for steroid responsiveness in patients with sarcoidosis. Our findings demonstrated that elevated sACE levels (> 64 U/L) were significantly associated with steroid resistance, reinforcing their potential utility in identifying patients who may require additional immunomodulatory therapy. The sensitivity and specificity of sACE levels in predicting steroid resistance were found to be 83% and 73%, respectively, which aligns well with previous studies suggesting sACE as a useful marker of active granulomatous inflammation and steroid resistance [4,5] . 4.1 Interpretation of findings The high sensitivity and specificity observed in this study indicate that elevated sACE levels serve as a reliable predictor for identifying patients who may not respond adequately to corticosteroid therapy. This finding is crucial for early risk stratification and guiding therapeutic decisions, as it allows clinicians to identify patients who are more likely to require disease-modifying agents (DMAs) beyond corticosteroids. In our cohort, 25% of patients required additional immunomodulatory therapy, and these patients had significantly higher sACE levels compared to those managed with corticosteroids alone. Multivariate logistic regression revealed that elevated sACE levels, age over 54 years, hypercalcemia, and fatigue were independent predictors of steroid resistance. These results align with previous studies demonstrating that increased sACE levels correlate with more active disease and a greater likelihood of requiring additional immunosuppressive treatment [5,14]. The presence of fatigue as an independent predictor is noteworthy, as it highlights the systemic nature of sarcoidosis and its impact on patient well-being. Fatigue is a common and debilitating symptom in sarcoidosis, often reflecting ongoing disease ac-tivity or systemic inflammation. Its association with steroid resistance indicates that patients who present with significant fatigue may require closer monitoring and more aggressive treatment. Additionally, hypercalcemia was significantly associated with steroid resistance, consistent with the known pathophysiological mechanisms where sarcoid granulomas produce 1α-hydroxylase, leading to increased calcitriol production and hypercalcemia [16]. This finding further underscores the need for comprehensive biochemical assessment in sarcoidosis management. 4.2 Serum ACE as a biomarker In our study, the serum angiotensin-converting enzyme (sACE) level demonstrated a sensitivity of 83% and a specificity of 73% for predicting steroid resistance in sarcoidosis patients. While the high sensitivity indicates that elevated sACE levels are effective in identifying patients likely to exhibit resistance to corticosteroid therapy, the relatively lower specificity suggests that not all patients with elevated sACE levels will necessarily develop steroid resistance. This discrepancy can be attributed to the presence of other conditions that can also raise sACE levels, such as tuberculosis, silicosis, and hyperthyroidism, which may confound the accuracy of sACE as a sole predictive marker [17,3]. Additionally, variations in genetic predisposition and disease heterogeneity may also influence sACE levels, resulting in false positives. Therefore, while sACE is a useful adjunct in predicting steroid resistance, it should not be used in isolation. Instead, it is best interpreted alongside clinical and radiological findings to enhance decision-making and improve patient stratification. sACE has long been considered a potential biomarker for sarcoidosis, primarily due to its production by epithelioid cells within granulomas. While earlier studies questioned its utility due to inconsistent sensitivity and specificity, our study reaffirms that elevated sACE levels are indicative of active granulomatous inflammation and potential steroid resistance. Previous reports have documented wide variations in sACE sensitivity (41–100%) and specificity (83–99%), partly attributed to heterogeneity in study populations and variations in disease presentation [3] . However, recent studies have highlighted that while sACE levels alone may not suffice as a definitive diagnostic marker, they hold substantial value in predicting disease activity and relapse when used as part of a comprehensive assessment. Our findings support the growing consensus that sACE can serve as a valuable adjunct to clinical and radiographic evaluations, particularly in identifying patients who may not adequately respond to steroids alone. The renewed interest in sACE as a biomarker has been driven by its ability to stratify patients at risk of relapse or progression, thereby guiding the early initiation of steroid-sparing agents, such as methotrexate, azathioprine, or TNF-α inhibitors [5,14]. 4.3 Relevance to Clinical Practice From a clinical perspective, identifying patients at risk of steroid resistance is essential to reducing prolonged corticosteroid exposure and associated adverse effects. Our findings suggest that monitoring sACE levels after 4 to 6 weeks of corticosteroid therapy can help identify those who may benefit from early intervention with additional immunosuppressive agents. The integration of sACE measurement into routine practice could enhance decision-making, particularly for patients who present with risk factors such as fatigue, hypercalcemia, or advanced age. Additionally, our study contributes to the ongoing debate regarding the utility of sACE as a standalone marker. While our data demonstrate its relevance as a predictive tool, it remains essential to interpret sACE levels in conjunction with clinical, radiological, and laboratory data. This multimodal approach ensures that therapeutic decisions are based on comprehensive patient assessments rather than relying solely on single biomarker values. 4.4 Strength and limitations The strengths of this study include its prospective design, the use of biop-sy-confirmed sarcoidosis cases, and the application of robust statistical methods to identify independent predictors of steroid resistance. Moreover, the assessment of sACE levels post-therapy provided valuable insights into their prognostic utility rather than simply evaluating baseline levels. However, several limitations should be considered. Firstly, baseline sACE levels before corticosteroid initiation were not measured, as the primary objective was to assess post-treatment levels as predictors of resistance. This approach limited the evaluation of dynamic changes in sACE levels over time. Additionally, the study did not investigate the long-term outcomes of patients who transitioned to second-line therapies, which could offer further insights into treatment effectiveness. Furthermore, the study was conducted at a single tertiary care center, which may limit the generalizability of the findings. While serum levels of angiotensin-converting enzyme (sACE) can be raised in a substantial proportion of patients, their diagnostic value remains low [18]. 4.5 Future Perspective Further large-scale, multicenter studies are needed to validate our findings and explore the long-term outcomes of patients stratified by sACE levels. Additionally, investigating serial changes in sACE levels over the course of treatment could provide insights into their role as a dynamic biomarker. Integrating sACE measurements with other promising biomarkers, such as soluble interleukin-2 receptor (sIL-2R) levels, could enhance the accuracy of predicting treatment outcomes[19,20].Developing standardized protocols for measuring and interpreting sACE levels will also be essential to improve reproducibility and clinical utility. Ultimately, incorporating sACE assessment into routine practice as part of a multimodal approach could help reduce unnecessary corticosteroid exposure and enable early initiation of more targeted therapies, thereby optimizing patient outcomes 4.6 Implications for Practice The integration of sACE levels into routine clinical practice has the potential to guide early decision-making, particularly in identifying patients who are likely to require additional immunosuppressive therapy. However, the moderate specificity observed in our study calls for cautious interpretation, emphasizing the need for a comprehensive, multimodal approach that includes clinical, radiological, and laboratory assessments. While sACE serves as a valuable adjunct, it should not replace thorough clinical evaluation when determining treatment plans. 5. Conclusions Our study highlights the importance of a personalized approach in sarcoidosis management, emphasizing the role of serum angiotensin-converting enzyme (sACE) as a biomarker for predicting steroid resistance. An sACE level greater than 64 U/L was significantly associated with the need for additional immunosuppressive therapy, with a specificity of 73% and a sensitivity of 83%. Fatigue and hypercalcemia (Ca > 10 mg/dL) also emerged as independent predictors of steroid resistance. Localized thoracic sarcoidosis showed a negative association with the need for additional immunosuppressants, suggesting a milder disease course. Reducing glucocorticoid dependence through the use of steroid-sparing agents and comprehensive patient assessment should be prioritized. Additionally, adopting a holistic care model that includes lifestyle changes and mental health support can enhance overall patient well-being and adherence to therapy. Abbreviations The following abbreviations are used in this manuscript: sACE Serum Angiotensin-Converting Enzyme ILD Interstitial Lung Disease GCs Glucocorticoids ATS American Thoracic Society ERS European Respiratory Society WASOG World Association for Sarcoidosis and Other Granulomatous Disorders QoL Quality of Life FDA Food and Drug Administration HRCT High-Resolution Computed Tomography TBNA Transbronchial Needle Aspiration EBUS-TBNA Endobronchial Ultrasound-Guided Transbronchial Needle Aspiration EBB Endobronchial Biopsy TBLB Transbronchial Lung Biopsy ANA Antinuclear Antibody ATT Anti-Tuberculosis Treatment CECT Contrast-Enhanced Computed Tomography sACE Serum Angiotensin-Converting Enzyme Declarations Ethics approval and consent to participate: The study was conducted in accordance with the Declaration of Helsinki, and the protocol was approved by the Ethics Committee of Amrita Institute of Medical Sciences and Research, Kochi (ECASM-AIMS-2022-109) on 07/06/2022. Informed Consent Statement : Informed consent was obtained from all subjects involved in the study. Competing interests The authors declare that they have no competing interests Funding: This research received no external funding Author Contribution Conceptualization: A.A.M. ; methodology, A.A.M. ; software, A.A.M. ; formal analysis, A.A.M., L.V.P. ; investigation, A.A.M., G.G. ,L.A . ; data curation, A.A.M. , G.G. ,L.A. ; writing—original draft preparation, A.A.M. , L.V.P. ; writing—review and editing, A.A.M. , L.V.P. ;. All authors have read and agreed to the published version of the manuscript. Acknowledgement We sincerely thank Dr. Sreekumar P and Dr. Rajasekaran from Amrita Institute of Medical Sciences for their invaluable assistance in interpreting CT chest scans for this study. Their expertise and support were instrumental in achieving accurate radiological assessments. Data Availability The data supporting the findings of this study are available at the following link:https://docs.google.com/spreadsheets/d/1KDNkP8QDuHZ9mWWA8LWaMSaAHFDizgQWM1q37Hxyc_w/edit?usp=sharing References Seve P, Pacheco Y, Durupt F, et al. Sarcoidosis: A Clinical Overview from Symptoms to Diagnosis. Cells. 2021;10(4):766. Published 2021 Mar 31.(1a). Grunewald J, Grutters JC, Arkema EV, et al. Sarcoidosis Nat Rev Dis Primer. 2019;5(1):1–22. Kraaijvanger R, Janssen BM, Vorselaars ADM, et al. Biomarkers in the Diagnosis and Prognosis of Sarcoidosis: Current Use and Future Prospects. Front Immunol. 2020;11:1443. Goldman C, Judson MA. Corticosteroid refractory sarcoidosis. Respir Med. 2020;171:106081. Baughman RP, Valeyre D, Korsten P et al. ERS clinical practice guidelines on treatment of sarcoidosis. Eur Respir J. 2021;58(6):2004079. 10.1183/13993003.04079-2020 . PMID: 34140301. Judson MA. The treatment of pulmonary sarcoidosis. Respir Med. 2012;106(10):1351–61. 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J Clin Med. 2024;13(24):7657. Zheng SY, Du X, Dong JZ. Re-evaluating Serum Angiotensin-Converting Enzyme in Sarcoidosis. Front Immunol. 2023;14:950095. Hu X, Zou L, Wang S, et al. Performance of Serum Angiotensin-Converting Enzyme in Diagnosing Sarcoidosis and Predicting the Active Status of Sarcoidosis: A Meta-Analysis. Biomolecules. 2022;12(10):1400. Tebben PJ, Singh RJ, Kumar R, Vitamin D-M, Hypercalcemia. Mechanisms, Diagnosis, and Treatment. Endocr Rev. 2016;37(5):521–47. Hoy RF, Hansen J, Glass DC, et al. Serum angiotensin converting enzyme elevation in association with artificial stone silicosis. Respir Med. 2021;177:106289. Grunewald J, Grutters JC, Arkema EV, et al. Sarcoidosis. Nat Rev Dis Primer. 2019;5(1):1–22. Zhou Y, Chen X, Zhao M, et al. SACE and IL-2R as serum biomarkers for evaluation of multi-organ involvement and prognosis of sarcoidosis. Respir Res. 2023;24:219. Della ZM, Bertuccio FR, Campo I, et al. Phenotypes and Serum Biomarkers in Sarcoidosis. Diagnostics. 2024;14(7):709. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6560786","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":461574217,"identity":"6b4ad147-7df0-4b50-bafc-90a2a67e78b7","order_by":0,"name":"Asmita A Mehta","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABDElEQVRIiWNgGAWjYJCCAyDCgIGB/ccHAxsgk7HxAEEtIBUGbAwMkjMq0kBaGghqYYBpkeY5cxhhLy7A33868fCHmm1y5vLND4x5287brW0/DLSlxiYalxaJG7kbDhw4dtvYso3NIHFu2+3kbWcSgVqOpeU24NJzgxeohe124oZjDAYH3gK1mB0AamFsOIxTi/z5s0At/27XbzjG/rGBt+1cstn5h/i1GBwAOuxg2+0Eg2M8xow8Zw7Ymd0gYIshyC9n+24bbjiWU8Y4oyI5wewG0JYEPH6RO39284eKb7flDQ4f38bwwcDO3ux8+sMHH2pscHsfHSSCVSYQqxwE7ElRPApGwSgYBSMDAACdiXNpYdpJjgAAAABJRU5ErkJggg==","orcid":"","institution":"Amrita Institute of Medical Sciences and Research Centre","correspondingAuthor":true,"prefix":"","firstName":"Asmita","middleName":"A","lastName":"Mehta","suffix":""},{"id":461574218,"identity":"6bafc4f0-d7df-4305-a3dd-69d6f9a0dd49","order_by":1,"name":"Lakshmi Priya VP","email":"","orcid":"","institution":"Amrita Institute of Medical Sciences and Research Centre","correspondingAuthor":false,"prefix":"","firstName":"Lakshmi","middleName":"Priya","lastName":"VP","suffix":""},{"id":461574219,"identity":"64050a5f-6b10-49e6-8018-1ef58fd7abfb","order_by":2,"name":"Gokulakrishnan G","email":"","orcid":"","institution":"Amrita Institute of Medical Sciences and Research Centre","correspondingAuthor":false,"prefix":"","firstName":"Gokulakrishnan","middleName":"","lastName":"G","suffix":""},{"id":461574220,"identity":"cab0bbc2-4333-4369-a508-632a9af2a508","order_by":3,"name":"Liya Anil","email":"","orcid":"","institution":"Amrita Institute of Medical Sciences and Research Centre","correspondingAuthor":false,"prefix":"","firstName":"Liya","middleName":"","lastName":"Anil","suffix":""}],"badges":[],"createdAt":"2025-04-30 03:53:04","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6560786/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6560786/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":83479529,"identity":"4ddb3b68-c07a-4863-8dbe-9f66c0ea2087","added_by":"auto","created_at":"2025-05-27 06:13:35","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":29935,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of serum angiotensin-converting enzyme levels in the patients with need for immunomodulators and patients without need for immunomodulators.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6560786/v1/a2f4c89fb18f96ab90fbf6dd.png"},{"id":83479530,"identity":"4211e56c-04aa-4a4b-99f2-44711af04139","added_by":"auto","created_at":"2025-05-27 06:13:35","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":124396,"visible":true,"origin":"","legend":"\u003cp\u003eROC curve analysis of serum angiotensin-converting enzyme levels for predicting steroid resistance in sarcoidosis.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6560786/v1/ae0faa1bffc3986eb4169072.png"},{"id":87844585,"identity":"23dd03b2-e8d8-4b37-9134-64b92782fb88","added_by":"auto","created_at":"2025-07-29 14:47:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1061365,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6560786/v1/3459dd35-8c73-4406-9fe2-86f3f60207fb.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Role of serum angiotensin-converting enzyme (sACE) level as a biomarker for predicting steroid response in patients with sarcoidosis","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eSarcoidosis is a multi-system inflammatory disorder characterized by non-caseating granulomas, primarily affecting the lungs and intrathoracic lymph nodes but can involve the skin, eyes, liver, spleen, heart, nervous system, kidneys, bones, and salivary glands [1]. Pulmonary sarcoidosis often presents with cough, dyspnea, chest discomfort, fatigue, and fever. Other manifestations include uveitis, cardiac arrhythmias, cranial neuropathies, erythema nodosum, hepatomegaly, and joint pain. Diagnosis is based on clinical, radiographic, and histopathological findings, with biopsy confirmation being essential. High-resolution computed tomography (HRCT) helps assess pulmonary involvement, while serum biomarkers like sACE support monitoring and treatment decisions [2,3] Elevated sACE levels (\u0026gt;\u0026thinsp;64 U/L) indicate steroid resistance with 83% sensitivity and 73% specificity, but caution is needed due to variability from genetic factors and comorbidities [4,5].\u003c/p\u003e \u003cp\u003ePulmonary sarcoidosis therapy follows a structured six-step approach. Initially, corticosteroids are introduced and maintained for 6 weeks to 6 months. This is followed by a tapering phase, gradually reducing the dose to a maintenance level of 20\u0026ndash;40 mg daily for 2\u0026ndash;6 weeks. Subsequently, the dose is lowered to 5\u0026ndash;15 mg per day for 5\u0026ndash;9 months. The taper-off phase lasts 1\u0026ndash;6 months, with progressive dose reduction, after which patients enter a monitoring phase without ongoing medication. In case of relapse, the corticosteroid dose is reduced to less than 10 mg/day, and corticosteroid-sparing medications may be considered [6].\u003c/p\u003e \u003cp\u003eProlonged corticosteroid use, especially doses above 10 mg/day, can lead to serious adverse effects [7]. Steroid resistance in sarcoidosis refers to the failure to achieve clinical or radiographic improvement despite adequate corticosteroid therapy. It is characterized by persistent symptoms, radiographic abnormalities, or functional impairment after receiving high doses (20\u0026ndash;40 mg/day) for 4\u0026ndash;6 weeks. Relapse or worsening while on maintenance therapy also suggests resistance, as does persistent inflammation on imaging or lab markers. Contributing factors may include fibrosis, inadequate dosing, genetic factors, or comorbidities. In such cases, immunosuppressive agents or biologics may be necessary[5].\u003c/p\u003e \u003cp\u003eSteroid resistance in sarcoidosis remains poorly defined and challenging to manage. While patients requiring second-line agents such as methotrexate, azathioprine, or TNF-α inhibitors are often considered steroid-resistant, the response to corticosteroids is more nuanced than a simple binary classification [8]. Jeny et al. emphasize the need for clear criteria to identify steroid-resistant cases, as the absence of standardized definitions complicates both clinical management and research interpretations [9].\u003c/p\u003e \u003cp\u003eSarcoidosis treatment presents several challenges due to its unpredictable nature, multi organ involvement, and variability in patient response. The heterogeneity of the disease further complicates management, as no FDA-approved treatments exist specifically for sarcoidosis, and most therapies are used off-label, necessitating individualized treatment strategies [10]. Additionally, the impact of sarcoidosis on quality of life (QoL) varies widely, highlighting the need for personalized care approaches [11].\u003c/p\u003e \u003cp\u003eSerum angiotensin-converting enzyme (sACE) has long been considered a poten-tial biomarker for sarcoidosis, given that it is produced by epithelioid cells within granulomas and reflects disease activity [12]. However, its clinical utility was initially questioned due to inconsistent sensitivity and specificity across studies. Early research reported wide variations in sACE sensitivity (41\u0026ndash;100%) and specificity (83\u0026ndash;99%), which led to skepticism about its value as a standalone diagnostic marker [3]. Moreover, elevated sACE levels were observed not only in sarcoidosis but also in other granulomatous and non-granulomatous conditions, including tuberculosis, silicosis, hyperthyroidism, and diabetes, further complicating its interpretation [13].\u003c/p\u003e \u003cp\u003eDespite these limitations, the role of sACE has recently been revisited due to emerging evidence supporting its utility in identifying patients at risk of steroid resis-tance and predicting relapse. Recent studies have shown that elevated sACE levels, particularly those exceeding 64 U/L, are significantly associated with poor response to corticosteroids and an increased need for second-line immunosuppressive therapy [4]. In addition to its prognostic value, serial sACE measurements have been proposed as a means to monitor disease activity and relapse, as fluctuations in sACE levels often cor-relate with changes in clinical status and treatment response [14]. This renewed interest in sACE as a biomarker has been driven by a better understanding of its dynamic nature and its role in reflecting active granulomatous inflammation rather than merely indicating disease presence.\u003c/p\u003e \u003cp\u003eFurthermore, sACE levels have demonstrated the ability to stratify patients who may not adequately respond to steroids alone, guiding clinicians towards early initiation of steroid-sparing agents, thereby minimizing prolonged corticosteroid exposure and its associated adverse effects [4]. As a result, while sACE should not be used as the sole indicator for diagnosis or management, its role as part of a multimodal assessment strategy has gained considerable traction, particularly in predicting relapse and identifying steroid-resistant sarcoidosis [15].\u003c/p\u003e \u003cp\u003eThis study aims to tackle the challenges of sarcoidosis management by investigating the relationship between sACE levels and steroid responsiveness. The goal is to identify reliable biomarkers that can guide treatment strategies, helping clinicians make more informed decisions. By establishing accurate predictors of treatment response, this research has the potential to minimize unnecessary corticosteroid use and enhance overall disease management, ultimately leading to improved patient outcomes.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cp\u003eThis prospective study was conducted at a tertiary care hospital in South India and in-cluded 188 patients diagnosed with sarcoidosis between June 2021 and June 2022. The diagnosis was established through clinical presentation and histopathological confirmation of non-necrotizing granulomas.\u003c/p\u003e\n\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n\u003ch2\u003e2.1. Patient selection and Patient involvement\u003c/h2\u003e\n\u003cp\u003eA total of 191 patients were initially enrolled in the study. Three patients were excluded due to the use of angiotensin-converting enzyme (ACE) inhibitors, which could potentially confound serum ACE (sACE) measurements. The final cohort comprised 188 patients with biopsy-proven sarcoidosis, confirmed by the histopathological presence of non-caseating granulomas.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n\u003ch2\u003e2.2. Study Definitions and Outcome Measures\u003c/h2\u003e\n\u003cp\u003eSteroid responsiveness was defined as significant clinical and radiological im-provement observed during follow-up after corticosteroid therapy. Persistent disease was characterized by the absence of clinical or radiological improvement or by worsening features despite ongoing treatment.\u003c/p\u003e\n\u003cp\u003eSteroid resistance in sarcoidosis was defined as the lack of a significant clinical or radiological response despite receiving adequate doses of corticosteroids (typically 20\u0026ndash;40 mg/day) for at least 4\u0026ndash;6 weeks. Additionally, relapse or worsening of the disease while on maintenance corticosteroid therapy, or persistent inflammation on imaging or laboratory markers, was considered indicative of resistance.\u003c/p\u003e\n\u003cp\u003eIn this study, the primary outcome measure was the requirement for disease-modifying agents (DMAs) beyond corticosteroids. The study cohort was divided into two outcome groups based on their therapeutic needs:\u003c/p\u003e\n\u003cp\u003eSteroid-Responsive Group: These patients demonstrated significant clinical and radiological improvement with corticosteroid therapy alone (typically prednisone 20\u0026ndash;40 mg/day), and did not require additional disease-modifying agents. They remained stable on maintenance corticosteroid doses (5\u0026ndash;15 mg/day) without relapse or worsening symptoms.\u003c/p\u003e\n\u003cp\u003eSteroid-Resistant Group: These patients exhibited persistent symptoms, radiographic abnormalities, or disease progression despite adequate corticosteroid therapy. This group required additional immunosuppressive or steroid-sparing agents, such as methotrexate, azathioprine, mycophenolate mofetil, or biologics (e.g., TNF-\u0026alpha; inhibitors), to achieve disease control.\u003c/p\u003e\n\u003cp\u003eOutcome Assessment\u003c/p\u003e\n\u003cp\u003eThe distinction between the two groups was based on:\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003eClinical Response: Improvement in symptoms such as cough, dyspnea, or chest discomfort.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eRadiological Response: Resolution or significant reduction of granulomatous inflammation on HRCT.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eLaboratory Markers: sACE levels post-therapy.\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n\u003ch2\u003e2.3. Laboratory Biomarker Assessment\u003c/h2\u003e\n\u003cp\u003eVenous blood samples were collected from all patients diagnosed with sarcoidosis. After 4 to 6 weeks of corticosteroid therapy, serum angiotensin-converting enzyme (sACE) levels were measured using the Kasahara colorimetric method. The method employed p-hydroxyhippuryl-l-histidyl-l-leucine as the substrate, and the normal reference range for sACE in the laboratory was 8\u0026ndash;65 units per liter. An sACE level of 64 units per liter was selected as the cut-off value based on prior studies and clinical relevance.\u003c/p\u003e\n\u003cp\u003eThe measurement of serum angiotensin-converting enzyme (sACE) levels was performed 4 to 6 weeks after initiating corticosteroid therapy to evaluate their potential role as predictive markers of steroid resistance. Baseline sACE levels were not included as the primary objective was to assess post-treatment levels rather than initial diagnostic values. Furthermore, reduction trends in sACE post-therapy were not analyzed due to logistical constraints. An sACE level greater than 64 U/L was used as the cut-off value for predicting steroid resistance, based on prior studies demonstrating its sensitivity (83%) and specificity (73%) in identifying patients with poor corticosteroid responsiveness.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n\u003ch2\u003e2.5. Statistical Analysis\u003c/h2\u003e\n\u003cp\u003eDescriptive statistics were employed to summarize demographic and clinical cha-racteristics. Continuous variables were reported as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation for normally distributed data and as median with interquartile range for non-normally distributed data. Categorical variables were expressed as frequencies and percentages.\u003c/p\u003e\n\u003cp\u003eFor statistical comparisons, a range of tests was employed depending on the variable type. Categorical variables were analyzed using the Chi-square test to assess associations with the need for disease-modifying agents. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using a univariate logistic regression model. A p-value of less than 0.05 was considered statistically significant.\u003c/p\u003e\n\u003cp\u003eReceiver operating characteristic (ROC) analysis was performed to determine the sensitivity, specificity, and optimal cut-off value for sACE in predicting steroid resis-tance. To identify independent predictors of steroid resistance, multivariate logistic re-gression analysis was conducted. All statistical analyses were performed using SPSS software version 22.0.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003eA study involving 191 patients with biopsy-confirmed sarcoidosis was conducted, with 3 patients excluded due to their use of serum angiotensin-converting enzyme inhibitors that can affect serum angiotensin converting enzyme levels. The mean age of participants was 54 years (\u0026plusmn;\u0026thinsp;13.8), and 116 (61.7%) of them were female. The majority of patients (116, 61.7%) had pulmonary involvement, while 18 (9.6%) had gastrointestinal involvement, 18 (9.6%) presented with uveitis, 16 (8.5%) had generalized lymphadenopathy, and smaller proportions had erythemanodosum (6, 3.2%), salivary gland involvement (6, 3.2%), cardiac involvement (4, 2.1%), kidney involvement (2, 1.1%), and facial nerve involvement (2, 1.1%).\u003c/p\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003e3.1. Clinical Characteristics\u003c/h2\u003e\n \u003cp\u003eThe most common presenting symptoms were cough (106 patients, 56%), dyspnea (105 patients, 55%), fatigue (23 patients, 12%), fever (36 patients, 19%), chest pain (31 patients, 16%), and arthralgia (48 patients, 26%). A total of 17 patients (9%) were asymptomatic asymptomatic at time of presentation in view of respiratory symptoms.The most frequent comorbidities were diabetes mellitus (62 patients, 33%), hypertension (55 patients, 29%), and hypothyroidism (22 patients, 12%).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003e3.2. Radiological Findings and Hypercalcemia\u003c/h2\u003e\n \u003cp\u003eRadiological findings indicated that the majority of patients were diagnosed with Stage I as shown in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u0026nbsp;\u0026nbsp;\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eBaseline characteristics of study population.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCharacter\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eN\u0026thinsp;=\u0026thinsp;188, Median\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e(Percentage/Range)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53\u0026thinsp;\u0026plusmn;\u0026thinsp;13.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGender Male\u003c/p\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e72 (38.3%)\u003c/p\u003e\n \u003cp\u003e116 (61.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSmokers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18 (9.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePatient history of ATT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25 (13.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCo-morbidities: Diabetes mellitus\u003c/p\u003e\n \u003cp\u003eHypertension\u003c/p\u003e\n \u003cp\u003eHypothyroid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e62 (33.0%)\u003c/p\u003e\n \u003cp\u003e55 (29.3%)\u003c/p\u003e\n \u003cp\u003e22 (11.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHypercalcemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20 (10.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMantoux Positive\u003c/p\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25 (13.3%)\u003c/p\u003e\n \u003cp\u003e133 (76.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChest X-ray stage Stage I\u003c/p\u003e\n \u003cp\u003eStage II\u003c/p\u003e\n \u003cp\u003eStage III\u003c/p\u003e\n \u003cp\u003eStage IV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e59 (31.4%)\u003c/p\u003e\n \u003cp\u003e54 (28.7%)\u003c/p\u003e\n \u003cp\u003e16 (8.5%)\u003c/p\u003e\n \u003cp\u003e6 (3.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCECT Mediastinal lymph node\u003c/p\u003e\n \u003cp\u003eInterseptal thickening ground glass opacity\u003c/p\u003e\n \u003cp\u003eFibrosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e89 (47.3%)\u003c/p\u003e\n \u003cp\u003e52 (27.7%)\u003c/p\u003e\n \u003cp\u003e12 (6.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMode of diagnosis c TBNA\u003c/p\u003e\n \u003cp\u003eEBUS-TBNA\u003c/p\u003e\n \u003cp\u003eEBB\u003c/p\u003e\n \u003cp\u003eTBLB\u003c/p\u003e\n \u003cp\u003eBiopsy from other site\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (3.1%)\u003c/p\u003e\n \u003cp\u003e72 (38.2%)\u003c/p\u003e\n \u003cp\u003e4 (2.1%)\u003c/p\u003e\n \u003cp\u003e34 (18.1%)\u003c/p\u003e\n \u003cp\u003e72 (38.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eANA positive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27 (14.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003es ACE\u0026thinsp;\u0026gt;\u0026thinsp;64 U/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e77(41%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNeed for additional immunomodulators\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47 (25%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e*N\u0026thinsp;=\u0026thinsp;total number of samples\u003c/p\u003e\n \u003cp\u003eHypercalcemia was observed in 20 patients (10.6%) and showed a significant association with the requirement for disease-modifying agents as shown in Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e.\u0026nbsp;\u003c/p\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eAssociation of Clinical and Radiological Variables with the Requirement for Disease-Modifying Agents in Sarcoidosis Patients.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" style=\"width: 18.8014%;\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" style=\"width: 21.1516%;\"\u003e\n \u003cp\u003eDisease\u003c/p\u003e\n \u003cp\u003eModifying-agent required\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDisease\u003c/p\u003e\n \u003cp\u003eModifying-agent not required\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOdds ratio\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95% Confidence interval\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 18.8014%;\"\u003e\n \u003cp\u003eGender Male\u003c/p\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 21.1516%;\"\u003e\n \u003cp\u003e15(20.8%)\u003c/p\u003e\n \u003cp\u003e32(27.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e57(79.2%)\u003c/p\u003e\n \u003cp\u003e84(72.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.448\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.719\u0026ndash;2.914\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.299\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 18.8014%;\"\u003e\n \u003cp\u003eSmoking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 21.1516%;\"\u003e\n \u003cp\u003e4(22.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14(77.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.844\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.264\u0026ndash;2.702\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.775\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 18.8014%;\"\u003e\n \u003cp\u003ePatient history of ATT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 21.1516%;\"\u003e\n \u003cp\u003e6(24%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19(76%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.940\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.351\u0026ndash;2.513\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.901\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 18.8014%;\"\u003e\n \u003cp\u003eCough\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 21.1516%;\"\u003e\n \u003cp\u003e30(28.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e76(71.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.509\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.764\u0026ndash;2.982\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.235\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 18.8014%;\"\u003e\n \u003cp\u003eFatigue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 21.1516%;\"\u003e\n \u003cp\u003e11(47.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12(52.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.285\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.339\u0026ndash;8.060\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003e0.007\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 18.8014%;\"\u003e\n \u003cp\u003eHypercalcemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 21.1516%;\"\u003e\n \u003cp\u003e10(50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10(50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.514\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.359\u0026ndash;9.081\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003e0.007\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 18.8014%;\"\u003e\n \u003cp\u003eCECT\u003c/p\u003e\n \u003cp\u003eMediastinal lymph node\u003c/p\u003e\n \u003cp\u003eGround glass opacities\u003c/p\u003e\n \u003cp\u003eFibrosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 21.1516%;\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e20(22.5%)\u003c/p\u003e\n \u003cp\u003e18(34.6%)\u003c/p\u003e\n \u003cp\u003e5(41.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e69(77.5%)\u003c/p\u003e\n \u003cp\u003e34(65.4%)\u003c/p\u003e\n \u003cp\u003e7(58.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003e0.044\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 18.8014%;\"\u003e\n \u003cp\u003eThorax\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 21.1516%;\"\u003e\n \u003cp\u003e35(30.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e81(69.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.160\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.035\u0026ndash;4.509\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003e0.038\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 18.8014%;\"\u003e\n \u003cp\u003eGastrointestinal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 21.1516%;\"\u003e\n \u003cp\u003e5(27.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13(72.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.172\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.395\u0026ndash;3.482\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.775\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 18.8014%;\"\u003e\n \u003cp\u003eKidney\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 21.1516%;\"\u003e\n \u003cp\u003e1(50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1(50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.185\u0026ndash;49.285\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.415\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 18.8014%;\"\u003e\n \u003cp\u003eUveitis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 21.1516%;\"\u003e\n \u003cp\u003e6(33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12(66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.573\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.555\u0026ndash;4.456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.391\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 18.8014%;\"\u003e\n \u003cp\u003eErythema nodosum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 21.1516%;\"\u003e\n \u003cp\u003e1(16.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5(83.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.591\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.067\u0026ndash;5.194\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.632\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 18.8014%;\"\u003e\n \u003cp\u003eCardiac\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 21.1516%;\"\u003e\n \u003cp\u003e1(25.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3(75.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.102\u0026ndash;9.852\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 18.8014%;\"\u003e\n \u003cp\u003eSalivary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 21.1516%;\"\u003e\n \u003cp\u003e3(50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3(50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.136\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.611\u0026ndash;16.102\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.151\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 18.8014%;\"\u003e\n \u003cp\u003eGeneralized lymph node\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 21.1516%;\"\u003e\n \u003cp\u003e7(43.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9(56.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.567\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.899\u0026ndash;7.329\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.070\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 18.8014%;\"\u003e\n \u003cp\u003eACE level\u0026thinsp;\u0026lt;\u0026thinsp;64 U/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 21.1516%;\"\u003e\n \u003cp\u003e13(10.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e109(89.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.909\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.205\u0026ndash;18.876\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003e\u0026lt;\u0026thinsp;0.001\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n \u003ch2\u003e3.3 Need for Immunomodulatory Therapy\u003c/h2\u003e\n \u003cp\u003eA total of 47 patients (25%) required disease-modifying agents, while 141 patients (75%) did not. Within the group requiring immunomodulatory therapy, 32 patients (27.6%) were female, and 15 (20.8%) were male. In the group that did not require immunomodulatory therapy, 84 patients (72.4%) were female, and 57 (79.2%) were male. Gender differences between the two groups were statistically significant.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003e3.4 Serum ACE Levels\u003c/h2\u003e\n \u003cp\u003eThe mean serum ACE level for the entire cohort was 64\u0026thinsp;\u0026plusmn;\u0026thinsp;61 IU/L, with levels ranging from 1 to 490 IU/L. Elevated serum ACE levels (\u0026gt;\u0026thinsp;64 IU/L) were observed in 77 patients (41%) [Figure \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003e3.5 ROC Curve Analysis\u003c/h2\u003e\n \u003cp\u003eThe ROC curve analysis confirmed that a serum ACE level of 64 IU/L was the optimal cut-off for distinguishing patients requiring immunomodulatory therapy. The area under the curve (AUC) was significant, with a sensitivity of 83% and specificity of 73%, supporting the potential of serum ACE as a predictive biomarker for steroid resistance in sarcoidosis [Figure \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003e3.6 Factors Associated with Steroid Resistance\u003c/h2\u003e\n \u003cp\u003eUnivariate analysis identified several factors significantly associated with steroid resistance, including elevated serum ACE levels (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), fatigue (p\u0026thinsp;=\u0026thinsp;0.002), hypercalcemia (p\u0026thinsp;=\u0026thinsp;0.007), thoracic involvement (p\u0026thinsp;=\u0026thinsp;0.038), and ground-glass opacities on HRCT (p\u0026thinsp;=\u0026thinsp;0.044) [Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eThe study utilized multivariate binary logistic regression was used to analyze factors influencing the requirement of disease-modifying agents (DMAs) in sarcoidosis .It revealed that elevated serum ACE levels (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), age\u0026thinsp;\u0026gt;\u0026thinsp;54 years (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), fatigue (p\u0026thinsp;=\u0026thinsp;0.002), hypercalcemia (p\u0026thinsp;=\u0026thinsp;0.019), and specific radiological findings (e.g., CECT showing mediastinal lymph node involvement, p\u0026thinsp;=\u0026thinsp;0.036) were independent risk factors for requiring immunomodulatory therapy [Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u0026nbsp;\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eLogistic regression analysis of factors influencing disease-modifying agent requirement in sarcoidosis\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eWald\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95% Confidence interval\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e53\u0026thinsp;\u0026plusmn;\u0026thinsp;13.8 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003e\u0026lt;\u0026thinsp;0.001\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDyspnea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.330\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.719\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.068\u0026ndash;1.022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003e0.054\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFatigue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.663\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.141\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.551\u0026ndash;80.552\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003e0.002\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCalcium\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.709\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.520\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.328\u0026ndash;22.988\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003e0.019\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCECT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.357\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.387\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.163\u0026ndash;95.771\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003e0.036\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThorax\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.982\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.998\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.096\u0026ndash;1.461\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.157\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eErythema nodosum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.164\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.054\u0026ndash;25.463\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.917\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCardiac\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.550\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.835\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.170\u0026ndash;130.984\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.361\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSalivary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.491\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.787\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.975\u0026ndash;1104.034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003e0.052\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eACE level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.997\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24.132\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.050\u0026ndash;268.276\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003e\u0026lt;\u0026thinsp;0.001\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis study evaluated the role of serum angiotensin-converting enzyme (sACE) le-vels as a predictive biomarker for steroid responsiveness in patients with sarcoidosis. Our findings demonstrated that elevated sACE levels (\u0026gt;\u0026thinsp;64 U/L) were significantly associated with steroid resistance, reinforcing their potential utility in identifying patients who may require additional immunomodulatory therapy. The sensitivity and specificity of sACE levels in predicting steroid resistance were found to be 83% and 73%, respectively, which aligns well with previous studies suggesting sACE as a useful marker of active granulomatous inflammation and steroid resistance [4,5] .\u003c/p\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Interpretation of findings\u003c/h2\u003e \u003cp\u003eThe high sensitivity and specificity observed in this study indicate that elevated sACE levels serve as a reliable predictor for identifying patients who may not respond adequately to corticosteroid therapy. This finding is crucial for early risk stratification and guiding therapeutic decisions, as it allows clinicians to identify patients who are more likely to require disease-modifying agents (DMAs) beyond corticosteroids.\u003c/p\u003e \u003cp\u003eIn our cohort, 25% of patients required additional immunomodulatory therapy, and these patients had significantly higher sACE levels compared to those managed with corticosteroids alone. Multivariate logistic regression revealed that elevated sACE levels, age over 54 years, hypercalcemia, and fatigue were independent predictors of steroid resistance. These results align with previous studies demonstrating that increased sACE levels correlate with more active disease and a greater likelihood of requiring additional immunosuppressive treatment [5,14].\u003c/p\u003e \u003cp\u003eThe presence of fatigue as an independent predictor is noteworthy, as it highlights the systemic nature of sarcoidosis and its impact on patient well-being. Fatigue is a common and debilitating symptom in sarcoidosis, often reflecting ongoing disease ac-tivity or systemic inflammation. Its association with steroid resistance indicates that patients who present with significant fatigue may require closer monitoring and more aggressive treatment. Additionally, hypercalcemia was significantly associated with steroid resistance, consistent with the known pathophysiological mechanisms where sarcoid granulomas produce 1α-hydroxylase, leading to increased calcitriol production and hypercalcemia [16]. This finding further underscores the need for comprehensive biochemical assessment in sarcoidosis management.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Serum ACE as a biomarker\u003c/h2\u003e \u003cp\u003eIn our study, the serum angiotensin-converting enzyme (sACE) level demonstrated a sensitivity of 83% and a specificity of 73% for predicting steroid resistance in sarcoidosis patients. While the high sensitivity indicates that elevated sACE levels are effective in identifying patients likely to exhibit resistance to corticosteroid therapy, the relatively lower specificity suggests that not all patients with elevated sACE levels will necessarily develop steroid resistance. This discrepancy can be attributed to the presence of other conditions that can also raise sACE levels, such as tuberculosis, silicosis, and hyperthyroidism, which may confound the accuracy of sACE as a sole predictive marker [17,3]. Additionally, variations in genetic predisposition and disease heterogeneity may also influence sACE levels, resulting in false positives. Therefore, while sACE is a useful adjunct in predicting steroid resistance, it should not be used in isolation. Instead, it is best interpreted alongside clinical and radiological findings to enhance decision-making and improve patient stratification.\u003c/p\u003e \u003cp\u003esACE has long been considered a potential biomarker for sarcoidosis, primarily due to its production by epithelioid cells within granulomas. While earlier studies questioned its utility due to inconsistent sensitivity and specificity, our study reaffirms that elevated sACE levels are indicative of active granulomatous inflammation and potential steroid resistance. Previous reports have documented wide variations in sACE sensitivity (41\u0026ndash;100%) and specificity (83\u0026ndash;99%), partly attributed to heterogeneity in study populations and variations in disease presentation [3] .\u003c/p\u003e \u003cp\u003eHowever, recent studies have highlighted that while sACE levels alone may not suffice as a definitive diagnostic marker, they hold substantial value in predicting disease activity and relapse when used as part of a comprehensive assessment. Our findings support the growing consensus that sACE can serve as a valuable adjunct to clinical and radiographic evaluations, particularly in identifying patients who may not adequately respond to steroids alone. The renewed interest in sACE as a biomarker has been driven by its ability to stratify patients at risk of relapse or progression, thereby guiding the early initiation of steroid-sparing agents, such as methotrexate, azathioprine, or TNF-α inhibitors [5,14].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Relevance to Clinical Practice\u003c/h2\u003e \u003cp\u003eFrom a clinical perspective, identifying patients at risk of steroid resistance is essential to reducing prolonged corticosteroid exposure and associated adverse effects. Our findings suggest that monitoring sACE levels after 4 to 6 weeks of corticosteroid therapy can help identify those who may benefit from early intervention with additional immunosuppressive agents. The integration of sACE measurement into routine practice could enhance decision-making, particularly for patients who present with risk factors such as fatigue, hypercalcemia, or advanced age.\u003c/p\u003e \u003cp\u003eAdditionally, our study contributes to the ongoing debate regarding the utility of sACE as a standalone marker. While our data demonstrate its relevance as a predictive tool, it remains essential to interpret sACE levels in conjunction with clinical, radiological, and laboratory data. This multimodal approach ensures that therapeutic decisions are based on comprehensive patient assessments rather than relying solely on single biomarker values.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e4.4 Strength and limitations\u003c/h2\u003e \u003cp\u003eThe strengths of this study include its prospective design, the use of biop-sy-confirmed sarcoidosis cases, and the application of robust statistical methods to identify independent predictors of steroid resistance. Moreover, the assessment of sACE levels post-therapy provided valuable insights into their prognostic utility rather than simply evaluating baseline levels.\u003c/p\u003e \u003cp\u003eHowever, several limitations should be considered. Firstly, baseline sACE levels before corticosteroid initiation were not measured, as the primary objective was to assess post-treatment levels as predictors of resistance. This approach limited the evaluation of dynamic changes in sACE levels over time. Additionally, the study did not investigate the long-term outcomes of patients who transitioned to second-line therapies, which could offer further insights into treatment effectiveness. Furthermore, the study was conducted at a single tertiary care center, which may limit the generalizability of the findings. While serum levels of angiotensin-converting enzyme (sACE) can be raised in a substantial proportion of patients, their diagnostic value remains low [18].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e4.5 Future Perspective\u003c/h2\u003e \u003cp\u003eFurther large-scale, multicenter studies are needed to validate our findings and explore the long-term outcomes of patients stratified by sACE levels. Additionally, investigating serial changes in sACE levels over the course of treatment could provide insights into their role as a dynamic biomarker. Integrating sACE measurements with other promising biomarkers, such as soluble interleukin-2 receptor (sIL-2R) levels, could enhance the accuracy of predicting treatment outcomes[19,20].Developing standardized protocols for measuring and interpreting sACE levels will also be essential to improve reproducibility and clinical utility. Ultimately, incorporating sACE assessment into routine practice as part of a multimodal approach could help reduce unnecessary corticosteroid exposure and enable early initiation of more targeted therapies, thereby optimizing patient outcomes\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e4.6 Implications for Practice\u003c/h2\u003e \u003cp\u003eThe integration of sACE levels into routine clinical practice has the potential to guide early decision-making, particularly in identifying patients who are likely to require additional immunosuppressive therapy. However, the moderate specificity observed in our study calls for cautious interpretation, emphasizing the need for a comprehensive, multimodal approach that includes clinical, radiological, and laboratory assessments. While sACE serves as a valuable adjunct, it should not replace thorough clinical evaluation when determining treatment plans.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eOur study highlights the importance of a personalized approach in sarcoidosis management, emphasizing the role of serum angiotensin-converting enzyme (sACE) as a biomarker for predicting steroid resistance. An sACE level greater than 64 U/L was significantly associated with the need for additional immunosuppressive therapy, with a specificity of 73% and a sensitivity of 83%. Fatigue and hypercalcemia (Ca\u0026thinsp;\u0026gt;\u0026thinsp;10 mg/dL) also emerged as independent predictors of steroid resistance.\u003c/p\u003e \u003cp\u003eLocalized thoracic sarcoidosis showed a negative association with the need for additional immunosuppressants, suggesting a milder disease course. Reducing glucocorticoid dependence through the use of steroid-sparing agents and comprehensive patient assessment should be prioritized. Additionally, adopting a holistic care model that includes lifestyle changes and mental health support can enhance overall patient well-being and adherence to therapy.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eThe following abbreviations are used in this manuscript:\u003c/p\u003e\n\u003cp\u003esACE\u0026nbsp; \u0026nbsp; \u0026nbsp;Serum Angiotensin-Converting Enzyme\u003c/p\u003e\n\u003cp\u003eILD\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Interstitial Lung Disease\u003c/p\u003e\n\u003cp\u003eGCs\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Glucocorticoids\u003c/p\u003e\n\u003cp\u003eATS\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;American Thoracic Society\u003c/p\u003e\n\u003cp\u003eERS\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;European Respiratory Society\u003c/p\u003e\n\u003cp\u003eWASOG\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;World Association for Sarcoidosis and Other Granulomatous Disorders\u003c/p\u003e\n\u003cp\u003eQoL\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Quality of Life\u003c/p\u003e\n\u003cp\u003eFDA\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Food and Drug Administration\u003c/p\u003e\n\u003cp\u003eHRCT\u0026nbsp; \u0026nbsp;\u0026nbsp;High-Resolution Computed Tomography\u003c/p\u003e\n\u003cp\u003eTBNA\u0026nbsp; \u0026nbsp;Transbronchial Needle Aspiration\u003c/p\u003e\n\u003cp\u003eEBUS-TBNA\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Endobronchial Ultrasound-Guided Transbronchial Needle Aspiration\u003c/p\u003e\n\u003cp\u003eEBB\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Endobronchial Biopsy\u003c/p\u003e\n\u003cp\u003eTBLB\u0026nbsp; \u0026nbsp; \u0026nbsp;Transbronchial Lung Biopsy\u003c/p\u003e\n\u003cp\u003eANA\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Antinuclear Antibody\u003c/p\u003e\n\u003cp\u003eATT\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Anti-Tuberculosis Treatment\u003c/p\u003e\n\u003cp\u003eCECT\u0026nbsp; \u0026nbsp;\u0026nbsp;Contrast-Enhanced Computed Tomography\u003c/p\u003e\n\u003cp\u003esACE \u0026nbsp; \u0026nbsp; Serum Angiotensin-Converting Enzyme\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eEthics approval and consent to participate:\u003c/h2\u003e\n\u003cp\u003eThe study was conducted in accordance with the Declaration of Helsinki, and the protocol was approved by the Ethics Committee of Amrita Institute of Medical Sciences and Research, Kochi (ECASM-AIMS-2022-109) on 07/06/2022.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed Consent\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eStatement\u003c/strong\u003e: Informed consent was obtained from all subjects involved in the study.\u003c/p\u003e\n\u003ch2\u003eCompeting interests\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no competing interests\u003c/p\u003e\n\u003ch2\u003eFunding:\u003c/h2\u003e\n\u003cp\u003eThis research received no external funding\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eConceptualization: A.A.M. ; methodology, A.A.M. ; software, A.A.M. ; formal analysis, A.A.M., L.V.P. ; investigation, A.A.M., G.G. ,L.A . ; data curation, A.A.M. , G.G. ,L.A. ; writing\u0026mdash;original draft preparation, A.A.M. , L.V.P. ; writing\u0026mdash;review and editing, A.A.M. , L.V.P. ;. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgement\u003c/h2\u003e\n\u003cp\u003eWe sincerely thank Dr. Sreekumar P and Dr. Rajasekaran from Amrita Institute of Medical Sciences for their invaluable assistance in interpreting CT chest scans for this study. Their expertise and support were instrumental in achieving accurate radiological assessments.\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eThe data supporting the findings of this study are available at the following link:https://docs.google.com/spreadsheets/d/1KDNkP8QDuHZ9mWWA8LWaMSaAHFDizgQWM1q37Hxyc_w/edit?usp=sharing\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSeve P, Pacheco Y, Durupt F, et al. Sarcoidosis: A Clinical Overview from Symptoms to Diagnosis. Cells. 2021;10(4):766. Published 2021 Mar 31.(1a).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGrunewald J, Grutters JC, Arkema EV, et al. Sarcoidosis Nat Rev Dis Primer. 2019;5(1):1\u0026ndash;22.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKraaijvanger R, Janssen BM, Vorselaars ADM, et al. Biomarkers in the Diagnosis and Prognosis of Sarcoidosis: Current Use and Future Prospects. Front Immunol. 2020;11:1443.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGoldman C, Judson MA. Corticosteroid refractory sarcoidosis. Respir Med. 2020;171:106081.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBaughman RP, Valeyre D, Korsten P et al. ERS clinical practice guidelines on treatment of sarcoidosis. Eur Respir J. 2021;58(6):2004079. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1183/13993003.04079-2020\u003c/span\u003e\u003cspan address=\"10.1183/13993003.04079-2020\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 34140301.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJudson MA. The treatment of pulmonary sarcoidosis. Respir Med. 2012;106(10):1351\u0026ndash;61.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMelani AS, Bigliazzi C, Cimmino FA, et al. A Comprehensive Review of Sarcoidosis Treatment for Pulmonologists. Pulm Ther. 2021;7(2):325\u0026ndash;44.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDenys BG, Bogaerts Y, Coenegrachts KL, et al. Steroid-resistant sarcoidosis: is antagonism of TNF-alpha the answer? Clin Sci (Lond). 2007;112(5):281\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJeny F, Nunes H, Valeyre D. In sarcoidosis trials, time also matters. Eur Respir J. 2024;63(1):2301629. Published 2024 Jan 18.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDrent M, Crouser ED, Grunewald J. Challenges of Sarcoidosis and Its Management. Longo DL, editor. N Engl J Med. 2021;385(11):1018\u0026ndash;32.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMoor CC, Obi ON, Kahlmann V, et al. Quality of life in sarcoidosis. J Autoimmun. 2024;149:103123.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLopez SM, Caratti DLL, Danser AHJ, et al. Focus on increased serum angiotensin-converting enzyme level: From granulomatous diseases to genetic mutations. Clin Biochem. 2018;59:1\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDruyan A, Shuv N, Lidar M. Put Down the ACE: Low Clinical Utility for Angiotensin-Converting Enzyme Levels in Sarcoidosis: A Single-Center Retrospective Cohort Study. J Clin Med. 2024;13(24):7657.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZheng SY, Du X, Dong JZ. Re-evaluating Serum Angiotensin-Converting Enzyme in Sarcoidosis. Front Immunol. 2023;14:950095.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHu X, Zou L, Wang S, et al. Performance of Serum Angiotensin-Converting Enzyme in Diagnosing Sarcoidosis and Predicting the Active Status of Sarcoidosis: A Meta-Analysis. Biomolecules. 2022;12(10):1400.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTebben PJ, Singh RJ, Kumar R, Vitamin D-M, Hypercalcemia. Mechanisms, Diagnosis, and Treatment. Endocr Rev. 2016;37(5):521\u0026ndash;47.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHoy RF, Hansen J, Glass DC, et al. Serum angiotensin converting enzyme elevation in association with artificial stone silicosis. Respir Med. 2021;177:106289.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGrunewald J, Grutters JC, Arkema EV, et al. Sarcoidosis. Nat Rev Dis Primer. 2019;5(1):1\u0026ndash;22.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhou Y, Chen X, Zhao M, et al. SACE and IL-2R as serum biomarkers for evaluation of multi-organ involvement and prognosis of sarcoidosis. Respir Res. 2023;24:219.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDella ZM, Bertuccio FR, Campo I, et al. Phenotypes and Serum Biomarkers in Sarcoidosis. Diagnostics. 2024;14(7):709.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"sarcoidosis, angiotensin-converting enzyme level, corticosteroids, steroid resistance, immunomodulators","lastPublishedDoi":"10.21203/rs.3.rs-6560786/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6560786/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Sarcoidosis is a systemic inflammatory disease characterized by non-caseating granulomas in multiple organs, predominantly the lungs. Corticosteroids are the first-line treatment; however, steroid resistance remains a significant challenge. This study aims to evaluate serum angiotensin-converting enzyme (sACE) levels as a biomarker for predicting steroid resistance in sarcoidosis patients.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e This prospective study was conducted at a tertiary care center and included patients with biopsy-confirmed sarcoidosis. Serum ACE levels were measured after 4 to 6 weeks of corticosteroid therapy using the Kasahara colorimetric technique. The association between sACE levels and steroid resistance was evaluated. Statistical analysis was performed using SPSS version 20, with a significance threshold set at p \u0026lt; 0.05.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e A total of 188 sarcoidosis patients (mean age: 54 years, 62% women) were included. Common symptoms included cough, dyspnea, fatigue, fever, chest pain, and arthralgia. Hypercalcemia was observed in 11% of patients. ROC analysis revealed that sACE \u0026gt;64 U/L had 83% sensitivity and 73% specificity in predicting steroid resistance. Univariate analysis identified fatigue, hypercalcemia, fibrosis on chest CT, and elevated sACE levels as associated factors, while multivariate analysis confirmed elevated serum ACE levels (p \u0026lt; 0.001), age \u0026gt;54 years (p \u0026lt; 0.001), fatigue (p = 0.002), hypercalcemia (p = 0.019), and specific radiological findings (e.g., CECT showing mediastinal lymph node involvement, p = 0.036)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e Serum ACE levels \u0026gt;64 U/L are a potential biomarker for steroid resistance in sarcoidosis. However, further research and a multidisciplinary approach are needed to validate these findings and improve clinical management.\u003c/p\u003e","manuscriptTitle":"Role of serum angiotensin-converting enzyme (sACE) level as a biomarker for predicting steroid response in patients with sarcoidosis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-27 06:13:31","doi":"10.21203/rs.3.rs-6560786/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5de0e5d7-e7e3-416c-81f2-62773a913c24","owner":[],"postedDate":"May 27th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-07-29T14:38:55+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-27 06:13:31","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6560786","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6560786","identity":"rs-6560786","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}