Abstract
Background:
Sarcoidosis is a heterogeneous multisystem granulomatous disease with an unpredictable clinical course. Reliable biomarkers for predicting relapse remain limited. The Prognostic Nutritional Index (PNI), reflecting systemic inflammation and immunonutritional status, has emerged as a prognostic marker in various inflammatory and pulmonary diseases. However, its role in sarcoidosis has not been sufficiently clarified. This study aimed to investigate the association between baseline PNI levels and relapse in patients with sarcoidosis.
Methods:
This retrospective single-center study included 302 adult patients diagnosed with sarcoidosis between January 2015 and January 2025. Baseline was defined as the date of initial sarcoidosis diagnosis at our center, or, for patients diagnosed externally, the date of first evaluation at our center before treatment initiation or escalation. Laboratory parameters obtained at this baseline time point, including serum albumin, lymphocyte count, C-reactive protein (CRP), neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR), were recorded. PNI was calculated as: 10 × serum albumin (g/dL) + 0.005 × total lymphocyte count (/mm3). The primary outcome was disease relapse during follow-up. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the predictive performance of baseline PNI.
Results:
Relapse occurred in 52 patients (17.2%) during follow-up. Patients who developed relapse had significantly lower baseline albumin levels, lymphocyte counts, and PNI values, and significantly higher CRP, NLR, and PLR levels (all p<0.01). Baseline PNI demonstrated excellent discriminative ability for predicting relapse, with an area under the curve (AUC) of 0.922 (95% CI: 0.887–0.957, p<0.001). A cutoff value of ≤39.25 yielded a sensitivity of 94.2% and a specificity of 82.8%.
Conclusion:
Lower baseline PNI values are strongly associated with relapse in patients with sarcoidosis and show excellent predictive performance. As a simple, inexpensive, and widely available biomarker reflecting both inflammatory burden and immune competence, PNI may serve as a practical tool for risk stratification and individualized follow-up in clinical practice. Prospective multicenter studies are warranted to validate these findings.
Keywords: sarcoidosis, prognostic nutritional index, relapse
Introduction
Sarcoidosis is a multisystem granulomatous disease of unknown etiology that most commonly affects the lungs and intrathoracic lymph nodes. The clinical course is highly heterogeneous, ranging from spontaneous remission to chronic or progressive disease characterized by relapses and the need for prolonged immunosuppressive therapy. Despite advances in diagnostic and therapeutic approaches, predicting disease activity, relapse, and long term outcomes remains challenging. Current clinical practice guidelines emphasize the limitations of conventional radiological staging and pulmonary function tests in accurately reflecting inflammatory activity and predicting disease course in individual patients (1).
Chronic systemic inflammation and immune dysregulation play a central role in the pathogenesis of sarcoidosis. Recent translational studies have highlighted persistent Th1/Th17-driven immune activation, macrophage polarization, and cytokine mediated tissue remodeling as contributors to disease heterogeneity and progression (2, 3). Sustained inflammatory activity has been associated with more severe pulmonary involvement, systemic manifestations, and an increased likelihood of relapse (3).
Systemic inflammation is closely intertwined with nutritional and immunological status. Inflammatory processes influence hepatic protein synthesis, including serum albumin levels, and alter circulating lymphocyte profiles, thereby affecting both metabolic and immune homeostasis. Composite indices integrating these parameters have gained attention as practical markers reflecting the interaction between inflammation and host immune competence (4).
The Prognostic Nutritional Index (PNI), calculated from serum albumin concentration and peripheral lymphocyte count, has recently emerged as a prognostic biomarker in various chronic inflammatory and pulmonary conditions. Contemporary studies have demonstrated its association with disease severity, hospitalization risk, and mortality in interstitial lung diseases and other chronic inflammatory disorders (4, 5). However, its role in sarcoidosis remains insufficiently explored.
Recent investigations published in Sarcoidosis, Vasculitis and Diffuse Lung Diseases have underscored the prognostic relevance of systemic inflammatory markers, including leukocyte derived ratios, in identifying patients at higher risk of active disease and relapse(6). Nevertheless, whether PNI an index integrating both inflammatory burden and immune status provides additional prognostic value in sarcoidosis has not been adequately clarified.
Given that PNI reflects both systemic inflammation and immune competence, it may offer incremental prognostic information beyond conventional clinical and laboratory parameters. Therefore, the present study aimed to investigate the prognostic significance of baseline PNI levels in patients with sarcoidosis and to evaluate their association with disease course and relapse. Identifying a simple and widely available biomarker such as PNI may contribute to improved risk stratification and more individualized follow-up strategies in clinical practice.
Materials and Methods
Study design and population
This study was designed as a retrospective study. Adult patients diagnosed with sarcoidosis and followed regularly at the Department of Pulmonology, Sultan II. Abdülhamid Han Training and Research Hospital, between January 1, 2015, and January 1, 2025, were included.
The diagnosis of sarcoidosis was established based on clinical, radiological, and histopathological findings in accordance with the criteria of the American Thoracic Society (ATS), European Respiratory Society (ERS), and World Association of Sarcoidosis and Other Granulomatous Disorders (WASOG). Patients aged 18 years and older with radiologically and clinically defined sarcoidosis stages (Stage 0–IV) were eligible for inclusion.
Exclusion criteria were the presence of active infection, malignancy or hematological disease, chronic liver or renal failure, severe malnutrition, or protein-losing enteropathy. Patients with incomplete or inaccurate baseline clinical or laboratory data were also excluded from the analysis.
Data collection
Patient data were retrospectively retrieved from the hospital electronic medical records system. Collected variables included demographic characteristics (age, sex), smoking history, disease duration, diagnostic method, radiological stage, duration of follow up, presence of systemic involvement (lymph nodes, skin, ocular, cardiac, neurological, and other organ involvement), laboratory parameters, and treatment history.
Laboratory Parameters
The following laboratory parameters obtained at baseline were recorded:
- Biochemical parameters: serum albumin, total protein, aspartate aminotransferase (AST), alanine aminotransferase (ALT), urea, and creatinine
- Hematological parameters: leukocyte, neutrophil, lymphocyte, monocyte counts, hemoglobin, and platelet count
- Inflammatory markers: C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR)
Neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) were calculated from complete blood count results.
Prognostic nutritional index
The Prognostic Nutritional Index (PNI) was calculated using serum albumin levels and peripheral lymphocyte counts according to the following formula:
PNI = [10 × serum albumin (g/dL)] + [0.005 × total lymphocyte count (/mm3)]
PNI was used as a quantitative indicator reflecting both nutritional status and immune function. Baseline PNI values were evaluated in relation to clinical course and relapse development.
Clinical outcomes and definitions
The primary outcome of the study was disease relapse during follow up. In line with contemporary sarcoidosis management principles emphasizing organ specific assessment and treatment decisions, relapse was defined as the recurrence or worsening of sarcoidosis activity after a period of clinical stability, documented by at least two of the following: (1) new or worsening sarcoidosis related symptoms; (2) radiological progression on chest radiography or thoracic computed tomography; (3) deterioration in pulmonary function tests when available; (4) new or worsening extrapulmonary organ involvement; or (5) an increase in inflammatory or sarcoidosis related laboratory markers judged by the treating physician to be compatible with active disease. Relapse was not restricted to pulmonary involvement; extrapulmonary relapse involving skin, ocular, cardiac, neurological, lymph node, or other organ systems was also included when it required initiation, re initiation, or escalation of systemic therapy. Alternative causes that could mimic relapse, including respiratory infection, malignancy, heart failure, pulmonary embolism, drug related complications, and other inflammatory or granulomatous diseases, were excluded by review of clinical notes, microbiological tests when indicated, imaging findings, laboratory results, and specialist consultations. The most common relapse manifestations recorded in the cohort were worsening respiratory symptoms, radiological progression, constitutional symptoms, skin lesions, ocular involvement, and biochemical inflammatory activity. In patients who experienced relapse, laboratory parameters at baseline and at the time of relapse were compared.
Statistical analysis
Statistical analyses were performed using IBM SPSS Statistics version 30.0 (IBM Corp., Armonk, NY, USA). Categorical variables were expressed as number and percentage [n (%)], while continuous variables were presented as median and interquartile range (IQR).
Comparisons between patients with and without relapse were conducted using the Mann Whitney U test for continuous variables. Categorical variables were compared using the chi square test or Fisher’s exact test, as appropriate. In patients with relapse, baseline and relapse period laboratory parameters were compared using the Wilcoxon signed rank test.
Receiver operating characteristic (ROC) curve analysis was performed to assess the diagnostic performance of baseline PNI in predicting relapse. The area under the curve (AUC) and 95% confidence intervals were calculated using the DeLong method, and the optimal cutoff value was determined using the Youden index. A p-value <0.05 was considered statistically significant.
Ethics approval
The study was conducted in accordance with the principles of the Declaration of Helsinki. Ethical approval was obtained from the Istanbul Medipol University Non Interventional Clinical Research Ethics Committee on January 9, 2026, with decision number E-10840098-202.3.02-169.
Due to the retrospective nature of the study, the requirement for informed consent was waived by the Ethics Committee. All patient data were anonymized prior to analysis, and confidentiality was strictly maintained throughout the study.
Results
Patient characteristics
A total of 302 patients with sarcoidosis were included in the study. During the follow-up period, relapse occurred in 52 patients (17.2%), while 250 patients (82.8%) did not experience relapse. The median age of the study population was 51 years (IQR: 39–60), and 62.9% of the patients were female.
There were no significant differences between patients with and without relapse in terms of age, sex, smoking status, pack-year history, diagnostic method, or duration of follow-up (all p>0.05). Baseline demographic and clinical characteristics of patients according to relapse status are summarized in Table 1.
Table 1.
Distribution of Demographic and Clinical Characteristics of Patients with and without Relapse.
| Variables (N=302) | Total | No relapse (n=250) | Relapse (n=52) | p-value |
|---|---|---|---|---|
| n (%) or Median (IQR) | n (%) or Median (IQR) | n (%) or Median (IQR) | ||
| Sex | 0.241 | |||
| Male | 112 (37.1%) | 89 (35.6%) | 23 (44.2%) | |
| Female | 190 (62.9%) | 161 (64.4%) | 29 (55.8%) | |
| Age (years) | 51 (39–60) | 51 (39–59) | 52 (44–63) | 0.320 |
| Smoking status | 0.433 | |||
| Never smoker | 242 (80.1%) | 203 (81.2%) | 39 (75.0%) | |
| Current smoker | 54 (17.9%) | 43 (17.2%) | 11 (21.2%) | |
| Former smoker | 6 (2.0%) | 4 (1.6%) | 2 (3.8%) | |
| Pack-years | 15 (9–20) | 15 (8–20) | 15 (10–20) | 0.978 |
| Radiological stage | <0.001 | |||
| Stage 0 | 32 (10.6%) | 29 (11.6%) | 3 (5.8%) | |
| Stage 1 | 123 (40.7%) | 112 (44.8%) | 11 (21.2%) | |
| Stage 2 | 123 (40.7%) | 93 (37.2%) | 30 (57.7%) | |
| Stage 3 | 19 (6.3%) | 14 (5.6%) | 5 (9.6%) | |
| Stage 4 | 5 (1.7%) | 2 (0.8%) | 3 (5.8%) | |
| Follow-up duration (years) | 5 (3–7) | 5 (3–7) | 5 (4–6.5) | 0.642 |
| Diagnostic method | 0.077 | |||
| EBUS | 160 (53.0%) | 137 (54.8%) | 23 (44.2%) | |
| TBLB | 23 (7.6%) | 19 (7.6%) | 4 (7.7%) | |
| Mediastinoscopy | 35 (11.6%) | 25 (10.0%) | 10 (19.2%) | |
| Peripheral biopsy | 36 (11.9%) | 26 (10.4%) | 10 (19.2%) | |
| Not specified | 48 (15.9%) | 43 (17.2%) | 5 (9.6%) | |
| Systemic involvement | 99 (32.8%) | 75 (30.0%) | 24 (46.2%) | 0.024 |
| Skin | 46 (46.5%) | 37 (49.3%) | 9 (37.5%) | 0.312 |
| Ocular | 33 (33.3%) | 22 (29.3%) | 11 (45.8%) | 0.136 |
| Neurological | 8 (8.1%) | 4 (5.3%) | 4 (16.7%) | 0.095 |
| Cardiac | 4 (4.0%) | 3 (4.0%) | 1 (4.2%) | 1.000 |
| Other | 35 (35.4%) | 23 (30.7%) | 12 (50.0%) | 0.085 |
| Hypercalciuria | 18 (6.7%) | 11 (5.1%) | 7 (13.7%) | 0.055 |
| Serum ACE (U/L) | 57 (38–91) | 56.5 (37–86.5) | 63.5 (39–115.5) | 0.095 |
| Urinary calcium (mg/day) | 99 (35–194.4) | 93 (30–183) | 115 (66–224.6) | 0.034 |
| CRP (mg/L) | 4 (2–10.4) | 3.1 (2–8.2) | 8 (2–36.2) | <0.001 |
| ESR (mm/h) | 20 (11–36) | 20 (11–36) | 19 (10–38) | 0.613 |
| Serum calcium (mg/dL) | 9.5 (9.1–9.9) | 9.5 (9.1–9.9) | 9.5 (9.1–10.0) | 0.690 |
| Albumin (g/dL) | 4.2 (3.9–4.4) | 4.2 (4.1–4.5) | 3.6 (3.2–3.8) | <0.001 |
| Neutrophils (×109/L) | 4.3 (3.4–5.4) | 4.3 (3.4–5.4) | 4.4 (3.5–5.9) | 0.464 |
| Lymphocytes (×109/L) | 1.9 (1.5–2.5) | 2.0 (1.5–2.5) | 1.5 (1.1–2.2) | <0.001 |
| Monocytes (×109/L) | 0.5 (0.4–0.7) | 0.5 (0.4–0.6) | 0.6 (0.4–0.7) | 0.001 |
| Platelets (×109/L) | 265 (224–326) | 267.5 (229–321) | 240 (195–347) | 0.337 |
| PNI | 41.9 (39–44) | 42 (41–45) | 36 (32–38) | <0.001 |
| NLR | 2.2 (1.7–3.0) | 2.1 (1.6–2.9) | 2.7 (1.9–4.4) | <0.001 |
| PLR | 141.7 (104–190.6) | 137.1 (100–182.3) | 164.3 (118–256.9) | 0.006 |
| Treatment required | 146 (48.5%) | 94 (37.8%) | 52 (100%) | <0.001 |
| Mortality | 0.346 | |||
| Alive | 295 (97.7%) | 245 (98.0%) | 50 (96.2%) | |
| Death | 7 (2.3%) | 5 (2.0%) | 2 (3.8%) |
Radiological stage distribution differed significantly between the two groups (p<0.001). Patients who developed relapse had a higher proportion of Stage 2 and Stage 4 disease compared to those without relapse. In addition, systemic involvement was more frequently observed in the relapse group (46.2% vs. 30.0%, p=0.024). No significant differences were observed among individual organ involvement subgroups.
Laboratory findings according to relapse status
Baseline laboratory parameters differed significantly between patients with and without relapse (Table 1). Patients who experienced relapse had significantly higher baseline levels of C-reactive protein (CRP), neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR) (all p<0.01). In contrast, serum albumin levels, lymphocyte counts, and Prognostic Nutritional Index (PNI) values were significantly lower in the relapse group (p<0.001).
No significant differences were observed between the groups in terms of neutrophil count, platelet count, erythrocyte sedimentation rate, serum calcium, or mortality rates (p>0.05).
Comparison of baseline and relapse laboratory parameters
Among patients who developed relapse, laboratory parameters at baseline and at the time of relapse were compared (Table 2). During relapse, CRP, erythrocyte sedimentation rate, serum calcium levels, neutrophil and monocyte counts, platelet counts, NLR, and PLR values were significantly increased compared to baseline (all p<0.05).
Table 2.
Distribution of Laboratory Parameters at Baseline and at the Time of Relapse in Patients with Relapse.
| Variables | Baseline | Relapse | p-value |
|---|---|---|---|
| Median (IQR) | Median (IQR) | ||
| CRP (mg/L) | 8 (2–36.2) | 66.5 (47.5–100.5) | <0.001 |
| Erythrocyte sedimentation rate (mm/h) | 19 (10–38) | 30 (23–47) | 0.044 |
| Serum calcium (mg/dL) | 9.5 (9.1–10.0) | 10.7 (9.9–10.9) | <0.001 |
| Albumin (g/dL) | 3.6 (3.2–3.8) | 3.3 (2.6–3.9) | 0.058 |
| Neutrophils (×109/L) | 4.4 (3.5–5.9) | 7.7 (5.7–8.9) | <0.001 |
| Lymphocytes (×109/L) | 1.5 (1.1–2.2) | 1.1 (1.0–1.4) | <0.001 |
| Monocytes (×109/L) | 0.6 (0.4–0.7) | 0.8 (0.6–1.0) | 0.002 |
| Platelets (×109/L) | 240 (195–347) | 337 (246–456) | 0.002 |
| Prognostic Nutritional Index (PNI) | 36 (32–38) | 32.5 (26–39) | 0.041 |
| Neutrophil-to-lymphocyte ratio (NLR) | 2.7 (1.9–4.4) | 7.0 (5.0–8.7) | <0.001 |
| Platelet-to-lymphocyte ratio (PLR) | 164.3 (118–256.9) | 350.8 (188.2–447.1) | <0.001 |
Conversely, lymphocyte counts and PNI values were significantly lower at the time of relapse compared to baseline (p<0.05). Although serum albumin levels showed a decreasing trend during relapse, this difference did not reach statistical significance (p=0.058).
Predictive value of prognostic nutritional ındex for relapse
Receiver operating characteristic (ROC) curve analysis was performed to evaluate the predictive performance of baseline PNI for relapse development (Table 3, Figure 1). The area under the curve (AUC) for PNI was 0.922 (95% CI: 0.887–0.957), indicating excellent discriminative ability (p<0.001).
Table 3.
ROC Analysis Results of Baseline PNI for Predicting Relapse.
| Variable | AUC (95% CI) | p-value | Cut-off value | Sensitivity (%) | Specificity (%) |
|---|---|---|---|---|---|
| PNI | 0.922 (0.887–0.957) | <0.001 | ≤39.25 | 94.2 | 82.8 |
Figure 1.
Receiver operating characteristic (ROC) curve of baseline Prognostic Nutritional Index (PNI) for predicting relapse in sarcoidosis. The ROC curve demonstrates the discriminative performance of baseline PNI in predicting relapse among patients with sarcoidosis. The area under the curve (AUC) was 0.922 (95% CI: 0.887–0.957), indicating excellent predictive accuracy. A cut-off value of ≤39.25 provided a sensitivity of 94.2% and a specificity of 82.8% for relapse prediction.
Using a cutoff value of 39.25, baseline PNI predicted relapse with a sensitivity of 94.2% and a specificity of 82.8%.
Dıscussion
In this retrospective cohort of 302 patients with sarcoidosis, we demonstrated that lower baseline PNI values were strongly associated with relapse development during follow-up. Patients who experienced relapse had significantly lower albumin levels, lymphocyte counts, and PNI values at baseline, while inflammatory markers such as CRP, NLR, and PLR were significantly higher. Notably, baseline PNI showed excellent discriminative ability for relapse prediction (AUC 0.922), suggesting that this simple composite index may serve as a robust prognostic biomarker in sarcoidosis.
Predicting disease course in sarcoidosis remains a major clinical challenge despite advances in diagnostic and therapeutic strategies. The 2020 ATS clinical practice guideline emphasizes that radiological staging and pulmonary function testing do not reliably reflect inflammatory activity or predict long-term outcomes in individual patients (1). Similarly, the 2021 ERS treatment guideline highlights the heterogeneity of disease behavior and the need for better biomarkers to guide risk stratification and therapeutic decisions (2). Our findings support this unmet need and suggest that PNI may provide additional prognostic information beyond conventional clinical tools.
Systemic inflammation plays a central role in sarcoidosis pathogenesis. Recent mechanistic insights into Th1/Th17 polarization, macrophage activation, and cytokine-mediated tissue injury further reinforce the importance of persistent immune activation in driving disease progression and relapse (7). In this context, indices reflecting both inflammatory burden and immune competence may be particularly relevant. PNI, by integrating serum albumin and peripheral lymphocyte count, captures two key components of systemic inflammatory response: hepatic protein synthesis suppression and immune cell redistribution.
Our results are consistent with emerging literature on inflammatory hematologic indices in sarcoidosis. In a previously conducted study evaluating the predictive impact of hematological and biochemical parameters on the clinical course of sarcoidosis, leukocyte-derived ratios and inflammatory laboratory markers were found to be significantly associated with disease activity and clinical progression. Elevated inflammatory indices were suggested to reflect a higher inflammatory burden and a more unfavorable disease trajectory. In our cohort, NLR and PLR were likewise significantly higher in patients who developed relapse. However, PNI demonstrated superior discriminative performance compared to individual leukocyte-derived ratios. This finding may be explained by the fact that PNI incorporates both inflammatory and immunonutritional components, thereby providing a more comprehensive representation of systemic disease activity (8).
Beyond sarcoidosis, the prognostic value of PNI has been increasingly recognized in chronic inflammatory and pulmonary diseases. A large population-based study by Wu et al. demonstrated that lower PNI values were independently associated with increased mortality risk across a broad adult population, underscoring its role as a systemic inflammatory-nutritional marker (4). Similarly, recent reviews have highlighted the expanding role of PNI across clinical specialties, including respiratory diseases, emphasizing its association with adverse outcomes and disease severity (5). Although most data derive from oncology and cardiovascular populations, the biological rationale remains applicable to sarcoidosis, a disease characterized by chronic immune activation and metabolic-inflammation interplay.
The pathophysiological basis for the observed association between low PNI and relapse risk is plausible. Chronic inflammation suppresses albumin synthesis via cytokine-mediated hepatic reprioritization, while persistent immune activation may lead to lymphocyte redistribution or relative lymphopenia. The combined reduction in albumin and lymphocyte count therefore reflects an unfavorable systemic inflammatory milieu. In our study, PNI values decreased further during relapse episodes, supporting its dynamic relationship with inflammatory activity. These findings are consistent with previous reports published in Sarcoidosis, Vasculitis and Diffuse Lung Diseases, which have highlighted the clinical utility of composite inflammatory indices in the evaluation and differentiation of sarcoidosis (9).
From a clinical perspective, PNI offers several advantages. It is inexpensive, widely available, reproducible, and calculated from routine laboratory parameters. In contrast to more specialized biomarkers, it does not require advanced assays or additional costs. Given its high sensitivity and specificity in our analysis, baseline PNI may help identify patients at increased risk of relapse who could benefit from closer monitoring or more individualized follow-up strategies.
This study has several limitations. First, its retrospective single-center design may limit generalizability. Second, multivariable regression analysis was not performed to determine whether PNI is an independent predictor beyond established risk factors such as radiological stage and systemic involvement. Third, external validation in an independent cohort is lacking. Nevertheless, the relatively large sample size and long follow-up period strengthen the reliability of our findings.
Future prospective multicenter studies are needed to validate these results and to evaluate whether integrating PNI into clinical decision algorithms improves patient management. Comparative analyses with other inflammatory indices and incorporation into multivariable predictive models would further clarify its incremental value.
In conclusion, baseline PNI is strongly associated with relapse in patients with sarcoidosis and demonstrates excellent predictive performance. As a simple and accessible biomarker reflecting both systemic inflammation and immune competence, PNI may represent a promising tool for risk stratification and personalized follow-up in clinical practice.
Limitations
This study has several limitations that should be acknowledged. First, its retrospective and single-center design may limit the generalizability of the findings. Although the cohort included a relatively large number of patients with long-term follow-up, selection bias cannot be entirely excluded.
Second, laboratory parameters were assessed at predefined clinical visits, and therefore dynamic fluctuations in inflammatory markers between visits may not have been fully captured. Serial measurements obtained at standardized intervals might provide a more precise evaluation of the temporal relationship between PNI and disease activity.
Third, the identified cutoff value for PNI (≤39.25) was derived from the present cohort and has not yet been externally validated. Therefore, this threshold should be interpreted cautiously until confirmed in independent, multicenter populations.
Finally, although PNI reflects both inflammatory and immunonutritional status, it remains a surrogate biomarker and does not directly measure the underlying immunopathological mechanisms driving sarcoidosis progression. Future prospective multicenter studies are warranted to validate these findings and further clarify the biological significance of PNI in sarcoidosis.
Conclusion
In conclusion, the present study demonstrates that baseline Prognostic Nutritional Index (PNI) is strongly associated with relapse in patients with sarcoidosis and exhibits excellent predictive performance. Lower PNI values were observed in patients who subsequently developed relapse, supporting the role of systemic inflammation and immunonutritional status in disease progression.
Given its simplicity, accessibility, and cost-effectiveness, PNI may serve as a practical biomarker for risk stratification in routine clinical practice. Incorporating PNI into follow-up strategies may help identify patients at higher risk of relapse and support more individualized monitoring approaches.
Further prospective, multicenter studies are warranted to validate these findings and to determine the potential integration of PNI into clinical decision-making algorithms for sarcoidosis management.
Acknowledgments:
The authors thank the medical records and administrative staff of Sultan II. Abdülhamid Han Training and Research Hospital for their assistance in accessing patient data.
Ethics Approval and Consent to Participate:
Ethical approval for this study was obtained from the Istanbul Medipol University Non-Interventional Clinical Research Ethics Committee (Approval Date: January 9, 2026; Decision Number: E-10840098-202.3.02-169). The study was conducted in accordance with the principles of the Declaration of Helsinki. As this was a retrospective study based on anonymized patient data, the requirement for informed consent was waived by the ethics committee.
Conflict of Interests:
Each author declares that he or she has no commercial associations (e.g. consultancies, stock ownership, equity interest, patent/licensing arrangement etc.) that might pose a conflict of interest in connection with the submitted article.
Authors’ Contributions:
GT and MD contributed to the conception and design of the study. GT, MD, ŞB, and MGC were involved in data collection and clinical evaluation. GT performed the statistical analysis. GT drafted the manuscript. All authors contributed to data interpretation, critically revised the manuscript for important intellectual content, and approved the final version of the manuscript.
Declaration on the Use of AI:
None.
Consent for Publication:
Not applicable.
Availability of Data and Materials:
The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request.
Funding:
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
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Data Availability Statement
The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request.