Search Results (289)

Background/Objectives: Malignant melanoma remains a highly aggressive malignancy with substantial mortality despite advances in systemic therapy. Identifying simple and reproducible prognostic biomarkers is essential for improving risk stratification. Inflammation- and nutrition-based indices—including the Systemic Immune–Inflammation Index (SII), Systemic Inflammatory Response Index (SIRI), dynamic SIRI, and the Controlling Nutritional Status (CONUT) score—have shown prognostic value in various cancers. This study assessed the prognostic significance of these indices in patients with locally advanced or metastatic melanoma using real-world data. Methods: A retrospective cohort of 138 patients treated between 2010 and 2023 was analyzed. Baseline demographic, clinical, nutritional, and inflammatory parameters were collected. Optimal cut-off values for SII, SIRI, 6-month SIRI, and dynamic SIRI were determined using receiver operating characteristic analysis. Overall survival (OS) and progression-free survival (PFS) were evaluated using the Kaplan–Meier method, and independent predictors were identified with multivariate Cox regression. Results: Elevated baseline SII and SIRI were significantly associated with shorter overall survival. Both 6-month SIRI and dynamic SIRI demonstrated strong prognostic value, emphasizing the importance of longitudinal inflammatory changes. In multivariate analysis, response to first-line therapy emerged as the only independent predictor of disease progression. Patients with a CONUT score ≥ 3 showed significantly shorter OS and PFS in univariate analyses, underscoring the prognostic relevance of nutritional status. Conclusions: SII, SIRI, 6-month SIRI, dynamic SIRI, and CONUT are practical, accessible, and reproducible biomarkers with meaningful prognostic value in advanced melanoma. Incorporating these indices into routine clinical assessment may enhance risk stratification and support more personalized treatment decision-making. Full article

Background: Inflammatory activity in rheumatoid arthritis can be determined by normal blood count ratios such as Neutrophil Lymphocyte Ratio (NLR), Platelet Lymphocyte Ratio (PLR), Systemic Immune Inflammation Index (SII), and C-reactive Protein (CRP). Objective: The aim of this research is to determine how these markers change after therapy and whether their pre- and post-treatment differences follow patterns that allow for simple parametric analyses. Methods: A prospective cohort of 52 RA patients (30 females and 22 males) was examined. The patients’ blood samples were tested at baseline and at the end of their 6-month Infliximab treatment. Hematologic markers such as NLR, PLR, and SII were calculated from the complete blood count (CBC), and CRP levels were measured. The statistical methods of Shapiro–Wilk (SW), Kolmogorov–Smirnov (KS), and Anderson–Darling (AD) were used, and later, paired t-tests were used to generate statistics where necessary. Results: Post-treatment measurements were consistently lower for all four biomarkers. QQ-plots and formal tests revealed that the differences between findings were essentially normal, allowing for paired t-tests. The mean decreases were as follows: NLR −1.10 (95% CI −1.48 to −0.71), PLR −43.0 (−55.4 to −30.7), SII −299 (−388 to −211), and CRP −11.36 (−13.18 to −9.54), all p < 0.001. CRP showed the greatest drop, with significant decreases in PLR and SII and a moderate decline in NLR, indicating therapy-related attenuation of systemic inflammation. Conclusions: The study shows that six months of infliximab therapy results in a consistent post-treatment decrease in all four biomarkers: NLR, PLR, SII, and CRP. Because the pre-post differences were roughly normal, CRP revealed the greatest decrease, with significant decreases in PLR and SII and a moderate decrease in NLR, consistent with systemic inflammation reduction. When combined, the CBC-derived indices track with CRP and can serve as practical, low-cost markers for monitoring therapy response in RA, despite the single-arm design. Full article

Background: Mucosal malignant melanoma (MMM) is a rare and aggressive malignancy with a dismal prognosis. While the Systemic Immune-Inflammation Index (SII) has emerged as a prognostic marker in various solid tumors, its specific value in MMM remains undefined. This study investigated the association between pretreatment SII and overall survival (OS) in patients with MMM. Methods: We retrospectively analyzed 106 adults with histologically confirmed MMM treated at six oncology centers in Turkey between 2005 and 2025. The baseline SII was calculated as platelet × neutrophil/lymphocyte counts obtained before definitive treatment. A receiver operating characteristic (ROC) analysis identified an optimal SII cutoff of 776 for overall survival (OS), defining low (<776) and high (≥776) SII groups. Results: Gastrointestinal and head and neck mucosa were the most frequent primary sites, and one-third of patients presented with metastatic disease. The median OS for the entire cohort was 23.3 months. Patients with a high versus low SII had a shorter OS (16.2 vs. 35.2 months; HR 2.71, 95% CI 1.67–4.40; p < 0.001). In multivariable analysis, a high SII (HR 1.88, 95% CI 1.12–3.14; p = 0.016), gastrointestinal primary site (HR 1.99, 95% CI 1.23–3.23; p = 0.005), and metastatic disease at diagnosis (HR 4.01, 95% CI 2.32–6.94; p < 0.001) independently predicted a worse OS. Conclusions: The SII is a novel, independent prognostic biomarker in MMM. Elevated pretreatment SII correlates with aggressive clinicopathologic features and inferior survival. As a readily accessible and cost-effective marker, SII may facilitate improved risk stratification in routine clinical practice for MMM patients. Full article

Background/Objectives: This study aimed to evaluate the prognostic value of ¹⁸F-FDG PET/CT-based secondary lymphoid organ metabolic ratios—spleen/liver (SLR), bone marrow/liver (BLR), and ileocecal region/liver (ILR)—and hematological inflammation markers (neutrophil/lymphocyte ratio [NLR] and systemic immune-inflammation index [SII]) obtained before nivolumab treatment in relation to survival in patients with advanced non-small cell lung cancer (NSCLC). Methods: This retrospective single-center study included 79 advanced NSCLC patients who were treated with nivolumab monotherapy at Marmara University Faculty of Medicine Hospital between 2022 and 2024. Pretreatment SLR, BLR, and ILR ratios were calculated from ¹⁸F-FDG PET/CT examinations; NLR and SII values were obtained from hematological data. Survival outcomes were analyzed using the Kaplan–Meier method, and prognostic factors were assessed using Cox proportional hazards regression analysis. In a subset of patients, an exploratory longitudinal analysis was performed using early follow-up PET/CT to assess follow-up-to-baseline changes in immune-organ metabolic ratios in relation to overall survival. Results: High NLR and SII levels were significantly associated with shorter progression-free survival and overall survival. In contrast, no significant associations were observed between PET/CT-derived metabolic ratios (SLR, BLR, and ILR) and survival. Multivariate analysis identified the presence of liver metastases and a high NLR as independent adverse prognostic factors for overall survival. Conclusions: In this homogeneous real-world cohort treated exclusively with single-agent nivolumab, PET/CT-derived secondary lymphoid organ metabolic ratios showed limited prognostic value at baseline and during early on-treatment assessment. In contrast, hematological inflammation markers, especially high NLR levels, are strong prognostic indicators of survival and may complement established clinical factors in risk stratification. Full article

Background: The aim of this study was to evaluate the diagnostic and prognostic performance of albumin-based inflammatory–nutritional indices in hyperemesis gravidarum (HG) and to determine their associations with disease severity and risk of re-hospitalization. Methods: This retrospective case–control study included 246 women with HG and 246 gestational-age-matched healthy pregnant controls at 6–16 weeks of gestation. Disease severity was classified as mild, moderate, or severe using the Pregnancy-Unique Quantification of Emesis (24 h scale) (PUQE-24) score. A comprehensive panel of albumin-based inflammatory indices—including C-reactive protein-to-albumin ratio (CAR), fibrinogen-to-albumin ratio (FAR), neutrophil-to-albumin ratio (NAR), leukocyte-to-albumin ratio (LAR), neutrophil percentage-to-albumin ratio (NPAR), monocyte-to-albumin ratio (MAR), hemoglobin–albumin–lymphocyte–platelet (HALP) score, modified HALP (m-HALP) score, prognostic nutritional index (PNI) score, systemic immune-inflammation index-to-albumin (SII/Alb), and systemic inflammatory response index-to-albumin (SIRI/Alb)—was calculated from routine complete blood count and serum biochemistry results obtained at diagnosis. Receiver operating characteristic analysis, along with univariate and multivariate logistic regression models, was performed to evaluate diagnostic performance and identify predictors of severe HG and re-hospitalization. Results: Albumin-based indices exhibited severity-associated alterations, with an overall trend toward worsening immuno-nutritional status across increasing HG severity. Among these, m-HALP score demonstrated the strongest inverse correlations with PUQE-24 score, ketonuria grade, length of hospital stay, and re-hospitalization risk (r = −0.74 to −0.52; all p < 0.001) and achieved the highest discriminative accuracy for both severe HG (AUC 0.864, 95% CI 0.836–0.892, p < 0.001) and re-hospitalization (AUC 0.722, 95% CI 0.675–0.766, p < 0.001). In multivariable analysis, higher HALP, m-HALP, and PNI were independently associated with a lower likelihood of severe HG. For re-hospitalization, higher m-HALP and HALP were independently associated with a lower risk, whereas higher NPAR, higher ketonuria grade, and higher PUQE-24 score were independently associated with an increased risk of re-hospitalization. Conclusions: Albumin-based indices, particularly m-HALP, demonstrated robust diagnostic and prognostic performance in HG compared with conventional biomarkers. These readily available, cost-neutral composite biomarkers enable objective severity stratification and accurate identification of patients at elevated risk of recurrent hospitalization, offering immediate potential to guide personalized, evidence-based clinical management. Full article

Background: Systemic inflammation plays a central role in the pathogenesis and progression of type 2 diabetes mellitus (T2DM). Hematologic inflammatory indices-such as the Systemic Immune-Inflammation Index (SII), Neutrophil-to-Lymphocyte Ratio (NLR), Platelet-to-Lymphocyte Ratio (PLR), and Monocyte-to-Lymphocyte Ratio (MLR)-have emerged as accessible markers of chronic inflammation, yet longitudinal comparisons across oral antidiabetic therapies remain limited. This study uniquely integrates longitudinal correlation and network analyses in a large real-world T2DM cohort, allowing assessment of the temporal stability and class-specific inflammatory patterns across four oral antidiabetic therapies. Methods: This retrospective, longitudinal study analyzed 13,425 patients with T2DM treated with Biguanidines, Dipeptidyl Peptidase-4 (DPP-4) inhibitors, Sodium–Glucose Cotransporter-2 (SGLT-2) inhibitors or Thiazolidinediones (TZDs) between 2020 and 2024. Data were retrieved from the Probel^® Hospital Information System and included baseline, early (30–180 days), and late (180–360 days) follow-up laboratory results. Systemic inflammatory indices were computed from hematologic parameters, and correlations among inflammatory and biochemical markers were assessed using Spearman’s coefficients. Results: At baseline, all hematologic indices were strongly intercorrelated (SII–NLR r = 0.83, p < 0.001; SII–PLR r = 0.73, p < 0.001), with moderate associations to C-reactive protein (CRP; r ≈ 0.3–0.4) and weak or no correlations with Ferritin (r ≈ −0.1). These relationships remained stable throughout follow-up, confirming reproducibility of systemic inflammatory coupling. Longitudinally, SII and NLR showed modest early increases followed by significant declines at one year (p < 0.05), while PLR and MLR remained stable. Class-specific differences were observed: SGLT-2 inhibitors and TZDs demonstrated stronger and more integrated anti-inflammatory networks, whereas Biguanidines and DPP-4 inhibitors exhibited moderate coherence. Principal Component Analysis (PCA) explained 62.4% of total variance and revealed distinct clustering for TZD and SGLT-2 groups, reflecting class-specific inflammatory modulation. Conclusions: Systemic inflammatory indices (SII, NLR, PLR) provide reproducible and accessible measures of low-grade inflammation in T2DM. Despite overall inflammation reduction with treatment, drug-specific patterns emerged-SGLT-2 inhibitors and TZDs showed greater anti-inflammatory coherence, while Biguanidines and DPP-4 inhibitors maintained moderate effects. Full article

Background/Objectives: Rosacea increasingly appears to involve systemic immune and metabolic disturbances rather than isolated cutaneous inflammation. To evaluate inflammatory, platelet, and oxidative–metabolic biomarkers in rosacea and explore their interrelations. Methods: 90 patients with rosacea and 90 healthy controls were evaluated for hematologic inflammatory indices—neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), systemic immune–inflammation index (SII), pan-immune–inflammation value (PIV), mean platelet volume (MPV), and C-reactive protein (CRP)—along with oxidative–metabolic regulators including sirtuin 1 (SIRT1), sirtuin 3 (SIRT3), visfatin, and irisin. Logistic regression and receiver operating characteristic (ROC) analyses were used to identify independent predictors of rosacea, while inter-marker associations were evaluated using Spearman’s rank correlation. Results: Rosacea patients showed higher NLR, PLR, SII, PIV, MPV, CRP, and LDL cholesterol (p < 0.05) and lower SIRT1, SIRT3, visfatin, and irisin (p < 0.01). MPV independently predicted rosacea (OR = 7.24; AUC = 0.827), whereas SIRT1 inversely correlated with disease risk. SIRT1, SIRT3, and visfatin showed inverse correlations with HbA1c and waist-to-height ratio, while fasting glucose and HOMA-IR remained within normal ranges. Conclusions: Rosacea exhibits dual systemic activation, an inflammatory–platelet and an oxidative–metabolic axis bridging immune dysregulation, mitochondrial stress, and vascular dysfunction. Recognition of these pathways highlights the potential of redox-targeted and metabolic interventions beyond symptomatic treatment. Full article

Background/Objectives: Metachronous lung-limited oligometastatic disease represents a biologically heterogeneous state in which patient selection for pulmonary metastasectomy remains challenging. While systemic inflammation–nutrition indices have shown prognostic value across malignancies, their relevance in this strictly defined surgical setting is not well established. Methods: We conducted a retrospective single-center cohort study including 109 patients with isolated metachronous pulmonary recurrence who underwent curative intent R0 metastasectomy between September 2015 and April 2024. Preoperative systemic biomarkers, including neutrophil-to-lymphocyte ratio (NLR), systemic immune-inflammation index (SII), systemic inflammation response index (SIRI), pan-immune-inflammation value (PIV), and monocyte-to-albumin ratio (MAR), were evaluated using receiver operating characteristic (ROC) analysis and multivariable Cox models to determine their association with overall survival (OS) and progression-free survival (PFS). Clinicopathological variables, such as lymph node involvement and metastatic burden, were incorporated into the adjusted models. Results: The median age of the cohort was 61 years (range, 29–82 years), and the sex distribution was balanced (48.6% female and 51.4% male), with 62.4% of patients being younger than 65 years. Among the systemic indices evaluated, monocyte-weighted biomarkers demonstrated the strongest prognostic performance. The MAR showed the highest discriminative ability for mortality (AUC, 0.749; p < 0.001), followed by the SIRI (AUC, 0.682; p = 0.007). In multivariable analyses, MAR independently predicted OS (p = 0.043) and PFS (p = 0.023), while SIRI independently predicted PFS (p = 0.043). Lymph node involvement remained the dominant adverse prognostic factor for both outcomes (p < 0.001); however, monocyte-weighted indices provided additional prognostic value beyond conventional anatomic criteria. Conclusions: Preoperative SIRI and MAR capture host immune–metabolic states that are relevant to postoperative trajectories and may refine risk stratification in candidates for pulmonary metastasectomy. These readily obtainable markers warrant prospective validation within biologically integrated selection frameworks. Full article

Background/Objectives: Psoriasis is a chronic immune-mediated inflammatory disease associated with systemic inflammation and comorbidities such as cardiovascular disease and metabolic syndrome. Blood-derived inflammatory indices like neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), systemic inflammation response index (SIRI), and pan-immune-inflammation value (PIV) have been proposed as biomarkers of systemic inflammation and disease severity. This retrospective and prospective observational study aimed to evaluate the long-term effects of guselkumab, an IL-23 inhibitor, on these indices in moderate-to-severe psoriasis. Methods: We analyzed 208 patients with moderate-to-severe psoriasis treated with guselkumab, with hematologic evaluations available for 208 patients at baseline, 208 at week 52, 129 at week 104, and 94 at week 156. Systemic inflammatory indices were calculated from routine annual blood tests. Patients were stratified by obesity, cardiovascular comorbidities, treatment response, and prior biologic therapy. Longitudinal changes were assessed using Friedman tests with Wilcoxon post hoc comparisons, and correlations between PASI and inflammatory indices were evaluated using Spearman’s coefficients. Results: SIRI and PLR showed significant reductions at week 156 (p = 0.038 and p = 0.018, respectively), while MLR also decreased over time without reaching consistent significance. NLR and PIV showed minimal or inconsistent changes. Obese patients and those with cardiovascular disease had higher baseline SII and SIRI and less pronounced improvements. No significant differences were observed between super responders and others. Correlation between baseline PASI and most inflammatory markers was weak, except for a weak but significant correlation with PIV (ρ = 0.119, p = 0.049). Conclusions: Guselkumab treatment is associated with long-term reduction in systemic inflammatory indices, particularly SIRI. The weak correlation of these markers with skin severity highlights a dissociation between cutaneous and systemic inflammation. SIRI and SII may serve as useful biomarkers to monitor systemic inflammation and guide comprehensive management in psoriasis patients. Full article

Background/Objectives: Alopecia areata is an autoimmune disorder characterized by nonscarring hair loss and systemic immune dysregulation. Hematological indices such as neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), mean platelet volume (MPV), systemic immune-inflammation index (SII), erythrocyte sedimentation rate (ESR), and C-reactive protein (CRP) have been associated with inflammatory activity in dermatologic diseases. This study aimed to compare systemic inflammatory markers among patients with severe and mild alopecia areata and healthy controls, and to explore longitudinal changes in these markers in patients with severe disease who achieved clinical improvement following Janus kinase (JAK) inhibitor therapy. Methods: This retrospective cohort study included 129 participants: 43 patients with severe alopecia areata (SALT ≥ 50) treated with JAK inhibitors who achieved documented clinical improvement, 43 patients with mild disease (SALT ≤ 20), and 43 age- and sex-matched healthy controls. Hematological inflammatory markers, including red cell distribution width (RDW), MPV, MLR, NLR, PLR, SII, ESR, and CRP, were compared across groups. In patients with severe disease, longitudinal changes were assessed at baseline, three months after treatment initiation, and at the time of documented clinical improvement. Results: MLR, NLR, PLR, SII, and ESR levels were significantly higher in the severe group compared with mild cases and controls, while RDW, MPV, and CRP showed no significant differences. Among patients with severe alopecia areata who achieved clinical improvement following JAK inhibitor therapy, NLR and SII decreased significantly over time. MLR, PLR, and CRP also showed reductions during follow-up, while ESR and RDW remained unchanged. Conclusions: Systemic inflammatory markers are elevated in severe alopecia areata compared with mild disease and healthy controls. In patients who achieved clinical improvement with JAK inhibitor therapy, several inflammatory indices demonstrated longitudinal changes. These findings are exploratory and suggest an association between systemic inflammation, disease severity, and clinical improvement rather than definitive predictive biomarkers. Full article

This study evaluated whether a composite index combining the systemic immune–inflammation index (SII) and prognostic nutritional index (PNI), the coSII–PNI score, enhances prognostic prediction in head and neck cancer. We retrospectively evaluated 166 patients who underwent curative surgery between 2015 and 2023. Patients were stratified into three groups according to the coSII–PNI score (range, 0–2) derived from preoperative blood data. The optimal cutoff values for SII and PNI were 743 and 49, respectively. A significant correlation was observed between the SII and PNI (r = −0.386, p < 0.01). Patients with a high coSII–PNI score (low SII + high PNI) showed significantly better disease-free and overall survival than those with lower scores (both p < 0.01). The areas under the curve for predicting prognosis were 0.649 for SII, 0.717 for PNI, and 0.730 for the coSII–PNI score. These findings indicate that integrating systemic inflammation and nutritional status improves prognostic accuracy compared with either index alone. Therefore, the coSII–PNI score may serve as a simple, practical preoperative biomarker for risk stratification in patients with head and neck cancer. Full article

Background/Objectives: Immunotherapy has improved outcomes for selected patients with advanced non-small-cell lung cancer (NSCLC), yet the predictive value of individual biomarkers such as PD-L1 remains limited. Systemic inflammatory indices derived from routine blood tests may complement molecular and immunohistochemical features, offering a broader view of host–tumor immunobiology. Methods: We conducted a retrospective study of 298 patients with stage IIIB–IV NSCLC treated with immune checkpoint inhibitors (ICIs) at a tertiary oncology center between 2022 and 2024. Baseline neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), and systemic immune–inflammation index (SII) were collected alongside PD-L1 expression and molecular alterations (EGFR, KRAS, ALK, TP53). Patients were stratified into inflammatory–molecular clusters integrating these parameters. Associations with objective response rate (ORR), progression-free survival (PFS), and overall survival (OS) were evaluated using Kaplan–Meier and multivariate Cox analyses. Results: Four distinct inflammatory–molecular clusters demonstrated significantly different outcomes (p < 0.001). Patients with low NLR and high PD-L1 expression (Cluster A) showed the highest ORR (41%), longest median PFS (13.0 months), and OS (22.5 months). The EGFR/ALK-driven, inflammation-dominant cluster (Cluster C) exhibited poor response (ORR 7%) and shortest survival (PFS 4.3 months). High NLR (HR 2.12), PD-L1 < 1% (HR 1.91), and EGFR mutation (HR 2.36) independently predicted shorter PFS. A combined model incorporating NLR, PD-L1, and molecular status outperformed individual biomarkers (AUC 0.82). Conclusions: Integrating systemic inflammatory indices with PD-L1 expression and molecular alterations identifies clinically meaningful NSCLC subgroups with distinct immunotherapy outcomes. This multidimensional approach improves prediction of ICI response and may enhance real-world patient stratification, particularly in settings with limited access to extended molecular profiling. Full article

Background and Objectives: HER2-positive metastatic colorectal cancer (mCRC) represents a biologically distinct and clinically aggressive subtype associated with poor response to standard first-line chemotherapy. Reliable, low-cost prognostic biomarkers are urgently needed to identify early non-responders and guide treatment decisions. This real-world cohort study evaluated the prognostic value of carcinoembryonic antigen (CEA) kinetics and systemic inflammatory markers (SIMs) in HER2-positive mCRC treated with first-line chemotherapy. Materials and Methods: We retrospectively analyzed 98 patients with HER2-positive mCRC treated between 2015 and 2024. Serial CEA values were measured at baseline, after three cycles (week 6), and at radiologic progression. Early CEA change was categorized as ≥50% decline, 10–49% decline, or any increase. Baseline SIMs—including neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), and systemic immune-inflammation index (SII)—were calculated from pretreatment blood counts. Progression-free survival (PFS) was analyzed using Kaplan–Meier and Cox regression models. Results: Among patients with evaluable CEA kinetics (n = 60), early CEA increase occurred in 30% of patients (n = 18) and was strongly associated with inferior PFS (HR 2.84; 95% CI 1.81–4.44; p < 0.001). ROC analysis identified a ≥38% CEA reduction as the optimal predictor of radiologic response (AUC 0.79). High baseline NLR (≥3) and high SII (≥900) were also significantly associated with shorter PFS (median PFS: 5.2 vs. 9.1 months for NLR; 4.7 vs. 10.3 months for SII; both p < 0.01). In multivariate analysis, early CEA increase, high NLR, and high SII remained independent predictors of poor PFS. Conclusions: CEA dynamics and inflammation-based biomarkers provide robust, complementary prognostic information in HER2-positive mCRC. Early CEA increase is the strongest independent predictor of poor outcome, while high baseline NLR and SII further refine risk stratification. These inexpensive and widely accessible biomarkers may help identify early non-responders, optimize monitoring strategies, and support timely therapeutic adjustments in routine clinical practice. Full article

Cervical cancer, primarily caused by high-risk Human Papilloma Virus (HPV), remains a global health concern. Prognostic biomarkers reflecting systemic inflammation and immune response—the Systemic Immune-Inflammation Index (SII) and the Systemic Inflammation Response Index (SIRI)—have recently attracted interest for their potential predictive value in cervical cancer. We conducted a retrospective observational study including 344 patients who underwent loop electrosurgical excision of cervical intraepithelial neoplasia at Semmelweis University, Budapest, Hungary, between 2021 and 2024. Demographic, cytologic, histologic, and laboratory data were collected, and SII and SIRI were calculated. Statistical analyses, including Receiver Operating Characteristic (ROC) analyses, were performed. Higher SII and SIRI values were significantly associated with higher-grade lesions and invasive carcinoma. ROC analyses indicated good discriminatory performance, with negative predictive values of 96–100%, suggesting potential utility in ruling out malignant transformation. SII and SIRI are simple, cost-effective, and minimally invasive biomarkers that correlate with lesion severity in cervical disease. Their high negative predictive value supports a potential role as complementary rule-out tools in diagnostic evaluation. Further prospective studies are needed to validate these findings and to define clinically meaningful cut-off values for routine use. Full article

Background: Systemic inflammation is an essential factor in the formation of the tumor microenvironment and has an impact on patient response to immune checkpoint inhibitors. Although there is a growing interest in biomarkers of inflammation, there is a gap in understanding their predictive value for response to nivolumab in clinical practice. The objective of this research was to design and assess a multi-algorithmic machine learning (ML) model based on regular systemic inflammation measurements to forecast the response of treatment to nivolumab. Methods: An analysis of a retrospective real-world cohort of 177 nivolumab-treated patients was performed. Baseline inflammatory biomarkers, such as neutrophils, lymphocytes, platelets, CRP, LDH, albumin, and derived indices (NLR, PLR, SII), were derived. After preprocessing, 5 ML models (Logistic Regression, Random Forest, Gradient Boosting, Support Vector Machine, and Neural Network) were trained and tested on a 70/30 stratified split. Accuracy, AUC, precision, recall, F1-score, and Brier score were used to evaluate predictive performance. The interpretability of the model was analyzed based on feature-importance ranking and SHAP. Results: Gradient Boosting performed best in terms of discriminative (AUC = 0.816), whereas Support Vector Machine performed best on overall predictive profile (accuracy = 0.833; F1 = 0.909; recall = 1.00; and Brier Score = 0.134) performance. CRP and LDH became the most common predictors of all models, and then neutrophils and platelets. SHAP analysis has verified that high CRP and LDH were strong predictors that forced the prediction to non-response, whereas higher lymphocyte levels were weak predictors that increased the response probability prediction. Conclusions: Machine learning models based on common inflammatory systemic markers give useful predictive information about nivolumab response. Their discriminative ability is moderate, but the high performance of SVM and Gradient Boosting pays attention to the opportunities of inflammation-based ML tools in making personalized decisions regarding immunotherapy. A combination of clinical, radiomic, and molecular biomarkers in the future can increase predictive capabilities and clinical use. Full article