Search Results (74)

Background: Major morbidity and mortality remain important concerns after colorectal cancer (CRC) surgery. Cancer-related sarcopenia and heightened systemic inflammation may increase the risk of early postoperative major complications. Methods: In this retrospective single-center study, we analyzed 190 patients undergoing major CRC surgery. Skeletal muscle gauge (SMG) and the pan-immune-inflammation value (PIV) were assessed as preoperative risk markers, and 30-day major complications were evaluated. Results: Low SMG was strongly associated with major complications (OR 6.50, 95% CI 3.24–13.05; p < 0.001), and high PIV was also associated with increased risk (OR 3.51, 95% CI 1.77–6.99; p < 0.001). In multivariable analysis adjusting for age, surgical urgency, and procedure type, low SMG and emergency surgery remained independent predictors of 30-day major complications. The highest-risk phenotype (high PIV/low SMG; n = 23) had a major complication rate of 78.3% (18/23) (p < 0.001). A clinical model including age, urgency, and procedure type yielded an AUC of 0.739 (95% CI 0.661–0.816). Adding low SMG improved discrimination (AUC 0.784, 95% CI 0.711–0.857), with only a small additional increase after adding high PIV (AUC 0.791, 95% CI 0.717–0.864). Conclusions: Preoperative low SMG was independently associated with 30-day major complications after CRC surgery, while PIV provided complementary risk-stratification value. The combined high-PIV/low-SMG phenotype identified patients with particularly high postoperative risk. Full article

Background/Objectives: This study aimed to compare hematological and inflammatory markers among patients with dry and wet age-related macular degeneration (AMD) and healthy controls, and to evaluate the influence of geographic atrophy (GA) in dry AMD and treatment response (TR) in wet AMD on these markers. Methods: The study included patients with dry AMD (n = 54), wet AMD (n = 53), and age- and sex-matched controls (n = 55). Hematological parameters, serum albumin, and systemic inflammatory indices, including neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), systemic immune–inflammation index (SII), systemic inflammation response index (SIRI), pan-immune–inflammation value (PIV), and hemoglobin, albumin, lymphocyte, and platelet index (HALP), were compared among the groups. Results: Age and sex distributions did not differ significantly between groups. Compared to controls, the wet AMD group had significantly higher neutrophil counts (p = 0.013), red cell distribution width (RDW) (p = 0.033), and inflammatory indices, including NLR, PLR, SII, SIRI, and PIV (all p < 0.01). HALP levels were significantly lower in wet AMD (p < 0.001). Dry AMD patients also had higher PLR (p = 0.045) and RDW (p = 0.005) than controls. When comparing wet and dry AMD groups directly, SIRI (p = 0.041) and PIV (p = 0.029) were significantly elevated in wet AMD, indicating stronger systemic inflammatory burden. In the dry AMD subgroup, patients with GA had significantly lower hemoglobin (p = 0.002) and erythrocyte counts (p = 0.039) than those without GA. No significant differences were observed between TR-positive and TR-negative wet AMD patients. Conclusions: Patients with wet AMD exhibit a more pronounced systemic inflammatory profile than both dry AMD patients and healthy controls. These findings support the hypothesis that systemic inflammation may contribute to AMD pathogenesis. Geographic atrophy in dry AMD may also be associated with additional hematologic alterations, whereas treatment response in wet AMD is not reflected in systemic markers. Full article

Background: Post-stroke dysphagia is a frequent complication associated with aspiration, malnutrition, and prolonged dependence on enteral feeding. Systemic inflammation and impaired nutritional status may adversely affect neuromuscular recovery; however, their relative and combined associations with swallowing recovery and transition from enteral to oral feeding remain insufficiently characterized. Objective: This study aimed to examine the independent associations of inflammatory and nutritional indices with swallowing function recovery and to evaluate their relationship with enteral-to-oral feeding transition in patients with post-stroke dysphagia. Methods: In this retrospective observational study, patients with dysphagia following ischemic stroke were evaluated before (T0) and after (T1) routine dysphagia rehabilitation. Inflammatory indices including the 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), as well as the prognostic nutritional index (PNI), were calculated at both time points. Changes in indices (Δ = T1 − T0) were analyzed in relation to changes in swallowing function assessed by the Functional Oral Intake Scale (FOIS) and the Penetration–Aspiration Scale (PAS). Results: Changes in PNI were independently associated with greater improvement in functional oral intake (ΔFOIS) and reductions in aspiration severity for both liquid and soft consistencies (ΔPAS; all p < 0.01). In contrast, changes in inflammatory indices (ΔSIRI, ΔSII, ΔPLR, and ΔPIV) were consistently associated with less favorable swallowing outcomes. In multivariable logistic regression analysis, baseline stroke severity (NIHSS) was the only independent determinant of transition from enteral to oral feeding (OR = 0.72, p = 0.002). The model demonstrated good discrimination (AUC = 0.81). Conclusions: Changes in nutritional status, as reflected by ΔPNI over time, were the biomarker most consistently associated with functional swallowing recovery and reduced aspiration severity in patients with post-stroke dysphagia. While inflammatory burden was associated with less favorable swallowing physiology, transition from enteral to oral feeding appeared to be primarily driven by neurological severity rather than inflammatory or nutritional indices alone. These findings may support the clinical value of monitoring nutritional reserve alongside inflammatory burden during dysphagia rehabilitation. Full article

Background/Objectives: We aim to investigate whether tracking pan-immune–inflammation value (PIV) dynamics during radiotherapy (RT) can inform real-time prognosis in patients with head and neck cancer (HNC). Methods: We retrospectively reviewed the medical records of patients with HNC who received RT at our institution between 2005 and 2013. Temporal changes in the PIV throughout the RT were evaluated using the Friedman test and Wilcoxon signed-rank test. The PIV dynamics were quantified using PIV ratios, defined as the PIV at three distinct time points (PIV-2, PIV-4, and PIV-6) during treatment divided by the pretreatment PIV (PIV-0). Overall survival (OS) and progression-free survival (PFS) served as the primary and secondary endpoints analyzed. Results: A total of 676 patients with HNC were enrolled, with a median follow-up of 8.1 years. The PIV demonstrated a continuously ascending trend over time, with the most dramatic increase occurring six weeks after the start of RT. Compared with patients with a low PIV ratio at six weeks (PIV-6/PIV-0), those with a high PIV ratio showed more favorable survival outcomes (five-year OS: 58.9% versus 70.8%, p = 0.002; five-year PFS: 62.0% versus 71.1%, p = 0.013). The subgroup analyses yielded consistent results. Notably, the real-time risks of death and recurrence changed in parallel with the PIV dynamics. Multivariate analysis confirmed PIV-6/PIV-0 as an independent prognostic factor for both OS and PFS. Conclusions: Monitoring longitudinal PIV dynamics may assist in forecasting the OS and PFS in patients with HNC being treated with RT, thus enabling individualized, risk-adapted treatment management. Full article

Objective: To evaluate the diagnostic and prognostic utility of the hemoglobin–albumin–lymphocyte–platelet (HALP) score and several systemic inflammatory indices derived from routine blood parameters—including the systemic immune-inflammation index (SII), platelet-to-lymphocyte ratio (PLR), pan-immune inflammation value (PIV), and systemic inflammatory response index (SIRI)—for pathogen differentiation and clinical assessment in culture-proven late-onset neonatal sepsis (LOS). Methods: A retrospective analysis was conducted on a cohort of 150 neonates with culture-proven LOS. Systemic inflammatory indices were calculated at baseline (first week of life) and at the time of septic insult. The discriminative power of these indices was assessed via ROC curve analysis, with optimal cut-off points determined by the Youden Index. Risk stratification was performed using Odds Ratio (OR) modeling with 95% Confidence Intervals (CIs) to evaluate the predictive strength of each marker according to its respective threshold. Results: Diagnosis-phase assessments identified SII as the premier discriminator for microbiological etiology (AUC = 0.869; OR = 44.57), outperforming PLR and PIV. Although HALP demonstrated moderate efficacy in distinguishing pathogens, it lacked prognostic value regarding mortality. Conversely, SIRI displayed limited clinical utility, yielding the lowest predictive performance in our cohort. Conclusions: In neonatal sepsis, the HALP score provided additional clinical information when compared with several hematological inflammatory indices. Although HALP was not associated with mortality, prospective multicenter studies are needed to clarify the role of these cost-effective markers in pathogen differentiation and clinical assessment of LOS. Full article

Background/Objectives: Contrast-associated acute kidney injury (CA-AKI) remains an important cause of morbidity and mortality in patients undergoing procedures that require intravascular contrast administration. Therefore, the early identification of high-risk individuals is paramount, above all for ST-segment elevation myocardial infarction (STEMI) patients in need of urgent percutaneous coronary intervention (PCI). Methods: This retrospective study evaluated the prognostic value of the Pan-Immune-Inflammation Value (PIV), a composite inflammatory index, in predicting CA-AKI among patients presenting with STEMI who received urgent PCI within a 12 h window from the onset of symptoms. Results: This study recruited 2325 patient. CA-AKI was defined as a >25% or ≥0.5 mg/dL increase in serum creatinine within 48–72 h after the procedure. Patients were categorized into CA-AKI (+) and CA-AKI (−) groups. PIV levels were significantly higher in patients who developed CA-AKI (502.5 ± 324.5 vs. 264.7 ± 165.8; p < 0.001). ROC analysis identified a PIV cutoff value of >320, yielding an AUC of 0.753 (95% CI: 0.740–0.787; p < 0.001), with 67% sensitivity and 66.9% specificity. Multivariate logistic regression confirmed that PIV > 320 independently predicted CA-AKI (OR 2.118; 95% CI: 1.329–3.790; p < 0.001). In multivariable analysis, age, Killip class, contrast volume, and PIV > 320 were identified as independent predictors of CA-AKI. Conclusions: Elevated admission PIV serves as an independent and practical biomarker for predicting CA-AKI in STEMI patients undergoing PCI. Full article

Cytokines are central regulators of inflammation and immune responses within the tumor microenvironment and have been implicated in cancer progression and prognosis. However, the prognostic value of coordinated cytokine-related transcriptional programs across cancer types has not been systematically explored. Pan-cancer transcriptomic and clinical data were analyzed to construct a cytokine-related prognostic signature using least absolute shrinkage and selection operator (LASSO) Cox regression. Patients were stratified into high-risk and low-risk groups based on the derived risk score. Prognostic performance was evaluated in training and test cohorts, and biological relevance was assessed through survival analyses and pathway-level investigations. A 16-gene cytokine-related signature was established that consistently stratified patients into distinct prognostic groups across multiple cancer types. High cytokine-related risk scores were significantly associated with unfavorable survival outcomes and were linked to enhanced cell cycle activity, epithelial-mesenchymal transition, and extracellular matrix remodeling. Integration of the risk score with clinical variables improved individualized survival prediction. Immunohistochemical analyses further confirmed increased protein expression of representative risk-associated genes, including pannexin 1 (PANX1) and FERM domain containing 8 (FRMD8), in multiple tumor tissues compared with corresponding normal tissues. The cytokine-related prognostic signature captures key inflammatory and immune-related programs underlying tumor aggressiveness and provides a robust tool for pan-cancer risk stratification with potential clinical utility. Full article

Background/Objectives: This study aimed to investigate the prognostic significance of the triglyceride–glucose index (TGI), triglyceride-to-high-density lipoprotein cholesterol (TG/HDL-C) ratio, and inflammatory biomarkers in predicting short-term mortality among intensive care unit (ICU) patients with sepsis. Additionally, this study evaluated whether combining these indices with conventional clinical scores improves prognostic accuracy. Methods: This retrospective cohort study included 600 adult ICU patients diagnosed with sepsis according to Sepsis-3 criteria between January 2020 and April 2025. Clinical, biochemical, and hematological data were collected within the first 24 h of ICU admission. Metabolic indices (TGI, TG/HDL-C) and inflammatory markers (neutrophil-to-lymphocyte ratio [NLR], systemic immune-inflammation index [SII], and pan-immune-inflammation value [PIV]) were analyzed. The primary outcome was 28-day mortality. Receiver operating characteristic (ROC) analyses, Kaplan–Meier survival curves, and a multivariable logistic regression model were applied to determine prognostic performance. Results: Non-survivors exhibited significantly higher levels of TGI, TG/HDL-C, NLR, SII, and PIV compared to survivors (all p < 0.001). In ROC analysis, TGI (AUC = 0.75, 95% CI: 0.71–0.79), TG/HDL-C (AUC = 0.72, 95% CI: 0.68–0.76), and PIV (AUC = 0.78, 95% CI: 0.74–0.82) demonstrated good discriminative power for predicting 28-day mortality. Multivariate logistic regression identified TGI > 8.95 (OR = 1.44, 95% CI: 1.19–1.74, p < 0.001), TG/HDL-C > 3.95 (OR = 1.31, 95% CI: 1.08–1.59, p = 0.005), and PIV > 260 (OR = 1.49, 95% CI: 1.22–1.82, p < 0.001) as independent predictors of mortality. Integrating TGI and PIV with the SOFA score improved prognostic performance (ΔAUC = +0.04). Conclusions: Both TGI and TG/HDL-C are independent predictors of short-term mortality in septic ICU patients, reflecting the contribution of metabolic dysregulation to disease severity. The PIV demonstrated comparable predictive ability to conventional severity scores. Combining metabolic and inflammatory biomarkers with established clinical indices may enhance early risk stratification and guide personalized management strategies in sepsis. Full article

Background/Objectives: Calprotectin (CLP), a calcium-binding protein complex released predominantly from neutrophils and monocytes, plays a key role in the inflammatory response. Increased levels of CLP have been reported in various inflammatory and malignant conditions. This study aimed to evaluate serum CLP concentrations and their associations with hematological and biochemical parameters in patients with lung cancer. Methods: This prospective observational study included newly diagnosed lung cancer patients and a healthy control group. Demographic data, routine laboratory parameters, CLP levels, and inflammatory indices including 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) were recorded. Comparisons were made between groups and across tumor molecular profile, cancer stages, and metastasis status. Correlation and ROC analyses were performed. Results: Serum CLP levels were significantly higher in the lung cancer group compared with healthy controls (p < 0.001). Among molecular subgroups, patients with positive molecular testing had significantly elevated CLP levels compared with negative and untested groups (p = 0.025). CLP did not differ significantly across cancer stages or metastasis status (p > 0.05). CLP showed a positive correlation with the SIRI (r = 0.323; p = 0.004) and PIV (r = 0.395; p < 0.001). ROC analysis revealed that CLP demonstrated good diagnostic performance for lung cancer, with an AUC of 0.930 (95% CI: 0.849–0.976), sensitivity of 79.5%, and specificity of 92.3%. Among inflammatory indices, PIV (AUC = 0.863) and SIRI (AUC = 0.810) also showed high diagnostic accuracy. Conclusions: CLP levels are significantly elevated in lung cancer and show strong discriminative ability, outperforming commonly used inflammatory indices. Although CLP is not specific to lung cancer, it may serve as a supportive, noninvasive biomarker reflecting inflammatory burden when interpreted alongside clinical evaluation, imaging findings, and other laboratory parameters. Full article

Background: This study aims to compare the performance of machine learning (ML) models developed to predict long-term mortality risk in patients with ST-segment elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention (pPCI) and to investigate the prognostic value of novel inflammatory–metabolic indices. Methods: In this retrospective study, 329 consecutive STEMI patients who underwent pPCI (292 survivors, 37 deaths) were included. Five ML algorithms—Logistic Regression (LR), Random Forest (RF), Extreme Gradient Boosting (XGBoost), Support Vector Machines (SVM), and Artificial Neural Networks (ANN)—were developed for mortality prediction. Model performance was evaluated using accuracy, sensitivity, specificity, and the area under the receiver operating characteristic (ROC) curve (AUC). SHAP (Shapley Additive exPlanations) analysis was used to interpret model decision mechanisms. Results: The mortality group had significantly higher door-to-balloon time (DTBT), Systemic Inflammatory Response Index (SIRI), pan-immune-inflammation value (PIV), whereas body mass index (BMI), Prognostic Nutritional Index (PNI), and Advanced Lung Cancer Inflammation Index (ALI) values were significantly lower (p < 0.001). Among the ML models, the XGBoost algorithm achieved the best performance, with 98.99% accuracy, a ROC-AUC of 0.999, and 100% sensitivity, correctly identifying all mortality cases. SHAP analysis identified DTBT, albumin level, and ALI score as the strongest predictors of mortality, in that order. Conclusions: The XGBoost algorithm provides high accuracy and reliability for predicting long-term mortality in STEMI patients. Beyond DTBT, integrating novel indices—especially ALI and TyG—into ML models may serve as a powerful clinical tool for early identification of high-risk patients and improved risk stratification. Full article

Objective: To investigate the association between inflammatory indices derived from complete blood count, including the systemic immune-inflammation index (SII), systemic inflammatory response index (SIRI), and pan-immune inflammation value (PIV), in predicting nausea and vomiting in pregnancy (NVP). Methods: Women diagnosed and treated for NVP at a tertiary care hospital between 2016 and 2021 were retrospectively analyzed. A total of 278 eligible patients with NVP and 278 gestational age-matched healthy pregnant women were included. Patients with NVP were categorized as having mild (n = 58), moderate (n = 140), or severe NVP (n = 80). Patients with moderate and severe NVP, who almost always required hospitalization, were grouped together and assigned to the inpatient treatment group. The groups were then compared. Results: SII and PIV were significantly higher in the NVP group than in the control group (p < 0.001 for both). In addition to SIRI, SII and PIV were also significantly higher in both the moderate NVP and HG groups compared to the mild NVP group (p = 0.017, 0.040, and 0.038, respectively, and p = 0.003, 0.009, and 0.006, respectively). SII, with a cut-off value of >966 × 10³/μL (63.67% sensitivity, 68.35% specificity), showed the best discriminatory performance for predicting NVP (p < 0.001), but there was no significant difference among SII, SIRI, and PIV in predicting the need for hospitalization. Conclusions: Our results show that there may be an association between high SII and PIV and an increased risk of developing NVP. In the future, after sufficient research, among these complete blood count-based inflammatory indices, SII may become an important component of regression models used as a screening tool to predict NVP, particularly in cases requiring inpatient care. Full article

Introduction: Acute coronary syndrome (ACS), encompassing unstable angina, NSTEMI, and STEMI, is a major cause of morbidity and mortality worldwide. Novel inflammatory and nutritional biomarkers may provide incremental value for risk stratification beyond conventional predictors. This work sought to determine whether the Pan-Immune-Inflammatory Value (PIV) and the Hemoglobin-Albumin-Lymphocyte-Platelet (HALP) score could serve as independent prognostic indicators in individuals presenting with acute coronary syndrome. Methods: A retrospective multicenter study included ACS patients hospitalized between January 2020 and May 2024. Demographics, clinical data, and laboratory results were collected. PIV was calculated as follows: neutrophils × platelets × monocytes/lymphocytes. HALP score was calculated as follows: hemoglobin × albumin × lymphocytes/platelets. Correlations with clinical parameters and mortality prediction were analyzed. Results: A total of 1134 patients (mean age 62 ± 12 years) were included. PIV showed positive correlations with WBC (Rho = 0.574), troponin (Rho = 0.381), and CRP (Rho = 0.295), and negative correlations with HDL (Rho = –0.101) and ejection fraction (Rho = –0.316) (all p < 0.01). PIV independently predicted mortality with a cut-off ≥1074.2 (AUC = 0.619, sensitivity 45%, specificity 79.9%). HALP score negatively correlated with age, troponin, CRP, and ICU stay, and predicted mortality with a cut-off ≤3.58 (AUC = 0.722, sensitivity 53.8%, specificity 82%). Comparative ROC analysis showed that HALP demonstrated superior discriminative ability for mortality prediction compared with PIV. Conclusions: PIV and HALP score are independent prognostic markers in ACS, reflecting inflammatory burden and nutritional status. Their integration into clinical workflows may enhance risk stratification and support individualized management strategies. Given their simplicity and universal availability, PIV and HALP may serve as practical adjunctive tools to established risk scores, enabling early identification of high-risk ACS patients at the time of admission. 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