The predictive impact of hematological inflammatory markers in detecting prostate cancer in patients with PI-RADS 3 lesions on multiparametric magnetic resonance imaging.

BACKGROUND: The diagnostic accuracy of suspicious lesions that are classified as PI-RADS 3 in multiparametric prostate magnetic-resonance imaging (mpMRI) is controversial. This study aims to assess the predictive capacity of hematological inflammatory markers such as neutrophil-lymphocyte ratio (NLR), pan-immune-inflammation value (PIV), and systemic immune-response index (SIRI) in detecting prostate cancer in PI-RADS 3 lesions. METHODS: 276 patients who underwent mpMRI and subsequent prostate biopsy after PI-RADS 3 lesion detection were included in the study. According to the biopsy results, the patients were distributed to two groups as prostate cancer (PCa) and no cancer (non-PCa). Data concerning age, PSA, prostate volume, PSA density, PI-RADS 3 lesion size, prostate biopsy results, monocyte counts (109/L), lymphocyte counts (109/L), platelet counts (109/L), neutrophils count (109/L) were recorded from the complete blood count. From these data; PIV value is obtained by monocyte × neutrophil × platelet/lymphocyte, NLR by neutrophil/lymphocyte, and SIRI by monocyte number × NLR. RESULTS: Significant variations in neutrophil, lymphocyte, and monocyte levels between PCa and non-PCa patient groups were detected (p = 0.009, p = 0.001, p = 0.005 respectively, p < 0.05). NLR, PIV, and SIRI exhibited significant differences, with higher values in PCa patients (p = 0.004, p = 0.001, p < 0.001 respectively, p < 0.05). The area under curve of SIRI was 0.729, with a cut-off value of 1.20 and with a sensitivity 57.70%, and a specificity of 68.70%. CONCLUSION: SIRI outperformed NLR and PIV in detecting PCa in PI-RADS 3 lesions, showcasing its potential as a valuable biomarker. Implementation of this parameter to possible future nomograms has the potential to individualize and risk-stratify the patients in prostate biopsy decision.

Nomogram incorporating preoperative pan-immune-inflammation value and monocyte to high-density lipoprotein ratio for survival prediction in patients with colorectal cancer: a retrospective study.

OBJECTIVE: Using the preoperative pan-immune-inflammation value (PIV) and the monocyte to high-density lipoprotein ratio (MHR) to reflect inflammation, immunity, and cholesterol metabolism, we aim to develop and visualize a novel nomogram model for predicting the survival outcomes in patients with colorectal cancer (CRC). METHODS: A total of 172 patients with CRC who underwent radical resection were retrospectively analyzed. Survival analysis was conducted after patients were grouped according to the optimal cut-off values of PIV and MHR. Univariate and multivariate analyses were performed using Cox proportional hazards regression to screen the independent prognostic factors. Based on these factors, a nomogram was constructed and validated. RESULTS: The PIV was significantly associated with tumor location (P < 0.001), tumor maximum diameter (P = 0.008), and T stage (P = 0.019). The MHR was closely related to gender (P = 0.016), tumor maximum diameter (P = 0.002), and T stage (P = 0.038). Multivariate analysis results showed that PIV (Hazard Ratio (HR) = 2.476, 95% Confidence Interval (CI) = 1.410-4.348, P = 0.002), MHR (HR = 3.803, 95%CI = 1.609-8.989, P = 0.002), CEA (HR = 1.977, 95%CI = 1.121-3.485, P = 0.019), and TNM stage (HR = 1.759, 95%CI = 1.010-3.063, P = 0.046) were independent prognostic indicators for overall survival (OS). A nomogram incorporating these variables was developed, demonstrating robust predictive accuracy for OS. The area under the curve (AUC) values of the predictive model for 1-, 2-, and 3- year are 0.791,0.768,0.811, respectively. The calibration curves for the probability of survival at 1-, 2-, and 3- year presented a high degree of credibility. Furthermore, Decision curve analysis (DCA) for the probability of survival at 1-, 2-, and 3- year demonstrate the significant clinical utility in predicting survival outcomes. CONCLUSION: Preoperative PIV and MHR are independent risk factors for CRC prognosis. The novel developed nomogram demonstrates a robust predictive ability, offering substantial utility in facilitating the clinical decision-making process.

Utility of pan-immune-inflammation value as a predictor of the prognosis of childhood lupus.

BACKGROUND: Systemic lupus erythematosus (SLE) is a chronic inflammatory multisystemic disease. Monitoring disease activity thoughtout the disease course is important for effective management and assessment of disease outcome. OBJECTIVE: To assess whether the pan-immune inflammation value (PIIV) at diagnosis could predict organ involvement and disease activity in childhood SLE (cSLE) patients after 12 months of disease onst. METHODS: This is an observational retrospective multicenter study that comprised cSLE patients seen and followed at the participating centers between January 2010 and December 2022. All patients met the EULAR/ACR-19 criteria, were immunosuppressive drug-naïve at the time of SLE diagnosis and had a minimal follow-up period of 12 months. The data included clinical and laboratory findings and disease activity using the SLEDAI-2K. Receiver operating characteristic (ROC) curves were employed to determine the optimal cut-off value of PIIV and assess its predictive potential for disease activity, and organ involvement. RESULTS: A total of 125 patients (104 female) with a median age of 16.0 (IQR 5.6) years, a median age at disease onset of 10.9 (IQR 3.0) years, and a median disease duration of 4.8 (IQR 5.3) years were included. The most frequent involved organs at diagnosis were hematological (89.6%), musculoskeletal (68.8%), mucocutaneous (63.2%), and renal (58.4%). However, at a 12-month follow-up visit, the most frequent involved organs were renal (40.0%), hematological (39.2%), musculoskeletal (15.2%), and mucocutaneous (10.4%). The median PIIV at diagnosis was 139 (IQR 229.6), while the median SLEDAI was 12 (IQR 6.5) and 3.5 (IQR 7.0) at diagnosis and 12 months, respectively. An optimal PIIV cut-off of 250 was found to be a predicative for disease activity, with a sensitivity of 45% and a specificity of 86%. The study revealed that the PIIV successfully predicted four systems in our cohort of patients. CONCLUSION: Our work suggests the PIIV might be a reasonable predictor for organ involvement and disease activity in newly diagnosed cSLE, though further research, particularly larger studies, is required to validate these findings, especially regarding organ involvement.

The prognostic importance of the pan-immune-inflammation value in patients with septic shock.

INTRODUCTION: The purpose of this study was to determine whether the pan-immune-inflammation value (PIV), a novel biomarker combining neutrophil platelet, monocyte, and lymphocyte counts, some of the most widespread indicators of systemic inflammation, can predict mortality and prognosis in patients admitted to the intensive care unit (ICU) with septic shock. METHOD: This prospective study was performed with 82 patients aged 18 or over admitted to a tertiary ICU with diagnoses of septic shock. Patients with hematological disease and neutropenia were excluded. PIV was calculated with the formula [neutrophil count (103/µL) × platelet count (103/µL) × monocyte count (103/µL)]/lymphocyte count (103/µL). RESULTS: Median age, presence of hypertension, Acute Physiology and Chronic Health Evaluation II (APACHE II) levels, and neutrophil, monocyte, and platelet counts were lower in the low-PIV group than in the high-PIV group (p < 0.05). The highest area under ROC curve (AUC) was determined for Sequential Organ Failure Assessment (SOFA) (0.94 (0.89 - 0.99)), followed by Glasgow Coma Scale (GCS) (0.81 (0.70 - 0.91)), APACHE II (0.80 (0.69 - 0.91)) and lactate (0.77 (0.67 - 0.88)). Median survival was longer in the low-PIV group than in the high-PIV group (28 (15.25 - 40.76) vs 16 (9.46 - 22.55) days, respectively, p < 0.05). The univariate Cox proportional hazards (CPH) model showed that high PIV (HR = 2.13 (1.03-4.38)), low GCS (HR = 3.31 (1.34 - 8.15)), high SOFA (HR = 9.41 (2.86 - 30.95)), high APACHE II (HR = 3.08 (1.47 - 6.45)), high lactate (HR = 6.56 (2.73 - 15.75)), and high procalcitonin (PCT) (HR = 2.73 (1.11 - 6.69)) values were associated with a decreased survival time among ICU patients (p < 0.05). The multivariate CPH model showed the age-adjusted risk estimates for these six laboratory parameters. High lactate (HR = 7.97 (2.19 - 29.08)) and high SOFA scores (HR = 4.85 (1.22 - 19.32)) were significantly associated with shorter survival in ICU patients (p < 0.05). CONCLUSION: The findings of this research suggest that PIV could predict the longer survival in patients with septic shock. Despite PIV score's capability to show inflammation, it is not significantly associated with mortality in the multivariate analysis.

Can the pan-immune-inflammation value predict gram negative bloodstream infection-related 30-day mortality in solid organ transplant patients?

BACKGROUND: The recently used pan-immune-inflammation value (PIV) has not been adequately studied as a predictive marker for mortality in immunosuppressed patients. The aim of this study was to evaluate the usefulness of baseline PIV level as a predictor of 30-day mortality in solid organ transplant (SOT) recipients with gram negative bloodstream infections (GN-BSI). METHODS: This retrospective, cross-sectional study was conducted between January 1, 2019, and December 31, 2022, in 1104 SOT recipients. During the study period, 118 GN-BSI were recorded in 113 patients. Clinical, epidemiological, and laboratory data were collected, and mortality rates (30-day and all-cause) were recorded. RESULTS: The 113 recipients had a median age of 50 years [interquartile range (IQR) 37.5-61.5 years] with a male predominance (n = 72, 63.7%). The three most common microorganisms were as follows: 46 isolates (38.9%) of Escherichia coli, 41 (34.7%) of Klebsiella pneumoniae, and 12 (10.2%) of Acinetobacter baumannii. In 44.9% and 35.6% of the isolates, production of extended-spectrum beta-lactamases and carbapenem resistance were detected, respectively. The incidence of carbapenem-resistant GN-BSI was higher in liver recipients than in renal recipients (n = 27, 69.2% vs n = 13, 17.6%, p < 0.001). All-cause and 30-day mortality rates after GN-BSI were 26.5% (n = 30), and 16.8% (n = 19), respectively. In the group with GN-BSI-related 30-day mortality, the median PIV level was significantly lower (327.3, IQR 64.8-795.4 vs. 1049.6, IQR 338.6-2177.1; p = 0.002). The binary logistic regression analysis identified low PIV level [hazard ratio (HR) = 0.93, 95% confidence interval (CI) 0.86-0.99; p = 0.04], and increased age (HR = 1.05, 95% CI 1.01-1.09; p = 0.002) as factors associated with 30-day mortality. The receiver operating characteristic analysis revealed that PIV could determine the GN-BSI-related 30-day mortality with area under curve (AUC): 0.723, 95% CI 0.597-0.848, p = 0.0005. CONCLUSIONS: PIV is a simple and inexpensive biomarker that can be used to estimate mortality in immunosuppressed patients, but the results need to be interpreted carefully.

Prognostic significance of pan-immune-inflammation value in hepatocellular carcinoma treated by curative radiofrequency ablation: potential role for individualized adjuvant systemic treatment.

BACKGROUND: This study aimed to explore the prognostic role of pan-immune-inflammation value (PIV) and develop a new risk model to guide individualized adjuvant systemic treatment following radiofrequency ablation (RFA) for early-stage hepatocellular carcinoma (HCC). MATERIALS AND METHODS: Patients with early-stage HCC treated by RFA were randomly divided into training cohort A (n = 65) and testing cohort B (n = 68). Another 265 counterparts were enrolled into external validating cohort C. Various immune-inflammatory biomarkers (IIBs) were screened in cohort A. Prognostic role of PIV was evaluated and validated in cohort B and C, respectively. A nomogram risk model was built in cohort C and validated in pooled cohort D. Clinical benefits of adjuvant anti-angiogenesis therapy plus immune checkpoint inhibitor (AA-ICI) following RFA was assessed in low- and high-risk groups. RESULTS: The cutoff point of PIV was 120. High PIV was an independent predictor of unfavorable recurrence-free survival (RFS) and overall survival (OS). RFS and OS rates of patients with high PIV were significantly lower than those with low PIV both in cohort B (PRFS=0.016, POS=0.011) and C (PRFS<0.001, POS<0.001). The nomogram model based on PIV, tumor number and BCLC staging performed well in risk stratification in external validating cohort C. Adjuvant AA-ICI treatment showed an added benefit in OS (p = 0.011) for high-risk patients. CONCLUSIONS: PIV is a feasible independent prognostic factor for RFS and OS in early-stage HCC patients who received curative RFA. The proposed PIV-based nomogram risk model could help clinicians identify high-risk patients and tailor adjuvant systemic treatment and disease follow-up scheme.

Key findingsHigh pan-immune-inflammation value (PIV) is an independent indicator of unfavorable recurrence-free survival (RFS) and overall survival (OS) for early-stage hepatocellular carcinoma (HCC) patients who received curative radiofrequency ablation (RFA).Adjuvant anti-angiogenesis target therapy plus immune checkpoint inhibitor (AA-ICI) treatment showed added benefit in OS for the high-risk patients defined by a nomogram risk model based on PIV, tumor number and BCLC staging.What is known and what is new?Inflammation and impaired host immunity are associated with carcinogenesis and progression of HCC. Increasing evidences showed that immune-inflammatory biomarkers (IIBs) had prognostic roles in early-stage HCC patients who received RFA. However, prognostic potential of PIV has not been determined in this setting.Herein, high PIV was first reported to be an independent risk factor of poor RFS and OS in early-stage HCC patients treated by curative RFA and helped to discriminate patients between low- and high-risk groups. Adjuvant AA-ICI treatment following RFA was beneficial to OS of patients in the high-risk group.What is the implication, and what should change now?For early-stage HCC with high-risk factors (high PIV, multiple tumor foci and more advanced BCLC stage), intensive follow-up and adjuvant systemic therapy following curative RFA were warranted.

Predicting coronary artery severity in patients undergoing coronary computed tomographic angiography: Insights from pan-immune inflammation value and atherogenic index of plasma.

BACKGROUND AND AIMS: Coronary computed tomographic angiography (CCTA) is pivotal in diagnosing coronary artery disease (CAD). We explored the link between CAD severity and two biomarkers, Pan-Immune Inflammation Value (PIV) and Atherogenic Index of Plasma (AIP), in stable CAD patients. METHODS AND RESULTS: A retrospective observational study of 409 CCTA patients with stable angina pectoris. Logistic regression identified predictors of severe CAD, stratified by CAD-RADS score. Receiver Operating Characteristic (ROC) curves evaluated predictive performance. PIV and AIP were significant predictors of severe CAD (PIV: OR 1.002, 95% CI: 1.000-1.004, p < 0.021; AIP: OR 0.963, 95% CI: 0.934-0.993, p < 0.04). AUC values for predicting severe CAD were 0.563 (p < 0.001) for PIV and 0.625 (p < 0.05) for AIP. Combined with age, AUC improved to 0.662 (p < 0.02). CONCLUSIONS: PIV and AIP were associated with severe CAD, with AIP demonstrating superior predictive capability. Incorporating AIP into risk assessment could enhance CAD prediction, offering a cost-effective and accessible method for identifying individuals at high risk of coronary atherosclerosis.

Preinterventional pan-immune-inflammation value as a tool to predict postcontrast acute kidney injury among acute coronary syndrome patients implanted drug-eluting stents: a retrospective observational study.

We evaluated the value of pan-immune-inflammation value (PIV) in predicting the risk for postcontrast acute kidney injury (PCAKI), an important complication following percutaneous coronary intervention (PCI) in acute coronary syndrome (ACS) patients. Medical records of 839 ACS patients underwent PCI between June 2019 and December 2022 were retrospectively analyzed. Patients were divided into two groups: PCAKI (-) and PCAKI (+). PCAKI was defined as a ≥ 0.5 mg/dL and/or a ≥ 25% increase in serum creatinine within 72 h after PCI. The PIV was computed as [neutrophils × platelets × monocytes]÷lymphocytes. The mean age was 60.7 ± 12.9 years. PCAKI was detected in 105 (12.51%) patients. PIV was higher in the PCAKI (+) group compared to PCAKI (-) group (median 1150, interquartile range [IQR] 663-2021 vs median 366, IQR 238-527, p < 0.001). Receiver operating characteristic curve analysis showed that the best cutoff of PIV for predicting PCAKI was 576 with 81% sensitivity and 80% specificity. PIV was superior to neutrophil-lymphocyte ratio and platelet-lymphocyte ratio for the prediction of PCAKI (area under curve:0.894, 0.849 and 0.817, respectively, p < 0.001 for all). A high PIV was independently correlated with PCAKI (≤576 vs. >576, odds ratio [OR] 12.484, 95%confidence interval [CI] 4.853-32.118, p < 0.001) together with older age (OR 1.058, p = 0.009), female gender (OR 4.374, p = 0.005), active smoking (OR 0.193, p = 0.012), left ventricular ejection fraction (OR 0.954, p = 0.021), creatinine (OR 10.120, p < 0.001), hemoglobin (OR 0.759, p = 0.019) and c-reactive protein (OR 1.121, p = 0.002). In conclusion, a high PIV seems to be an easily assessable tool that can be used in clinical practice for predicting the risk of PCAKI in ACS patients implanted drug-eluting stents.

Association between Pan-Immune-Inflammation Value and Contrast-Induced Nephropathy with Coronary Angiography.

Background: Contrast-induced nephropathy (CIN) is one of the most important complications after invasive cardiovascular procedures. Considering the pivotal role of inflammation in CIN development, the use of peripheral blood-based indexes may be an easily available biomarker to predict CIN risk. Therefore, in the present study, we evaluated the association between the pan-immune-inflammation value (PIV) and the risk of CIN. Patients and Methods: A total of 1343 patients undergoing coronary angiography (CAG) were included. The PIV was calculated with the following equation: (neutrophil count × platelet count × monocyte count)/lymphocyte count. Multivariable regression analyses were used to determine the association between clinical and laboratory parameters and CIN development. Results: The median age of the cohort was 58 (IQR 50-67), and 48.2% of the patients were female. CIN developed in 202 patients (15%) in follow-up. In multivariate analyses, older age (OR: 1.015, 95% CI: 1.002-1.028, p = 0.020) and higher PIV levels (OR: 1.016, 95% CI: 1.004-1.028, p = 0.008) were associated with a higher CIN risk, while the use of antiplatelet agents was associated with a lower risk of CIN (OR: 0.670, 95% CI: 0.475-0.945, p = 0.022). Conclusions: We demonstrated that the risk of CIN was significantly higher in patients with higher PIV and older patients in a large cohort of patients undergoing CAG for stable ischemic heart disease. If supported with prospective evidence, PIV levels could be used as a minimally invasive reflector of CIN.

Comparison of pan-immune-inflammation value with other inflammation markers of long-term survival after ST-segment elevation myocardial infarction.

BACKGROUND: Atherosclerosis is a process that causes coronary artery disease and is associated with the inflammatory response. In this study, we aimed to evaluate the association of Pan-Immune-Inflammation Value (PIV) with in-hospital and long-term mortality in STEMI patients. METHODS: A total of 658 patients who were admitted to the emergency department of two tertiary centers with the diagnosis of STEMI and underwent percutaneous coronary intervention (PCI) between 2018 and 2022 were retrospectively enrolled. PIV and other inflammation parameters were compared for the study population. The primary outcome was one-year all-cause of mortality. RESULTS: The mean age was 58.7 ± 17.1 years and 507 (76.9%) were male. The mean duration of the follow-up was 18.8 ± 8.5 months (median 18.9 months). PIV was superior to the neutrophil-lymphocyte ratio, platelet-lymphocyte ratio, and systemic immune-inflammation index for the prediction of primary and secondary outcomes in STEMI. CONCLUSION: Our study reveals that PIV is a better predictor of mortality in STEMI patients. Prospective studies are needed to validate this biomarker.

Utility of pre-chemoradiotherapy Pan-Immune-Inflammation-Value for predicting the osteoradionecrosis rates in locally advanced nasopharyngeal cancers.

PURPOSE: The aim of this retrospective study was to explore whether pretreatment Pan-Immune-Inflammation-Value (PIV) measurements might predict the risk of mandibular osteoradionecrosis (ORN) in patients receiving concurrent chemoradiotherapy (CCRT) for locally advanced nasopharyngeal cancer (LA-NPC). METHODS: The platelet, monocyte, neutrophil, and lymphocyte counts acquired on the first day of CCRT were used to compute pretreatment PIV levels: PIV = (Plateletsâ€¯× Monocytesâ€¯× Neutrophils) ÷ Lymphocytes. Receiver operating characteristic curve analysis was used to determine the association between ORN rates and PIV levels. Spearman correlation analysis was used to examine the probable intergroup correlations. The potential link between the pretreatment PIV levels and the post-treatment ORN rates was determined as the primary objective. RESULTS: 21 (10.0%) of 210 eligible patients were diagnosed with ORN. The optimal pre-CCRT PIV cutoff was 833, which separated patients into two PIV groups with divergent ORN prevalence estimates: Group 1: PIV < 833 (N = 153), and Group 2: PIV ≥ 833 (N = 57). The comparison analysis found that the PIV ≥ 833 cohort had significantly higher ORN rates than the PIV < 833 cohort (29.8% vs. 2.6%; P < 0.001). Other characteristics linked to significantly higher ORN rates were the patient's continuing smoking, the use of the Three-dimensional conformal radiation therapy technique, the mean mandibular dose of ≥ 58.1 Gy, the number of tooth extractions before CCRT ≥ 4, and the presence of tooth extractions after CCRT. The independent importance of all factors on higher ORN occurrence rates were retained in multivariate analysis (P < 0.05). CONCLUSIONS: Our findings revealed a strong link between aggravated inflammatory response and ORN genesis, with high pretreatment PIV levels related to significantly higher ORN rates.

Pan-immune-inflammation and its dynamics: predictors of survival and immune-related adverse events in patients with advanced NSCLC receiving immunotherapy.

OBJECTIVES: Pan-immune-inflammation value (PIV) is defined by the neutrophil, platelet, monocyte, and lymphocyte counts and is associated with immune-checkpoint inhibitor (ICI) therapy outcomes in advanced non-small cell lung cancer (aNSCLC). However, PIV is dynamic under therapy and its longitudinal assessment may help predict efficacy. This study investigated the impact of baseline PIV and its dynamics on ICI efficacy and its immune-related adverse events (irAEs). The study additionally attempted to understand the biological significance of PIV. PATIENTS AND METHODS: This retrospective study analyzed the clinical data of 269 consecutive patients with aNSCLC. PIV was calculated at baseline and at weeks 3-4 to determine its association with overall survival (OS), progression-free survival (PFS), and irAEs. RESULTS: Results revealed that low baseline PIV was positively correlated with the incidence of irAEs. Moreover, a low PIV at baseline was significantly associated with a prolonged PFS (median PFS: 10 vs. 7 months, p = 0.0005) and OS (median OS: 29 vs. 21 months, p < 0.0001). When the PIV at baseline and weeks 3-4 was considered together, its low dynamics correlated with a higher incidence of irAEs (p = 0.001), a longer PFS (median PFS, 9 vs. 6 months, p = 0.012), and a longer OS (median OS; 28 vs. 21 months, p = 0.002). CONCLUSION: Thus, PIV at baseline and its dynamics are novel and potent predictors of irAEs, PFS, and OS in patients with aNSCLC receiving immunotherapy. Moreover, the PIV dynamics may be an effective, novel surrogate marker to dynamically observe the efficacy of immunotherapy.

Association between pan-immune-inflammation value and no-reflow in patients with ST elevation myocardial infarction undergoing percutaneous coronary intervention.

Noreflow is a condition associated with a poor prognosis in ST segment elevation myocardial infarction patients. It has been shown that many inflammatory markers and index such as procalcitonin, C-reactive protein, neutrophil to lymphocyte ratio, systemic immune inflammatory index (SII), are associated with noreflow. We used a brand-new index pan-immune-inflammation value (PIV) to retrospectively evaluate the relationship between PIV and noreflow. A total of 1212 patients were included for analysis. Noreflow was observed in 145 patients. In multivariate analysis, PIV (odds ratio (OR): 1.025; [1.002-1.115], p < 0.001), baseline ejection fraction (OR: 0.963; [0.934-0.993], p = 0.015), stent length (OR: 1.032; [1.010-1.054], p = 0.004), age (OR: 1.034; [1.014-1.053], p = 0.001) and pain to PCI time (OR: 1.003 [1.002-1.005], p < 0.001) were observed to be the independent predictors of noreflow. ROC curve analysis showed that the best cut off value of PIV for predicting noreflow was ≥889 with 77.2% sensitivity and 77.5% specificity (AUC, 0.828; 95% CI [0.806-0.849]). A ROC curve comparison analysis was performed to compare PIV and SII. The predictive power of PIV was higher than SII (differences between areas: 0.154; p < 0.001). According to our findings, an increase in PIV is an independent predictor of noreflow in patients with STEMI.

The prognostic impact of inflammation in patients with decompensated acute heart failure, as assessed using the pan-immune inflammation value (PIV).

There is increasing evidence that composite scores based on blood counts, which are reflectors of uncontrolled inflammation in the development and progression of heart failure, can be used as prognostic biomarkers in heart failure patients. The prognostic effects of pan-immune inflammation (PIV) as an independent predictor of in-hospital mortality in patients with acute heart failure (AHF) were evaluated based on this evidence. The data of 640 consecutive patients hospitalized for New York Heart Association (NYHA) class 2-3-4 AHF with reduced ejection fraction were analyzed and 565 patients were included after exclusion. The primary outcome was in hospital all-cause death. Secondary outcomes were defined as the following in-hospital events: Acute kidney injury (AKI), malignant arrhythmias, acute renal failure (ARF) and stroke. The PIV was computed using hemogram parameters such as lymphocytes, neutrophils, monocytes and platelets. Patients were categorized as low or high PIV group according to the median value, which was 382.8. A total of 81 (14.3%) in-hospital deaths, 31 (5.4%) AKI, 34 (6%) malignant arrhythmias, 60 (10.6%) ARF and 11 (2%) strokes were reported. Patients with high PIV had a higher in-hospital mortality rate than patients with low PIV (OR: 1.51, 95% CI, 1.26-1.80, p < 0.001). Incorporating PIV into the full model significantly improved model performance (odds ratio X2, p < 0.001) compared to the baseline model constructed with other inflammatory markers. PIV is a potent predictor of prognosis with better performance than other well-known inflammatory markers for patients with AHF.

Pan-immune inflammation value; a novel biomarker reflecting inflammation associated with frailty.

BACKGROUND: Frailty is suggested to be associated with age-related changes in the immune system, namely immunosenescence. Few studies have investigated the association of frailty with circulating immune biomarkers reflecting immunosenescence. Pan-immune inflammation value (PIV) is a new composite circulating immune biomarker to predict inflammation status. AIM: This study aimed to assess the relationship between PIV and frailty. METHODS: A total of 405 geriatric patients were enrolled in the study. All participants underwent a comprehensive geriatric assessment. The comorbidity burden was evaluated with Charlson Comorbidity Index. Frailty status was evaluated via the Clinical Frailty Scale (CFS), and patients with CFS scores ≥ 5 were defined as living with frailty. PIV was calculated using the formula: (Neutrophil × monocyte × platelet)/lymphocyte. Patients were defined as PIV-low (≤ 372) and PIV-high (> 372). RESULTS: The median age of participants was 72 (IQR = 67-78) years and; 63.0% (n = 225) were female. Patients were divided into two categories (i.e., robust and living with frailty groups), and 320 (79.0%) and 85 (21.0%) patients were in each group, respectively. Median PIV was higher in the living with frailty group (p = 0.008). In the linear and logistic regression analyses, both PIV and PIV-high (> 372) were significantly associated with frailty independently of confounders. DISCUSSION AND CONCLUSION: This is the first study revealing the relationship between PIV and frailty. PIV may be seen as a novel biomarker reflecting inflammation associated with frailty.

The association between pan-immune-inflammation value and survival in head and neck squamous cell carcinoma.

PURPOSE: A significant portion of patients with locally advanced head and neck squamous cell carcinoma (HNSCC) relapse despite multimodality treatment denoting the need for biomarkers. The pan-immune-inflammation value (PIV) is a recently developed blood count-based prognostic biomarker. We evaluated the relationship between PIV and survival in locally advanced HNSCC patients treated with chemoradiotherapy (CRT). METHODS: A total of 199 patients who underwent CRT at Hacettepe University Oncology Hospital were included. The relationship between clinical and laboratory parameters with overall survival (OS) and disease-free survival (DFS) was analyzed by multivariate analyses. RESULTS: The median age was 59 years and 90.5% of the patients were male. 66.8% of the patients had laryngeal primaries, and 78.9% had T3-T4 disease. 84.9% of the patients received CRT with cisplatin. The optimal PIV threshold value was calculated as 404 in ROC analyses. This PIV value had 75.8% sensitivity and 70.4% specificity for OS prediction (AUC 0.781; 95% CI 0.715-0.846; p < 0.001). In multivariate analyses, high PIV levels (≤ 404 vs. > 404, HR 2.862; 95% CI 1.553-5.276; p = 0.001), higher NLR (≤ 2.5 vs. > 2.5, HR 1.827; 95% CI 1.017-3.281; p = 0.044) levels and ECOG performance score of 2 (HR 2.267; 95% CI 1.385-3.711; p = 0.001) were associated with shorter OS. These factors were associated with shorter DFS also (HR for PIV 2.485, 95% CI 1.383-4.467, p = 0.002). CONCLUSIONS: We observed shorter OS and DFS in locally advanced HNSCC patients with high PIV levels. If prospective studies support our findings, the PIV score could be a prognostic biomarker in HNSCC.

Pan-immune-inflammation value is associated with poor prognosis in patients undergoing peritoneal dialysis.

BACKGROUND: Immune-inflammatory biomarkers (IIBs) have been shown to be correlated with prognosis in patients undergoing peritoneal dialysis (PD). In this study, we aimed to evaluate the relationship between a novel comprehensive biomarker, the pan-immune-inflammation value (PIV), and the prognosis of patients undergoing PD. METHODS: We retrospectively analyzed data from a multicenter, large-sample PD database. PIV was calculated as (neutrophil count × platelet count × monocyte count)/lymphocyte count. The prognostic endpoints in this study were all-cause death all-cause, cardiovascular disease (CVD) and infection-related death. The Kaplan-Meier method, a Cox proportional hazards regression, Fine-Gray competing risk model, smooth curve, and subgroup analysis were used to analyze the independent relationship between PIV and the prognosis of patients undergoing PD. RESULTS: A total of 2796 cases of PD were included, and the study population was divided into Tertiles 1, 2, and 3, according to the tertiles of baseline PIVs. After adjusting for multiple model factors, patients in the Tertile 3 group had a significantly higher risk of all-cause death, CVD death and infection-related death compared with patients with PIV in the Tertile 1 group. Interaction tests showed no positive correlations for subgroup parameters. Regarding all-cause death, compared with the lowest tertile, the multivariable-adjusted hazard ratios (95% confidence intervals) of the highest and middle tertiles were 1.55 (1.25-1.94) and 1.77 (1.43-2.19), respectively; PIV (log2 processing) was associated with 17% excess of mortality in the continuous model. CONCLUSIONS: A high PIV at baseline was significantly associated with an increased risk of deaths due to all-causes, CVD and infection in patients undergoing PD.

Prognostic value of pan-immune-inflammation value and body mass index in geriatric patients with metastatic renal cell carcinoma treated with tyrosine kinase inhibitors as first line treatment. A single-center retrospective study.

Introduction: Geriatric patients with metastatic renal cell carcinoma (mRCC) are underrepresented in clinical trials. Evaluation of the efficacy of the treatment and assignation of individuals to proper prognostic groups is an absolute necessity to guarantee them the best possible care. Material and methods: A total of 138 geriatric patients with mRCC treated with first-line tyrosine kinase inhibitors (TKIs) at the Maria Sklodowska-Curie National Research Institute of Oncology were retrospectively analyzed to determine whether the body mass index (BMI) and pan-immune-inflammation value (PIV) are prognostic values for overall survival (OS) and progression-free survival (PFS) in this type of cancer. For this purpose, Cox's proportional hazard model was used. Results: The median duration of follow-up for surviving patients was 46.6 (95% CI: 17.4-75.8) months. The median OS and PFS were respectively 33.8 months (95% CI: 23.8-47.8) and 19.1 months (95% CI: 15.0-23.3). BMI (p = 0.034) and PIV (p < 0.001) were statistically significantly associated with OS, and PIV (p = 0.001) was statistically significantly associated with PFS. The risk of death for patients from the high-PIV group (cut-off point: 548) was 3.4 times higher than for those with lower PIV values. The corresponding risk of progression for patients from the high-PIV group was 2.2 times higher. The G8 geriatric screening tool was not identified as a prognostic factor. Conclusions: Lower PIV and obesity are associated with longer OS in geriatric mRCC patients treated with TKIs in the first line. These factors may be considered while making treatment decisions if further studies show the same results.

Prognostic role of pan-immune-inflammation value in patients with metastatic castration-resistant prostate cancer treated with androgen receptor-signaling inhibitors.

AIM: To assess the prognostic effect of pan-immune inflammation value (PIV) in patients with metastatic castration-resistant prostate cancer (mCRPC) treated with abiraterone acetate (AA) or enzalutamide. METHODS: Patients with mCRPC treated with AA or enzalutamide between January 2010 and June 2021 were included in this study. The most recently examined complete blood count values in the 1-month period before treatment were used for calculating PIV. The relationship between overall survival (OS) and PIV was evaluated by multivariate analysis. By using PIV and lactate dehydrogenase (LDH) levels which had shown survival effect at multivariate analysis, PIV-LDH combined score was established. RESULTS: A total of 114 patients were included in this study. At the median follow-up of 34.6 months (95% confidence interval [CI]: 32.4-36.8), the median OS was 21 months (95% CI: 17.6-21.3). The median OS in the low-PIV group was significantly higher than in the high-PIV group (34.4 months (95% CI: 21.3-47.5) vs. 14.3 months (95% CI: 10.0-18.7), p < 0.001). In the multivariate analysis for OS, high PIV (hazard ratio [HR]: 1.86, 95% CI: 1.11-3.13, p = 0.018) and LDH value 1.5 times the upper limit of normal and above (HR: 3.65 95%, CI: 1.86-7.16, p < 0.001) were associated with shorter OS. When survival analysis was performed according to the PIV-LDH combined score, the median OS was 34.4 months (95% CI: 22.2-46.6) in the low-risk group, 17.7 months (95% CI: 11.7-23.6) in the intermediate-risk group, and 8.4 months (95% CI: 5.1-11.7) in the high-risk group (p < 0.001). The C-index of the combined PIV-LDH score was higher than the C-index of PIV (0.65 vs. 0.61). CONCLUSION: In this study, we demonstrated that PIV was an independent prognostic factor for OS in patients with mCRPC treated with AA or enzalutamide. Additionally, PIV-LDH combined score may be considered a promising composite peripheral blood-based biomarker to predict OS in those patients.

The preoperative pan-immune-inflammation value is a novel prognostic predictor for with stage I-III colorectal cancer patients undergoing surgery.

PURPOSE: The pan-immune-inflammation value (PIV) is useful for stratifying outcomes in patients with metastatic colorectal cancer. However, it is unclear whether preoperative PIV can predict the surgical outcomes of patients with stage I-III colorectal cancer who receive surgery. METHODS: The records of 758 patients with stage I-III colorectal cancer who received surgical treatment were retrospectively reviewed. The preoperative PIV was calculated as follows: (neutrophil count × platelet count × monocyte count)/lymphocyte count. The cut-off value was determined using a receiver operating characteristic curve for overall survival. RESULTS: The cut-off value of the preoperative PIV was 376. Five hundred sixty-eight patients (74.9%) had low values (≤ 376), and 190 (25.1%) had high values (> 376). Univariate and multivariate analyses revealed that the PIV (> 376/ ≤ 376) (HR 2.485; 95% CI 1.552-3.981, P < 0.001) was significantly associated with overall survival, as well as age (> 60/ ≤ 60, years) (HR 1.988; 95% CI 1.038-3.807, P = 0.038), globulin-to-albumin ratio (> 0.83/ ≤ 0.83) (HR 2.013; 95% CI 1.231-3.290, P = 0.005) and postoperative complication (C-D grade III-V/0-II) (HR 1.991; 95% CI 1.154-3.438, P = 0.013). The Kaplan-Meier method and log-rank test showed significant differences in overall survival between patients with stage I-III disease with high (> 376) and low (≤ 376) PIVs. CONCLUSION: The preoperative PIV is useful for predicting surgical outcomes in patients with stage I-III colorectal cancer.