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Background: Insulin resistance (IR), a hallmark feature of diabetes and metabolic syndrome, is characterized by chronic low-grade inflammation. Pan-immune-inflammation value (PIV), an emerging immune cell count-based inflammatory index, is the global quantifier of systemic inflammation. This study analyses the levels of PIV and its association with various markers of IR. Materials and Methods: This retrospective, cross-sectional study was done using the Center for Disease Control-National Health and Nutritional Examination Survey (CDC-NHANES) pre-pandemic data from 2017-2020. Data from 4620 survey participants was included after screening. Homeostasis model assessments of insulin resistance (HOMA-IR) and beta-cell function (HOMA-B), triglyceride glucose (TyG) index, visceral adiposity index (VAI), and lipid accumulation product (LAP) were used as markers of IR. Multiple logistic regression and trend analysis were done to determine the associations, and receiver operator characteristic curve (ROC) analysis was done to estimate the diagnostic utility of PIV to predict IR. Results: PIV levels were significantly higher in obesity, diabetes, and metabolic syndrome. HOMA-IR, HOMA-B, LAP, VAI, and TyG levels were found to be higher in those with higher PIV (i.e., quartiles 4 and 3). Regression and trend analysis showed that the odds ratio for IR increased with PIV. However, ROC indicated that the diagnostic utility of PIV to predict IR is low compared to the other surrogate markers. Conclusions: PIV levels differed significantly based on glycemic status, BMI, and metabolic syndrome status. PIV showed a significant positive association with IR. However, the ability of PIV to predict IR is not optimal compared to other surrogate markers.
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Objective: There is increasing evidence for the effect of inflammation on the etiology of febrile seizure (FS) patients. We aimed to investigate the role of easily accessible inflammatory markers such as the neutrophil-lymphocyte ratio (NLR), systemic immune-inflammation index (SII), systemic inflammation response index (SIRI), neutrophil-lymphocyte-platelet ratio (NLPR), and pan-immune-inflammation value (PIV) in febrile seizure. Methods: A total of 300 children, including 100 with febrile convulsions (FS), 100 febrile controls (FCs), and 100 healthy controls (HCs), were included in this retrospective study. The FS group was compared with the FC and HC groups in terms of these inflammatory indexes. Results: Between the FS group and the FC group, the neutrophil count was significantly higher in the FS group (p = 0.001) and the lymphocyte count was significantly lower (p < 0.001). The NLR (p < 0.001), SII (p < 0.001), SIRI (p < 0.001), NLPR (p < 0.001), and PIV (p < 0.001) were significantly higher in the FS group than in both the FC and healthy control groups. The optimal cut-off values for predicting FS in febrile conditions were 3.59> for NLR, >870.47 for SII, >1.96 for SIRI, 0.96> for NLPR, and >532.75 for PIV. Conclusions: The inflammatory indices are inexpensive, easily accessible hematological markers that can contribute to the diagnosis of FS.
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Background: The inflammatory response to atherosclerosis is a process that leads to coronary artery disease. Pan-immune-inflammation value (PIV) has emerged as a new and simple biomarker of inflammation. However, studies on the predictive power of PIV for major adverse cardiovascular events (MACE) or the degree of coronary artery stenosis are scarce. We aimed to explore the predictive ability of PIV for MACE and the degree of coronary artery stenosis in patients with ST-segment elevation myocardial infarction (STEMI) after percutaneous coronary intervention (PCI) during hospitalization. Methods: This study included 542 patients who were diagnosed with STEMI and who underwent PCI between 2016 and 2023 and whose PIV and other inflammatory markers were measured. Using univariate and multivariate logistic regression analysis, risk variables for MACE following PCI and severe coronary stenosis during hospitalization were assessed to create receiver operating characteristic (ROC) curves and determine the best thresholds for inflammatory markers. Spearman correlation analysis was used to evaluate the correlation of PIV and other inflammatory markers with the Gensini score (GS). Results: Compared with the systemic inflammatory index (SII), platelet-to-lymphocyte ratio (PLR), and neutrophil-to-lymphocyte ratio (NLR), the PIV may have greater predictive value in terms of the occurrence of MACE and the degree of coronary stenosis after PCI in hospitalized STEMI patients. The correlation between the PIV and GS was strong. Conclusions: PIV was superior to the SII, PLR, and NLR in predicting inpatient prognosis and severe coronary stenosis after PCI for STEMI patients.
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Purpose: To investigate the prognostic significance of pan-immune-inflammation value (PIV) and PILE score (based on PIV, lactate dehydrogenase (LDH), and Eastern Cooperative Oncology Group Performance Status (ECOG PS)) in patients with primary central nervous system lymphoma (PCNSL). Patients and Methods: A total of 109 patients were enrolled. PIV was calculated as follows: (neutrophil count × platelet count × monocyte count)/lymphocyte count. The PILE score was incorporated based on PIV, LDH levels, and ECOG PS. The Kaplan-Meier curves and Cox hazards regression models were applied for survival analyses. The relationship between PIV, PILE, and therapeutic response was examined. Results: Baseline high PIV was significantly associated with worse overall survival (OS) in univariate (HR 3.990, 95% CI 1.778-8.954, p < 0.001) and multivariate (HR 3.047, 95% CI 1.175-7.897, p = 0.022) analyses. High PIV was also associated with worse progression-free survival (PFS) in univariate (HR 2.121, 95% CI 1.075-4.186, p = 0.030) but not significant in multivariate analyses. PIV outperformed other systemic inflammation parameters. The patients in the high PILE group (PILE score 2-3) had worse OS (p = 0.008) and PFS (p < 0.001) compared to the low PILE group (PILE score 0-1). PILE was independently associated with therapeutic response to initial treatment (OR 0.17, 95% CI 0.05-0.46; p < 0.001). Conclusion: High PIV and PILE were correlated with worse clinical outcomes in PCNSL patients, indicating that PIV and PILE might be a powerful predictor of prognosis and a potential predictive indicator for therapeutic response in PCNSL.
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BACKGROUND: This study aimed to investigate the relationship between the pan-immune-inflammation value (PIV) and periodontitis based on a large national survey. METHODS: In the present cross-sectional study, data were obtained from the National Health and Nutrition Examination Survey (NHANES) 2009-2014, which included a total of 10,300 participants. The categorization of periodontitis was based on the 2017 classification scheme. The PIV was determined using the formula: (neutrophils count × monocyte count × platelet count)/lymphocytes count. Restricted cubic spline and weighted multivariable logistic regression analyses were employed to evaluate the associations between the PIV with periodontitis. RESULTS: The associations between PIV and stage III/IV periodontitis followed a U-shaped pattern (Pnon-linearity < 0.001). The risk of developing stage III/IV periodontitis showed an increasing trend among participants in the first quartile (odds ratio [OR] = 1.21; 95% confidence interval [CI]: 1.01-1.46), third quartile (OR = 1.34; 95% CI: 1.11-1.61), and fourth quartile (OR = 1.47; 95% CI: 1.25-1.73) compared to those in the second quartile. Subgroup analysis indicated stronger associations of PIV with periodontitis in males (ORQ4vs2 = 1.72, 95% CI: 1.36-2.18) and individuals with hypertension (ORQ4vs2 = 1.78, 95% CI: 1.38-2.28) with significant interactions (Pinteraction < 0.05). CONCLUSIONS: There is a U-shaped association between PIV and stage III/IV periodontitis, which suggests a potential adjunctive treatment strategy for periodontitis. Higher PIV values were found to have a stronger correlation with stage III/IV periodontitis in males and individuals with hypertension. Further prospective trials are needed to confirm the validity of our results. PLAIN LANGUAGE SUMMARY: A U-shaped association exists between the pan-immune inflammation value and periodontitis in US adults, suggesting that maintaining a moderate immune inflammation response is crucial for periodontal health.
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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.
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BACKGROUND: Inflammation and immunity play important roles in the formation of coronary collateral circulation (CCC). The pan-immune-inflammation value (PIV) is a novel marker for evaluating systemic inflammation and immunity. The study aimed to investigate the association between the PIV and CCC formation in patients with chronic total occlusion (CTO). METHODS: This retrospective study enrolled 1150 patients who were diagnosed with CTO through coronary angiographic (CAG) examinations from January 2013 to December 2021 in China. The Cohen-Rentrop criteria were used to catagorize CCC formation: good CCC formation (Rentrop grade 2-3) and poor CCC formation group (Rentrop grade 0-1). Based on the tertiles of the PIV, all patients were classified into three groups as follows: P1 group, PIV ≤ 237.56; P2 group, 237.56< PIV ≤ 575.18; and P3 group, PIV > 575.18. RESULTS: A significant relationship between the PIV and the formation of CCC was observed in our study. Utilizing multivariate logistic regression and adjusting for confounding factors, the PIV emerged as an independent risk factor for poor CCC formation. Notably, the restricted cubic splines revealed a dose-response relationship between the PIV and risk of poor CCC formation. In terms of predictive accuracy, the area under the ROC curve (AUC) for PIV in anticipating poor CCC formation was 0.618 (95% CI: 0.584-0.651, P < 0.001). Furthermore, the net reclassification index (NRI) and integrated discrimination index (IDI) for PIV, concerning the prediction of poor CCC formation, were found to be 0.272 (95% CI: 0.142-0.352, P < 0.001) and 0.051 (95% CI: 0.037-0.065, P < 0.001), respectively. It's noteworthy that both the NRI and IDI values were higher for PIV compared to other inflammatory biomarkers, suggesting its superiority in predictive capacity. CONCLUSIONS: PIV was associated with the formation of CCC. Notably, PIV exhibited potential as a predictor for poor CCC formation and showcased superior predictive performance compared to other complete blood count-based inflammatory biomarkers.
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Circulación Colateral , Angiografía Coronaria , Circulación Coronaria , Oclusión Coronaria , Mediadores de Inflamación , Inflamación , Valor Predictivo de las Pruebas , Humanos , Masculino , Persona de Mediana Edad , Oclusión Coronaria/fisiopatología , Oclusión Coronaria/diagnóstico por imagen , Femenino , Estudios Retrospectivos , Enfermedad Crónica , Anciano , Inflamación/diagnóstico , Inflamación/sangre , Inflamación/inmunología , Inflamación/fisiopatología , Mediadores de Inflamación/sangre , Medición de Riesgo , China , Biomarcadores/sangre , Factores de Riesgo , PronósticoRESUMEN
Objectives: We aimed to evaluate the predictive importance of various clinical and laboratory parameters in the differential diagnosis of Acute Coronary Syndrome (ACS). Understanding these predictors is critical for improving diagnostic accuracy, guiding therapeutic decisions, and ultimately enhancing patient outcomes. Methods: The study included a total of 427 patients diagnosed with ACS, comprising 142 with unstable angina, 142 with non-ST elevation myocardial infarction (NSTEMI), and 143 with ST elevation myocardial infarction (STEMI). The data were collected from medical records of patients treated at a tertiary care hospital between January 2020 and December 2024. In addition to other biochemical parameters, triglyceride/HDL ratio (THR), triglyceride-glucose index (TGI), and Pan-Immune-Inflammation Value (PIV) were calculated and compared. Results: THR, TGI, PIV, and mortality rate were statistically higher in the STEMI group (p = 0.034, p = 0.031, p = 0.022, p = 0.045, respectively). The risk factors were found to be significantly associated with STEMI in the multiple logistic regression analysis and included age, total cholesterol, triglycerides, diabetes mellitus, smoking, cTnI, LVEF, THR, TGI, and PIV. High THR increases the risk of STEMI (AUC = 0.67, 95% CI: 0.62-0.72, p = 0.020). High THR increases the risk of mortality in ACS patients (AUC = 0.70, 95% CI: 0.65-0.75, p = 0.004). THRs above 3.5 are associated with higher risk. Sensitivity is 75% and specificity is 60%. High TGI increases the risk of mortality in ACS patients (AUC = 0.73, 95% CI: 0.68-0.78, p = 0.007). TGIs above 8.5 are associated with higher risk. Sensitivity is 78% and specificity is 63%. High PIVs increase the risk of mortality in ACS patients (AUC = 0.75, 95% CI: 0.70-0.80, p = 0.009). PIVs above 370 are associated with higher risk. Sensitivity is 80% and specificity is 65%. The combination of TGI, THR, PIV, and cTnI has the highest predictive capability over individual parameters for STEMI and mortality. Conclusions: We found that age, total cholesterol, triglycerides, cTnI, THR, TGI, and PIV increase, low LVEF, presence of diabetes mellitus, and smoking have predictive values for STEMI and mortality in patients with ACS. Unlike the studies in the literature, this is the first study in which cTnI, THR, TGI, and PIV values were evaluated together in ACS and mortality prediction.
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Purpose: The inflammatory response of the body is intimately linked to the quick onset and high in-hospital mortality of Acute Type A Aortic Dissection (ATAAD). The purpose of the study was to examine the connection between in-hospital mortality in patients with ATAAD upon admission and the Pan-Immune-Inflammation Value (PIV). Patients and Methods: 308 patients who were diagnosed with ATAAD between September 2018 and October 2021 at Fujian Provincial Center for Cardiovascular Medicine had their clinical data retrospectively examined. PIV was assessed at the time of study population admission, with in-hospital mortality serving as the main outcome measure. Patients were divided into two groups, the high PIV group (PIV > 1807.704) and the low PIV group (PIV < 1807.704), based on the PIV ROC curve and the best threshold of the Youden index. The clinical results of the two groups were then compared. Results: Among ATAAD patients, postoperative in-hospital mortality was higher in the high PIV group (54.7% vs 10.6%, P < 0.001), and the high PIV group had significantly higher rates of postoperative acute kidney injury, acute liver insufficiency, and gastrointestinal hemorrhage (P < 0.05). Additionally, the high PIV group's ICU stays lasted longer than the low PIV group's (P < 0.05). The results of multifactorial logistic regression analysis, which controlled for other variables, indicated that the mechanical ventilation time (OR = 1.860, 95% CI: 1.437, 2.408; P < 0.001), the high PIV group (> 1807.704) (OR = 1.939, 95% CI: 1.257, 2.990; P = 0.003), the cardiopulmonary bypass time (OR = 1.011, 95% CI: 1.004, 1.018; P = 0.002), and the white blood cell count (OR = 1.188, 95% CI: 1.054, 1.340; P = 0.005) were independent risk factors for postoperative in-hospital mortality in ATAAD patients. Conclusion: Postoperative death in ATAAD patients was independently predicted by high PIV levels at admission. Patients should be informed about their preoperative inflammatory status and actively participate in prompt clinical decision-making and treatment.
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Trastuzumab emtansine (T-DM1) is a mainstay therapy for HER2-positive metastatic breast cancer (mBC). However, identifying patients who will benefit most remains a challenge due to the lack of reliable biomarkers. The recently developed pan-immune-inflammation value (PIV), a novel immune-inflammation marker, could aid in this regard, considering the immunomodulatory effects of T-DM1. Therefore, we aimed to evaluate the association between the PIV and the efficacy of T-DM1 in patients with HER2-positive mBC. A total of 122 HER2-positive mBC patients treated with T-DM1 were included. Receiver operating characteristic (ROC) curve analyses were conducted to determine the optimal PIV threshold value for survival prediction. Kaplan-Meier survival curves and Cox regression analyses were used for univariable and multivariable survival analyses, respectively. The median age was 51 years, and 95.1% of the patients had ECOG PS 0-1. The optimal PIV cutoff value was identified as 338 in ROC analyses (AUC: 0.667, 95% CI: 0.569-0.765, p = 0.002). The multivariate analysis revealed that patients in the high-PIV group had significantly shorter OS (HR: 2.332; 95% CI: 1.408-3.861; p = 0.001) and PFS (HR: 2.423; 95% CI: 1.585-3.702; p < 0.001) than patients in the low-PIV group. Additionally, both ORR and DCR were significantly lower in the high-PIV group (36.6% vs. 61.3%, p = 0.011; 56.1% vs. 76.0%, p = 0.027). Our findings suggest that pre-treatment PIV may be a novel prognostic biomarker for HER2-positive mBC patients receiving T-DM1. A low PIV level is associated with more favorable outcomes. Future prospective studies are warranted to validate these findings and explore the potential utility of PIV in aiding treatment decisions.
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Pan-Immune-Inflammation Value (PIV) has recently received more attention as a novel indicator of inflammation. We aimed to evaluate the association between PIV and prognosis in septic patients. Data were extracted from the Medical Information Mart for Intensive Care IV database. The primary and secondary outcomes were 28-day and 90-day mortality. The association between PIV and outcomes was assessed by Kaplan-Meier curves, Cox regression analysis, restricted cubic spline curves and subgroup analysis. A total of 11,331 septic patients were included. Kaplan-Meier curves showed that septic patients with higher PIV had lower 28-day survival rate. In multivariable Cox regression analysis, log2-PIV was positively associated with the risk of 28-day mortality [HR (95% CI) 1.06 (1.03, 1.09), P < 0.001]. The relationship between log2-PIV and 28-day mortality was non-linear with a predicted inflection point at 8. To the right of the inflection point, high log2-PIV was associated with an increased 28-day mortality risk [HR (95% CI) 1.13 (1.09, 1.18), P < 0.001]. However, to the left of this point, this association was non-significant [HR (95% CI) 1.01 (0.94, 1.08), P = 0.791]. Similar results were found for 90-day mortality. Our study showed a non-linear relationship between PIV and 28-day and 90-day mortality risk in septic patients.
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Sepsis , Humanos , Sepsis/mortalidad , Masculino , Femenino , Estudios Retrospectivos , Persona de Mediana Edad , Anciano , Pronóstico , Inflamación/mortalidad , Estimación de Kaplan-Meier , Biomarcadores , Unidades de Cuidados Intensivos , Modelos de Riesgos ProporcionalesRESUMEN
The pan-immune-inflammation value (PIV), calculated as (neutrophil × platelet × monocyte)/lymphocyte count, may be useful for estimating survival in breast cancer patients. To determine the prognostic value of PIV for overall survival in breast cancer patients in Lima, Peru. A retrospective cohort study was conducted. 97 breast cancer patients diagnosed between January 2010 and December 2016 had their medical records analyzed. The primary dependent variable was overall survival, and the key independent variable was the PIV, divided into high (≥ 310) and low (< 310) groups. Patient data included demographics, treatment protocols and other clinical variables. Statistical analysis involved Kaplan-Meier survival curves and Cox proportional hazards modeling. Patients with a PIV ≥ 310 had significantly lower 5-year survival functions (p = 0.004). Similar significant differences in survival were observed for clinical stage III-IV (p = 0.015), hemoglobin levels < 12 mg/Dl (p = 0.007), histological grade (p = 0.019), and nuclear grade (p < 0.001); however, molecular classification did not show a significant survival difference (p = 0.371). The adjusted Hazard Ratios showed that PIV ≥ 310 was significantly associated with poor outcome (5.08, IC95%: 1.52-16.92). While clinical stage and hemoglobin levels were associated with survival in the unadjusted model. These factors did not maintain significance after adjustment. PIV is an independent predictor of reduced survival in Peruvian breast cancer patients.
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Neoplasias de la Mama , Humanos , Neoplasias de la Mama/mortalidad , Neoplasias de la Mama/inmunología , Neoplasias de la Mama/patología , Femenino , Perú/epidemiología , Persona de Mediana Edad , Estudios Retrospectivos , Pronóstico , Adulto , Inflamación , Anciano , Estimación de Kaplan-Meier , Monocitos/inmunología , Modelos de Riesgos Proporcionales , Neutrófilos/inmunologíaRESUMEN
Objective: The aim of this study was to investigate the predictive value of systemic immune inflammation index (SII), systemic inflammatory response index (SIRI), and pan-immune inflammation value (PIV) in predicting intravenous immunoglobulin (IVIG) resistance in children diagnosed with Kawasaki disease (KD). Methods: The clinical data of pediatric patients diagnosed with Kawasaki disease and admitted to our hospital between January 2006 and December 2022 were retrospectively analyzed. Results: In total, 771 children diagnosed with KD were included in this study, 86 (11.2%) of whom were diagnosed with IVIG resistance. The correlation between SII, SIRI, PIV and IVIG resistance was evaluated using univariate testing, binary logistic regression analysis, and receiver operating characteristic (ROC) curve analysis. Our study found that the SII, SIRI, and PIV were independent risk factors (p=0.001, p<0.001, and p=0.02, respectively). The area under the ROC curve (AUC) values of the SII, SIRI, and PIV were 0.626 (95% confidence interval (CI): 0.553-0.698, p<0.001), 0.571 (95% CI: 0.500-0.642, p=0.032), and 0.568 (95% CI: 0.495-0.641, p=0.040), respectively, and the cutoff values were 2209.66, 3.77, and 1387.825, respectively. Conclusion: The SII, SIRI, and PIV have potential value in predicting IVIG resistance in patients with KD.
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Resistencia a Medicamentos , Inmunoglobulinas Intravenosas , Síndrome Mucocutáneo Linfonodular , Humanos , Síndrome Mucocutáneo Linfonodular/tratamiento farmacológico , Síndrome Mucocutáneo Linfonodular/inmunología , Inmunoglobulinas Intravenosas/uso terapéutico , Estudios Retrospectivos , Masculino , Femenino , Preescolar , Lactante , Niño , Curva ROC , Factores de Riesgo , PronósticoRESUMEN
Purpose: The purpose of this study was to investigate the predictive value of Pan-Immune-Inflammation Value (PIV) combined with the PILE score for immunotherapy in patients with advanced non-small cell lung cancer (NSCLC) and to construct a nomogram prediction model to provide reference for clinical work. Patients and Methods: Patients with advanced NSCLC who received ICIs treatment in Qingdao Municipal Hospital from January 2019 to December 2021 were selected as the study subjects. The chi-square test, Kaplan-Meier survival analysis, and Cox proportional risk regression analysis were used to evaluate the prognosis. The results were visualized by a nomogram, and the performance of the model was judged by indicators such as the area under the subject operating characteristic curve (AUC) and C-index. The patients were divided into high- and low-risk groups by PILE score, and the prognosis of patients in different risk groups was evaluated. Results: Multivariate Cox regression analysis showed that immune-related adverse events (irAEs) were prognostic factors for overall survival (OS) improvement, and ECOG PS score ≥2, bone metastases before treatment, and high PIV expression were independent risk factors for OS. The C index of OS predicted by the nomogram model is 0.750 (95% CI: 0.677-0.823), and the Calibration and ROC curves show that the model has good prediction performance. Compared with the low-risk group, patients in the high-risk group of PILE were associated with a higher inflammatory state and poorer physical condition, which often resulted in a poorer prognosis. Conclusion: PIV can be used as a prognostic indicator for patients with advanced NSCLC treated with ICIs, and a nomogram prediction model can be constructed to evaluate the survival prediction of patients, thus contributing to better clinical decision-making and prognosis assessment.
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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.
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Imágenes de Resonancia Magnética Multiparamétrica , Neutrófilos , Neoplasias de la Próstata , Humanos , Masculino , Neoplasias de la Próstata/patología , Neoplasias de la Próstata/sangre , Neoplasias de la Próstata/diagnóstico por imagen , Imágenes de Resonancia Magnética Multiparamétrica/métodos , Anciano , Persona de Mediana Edad , Neutrófilos/patología , Inflamación/sangre , Inflamación/diagnóstico por imagen , Inflamación/patología , Valor Predictivo de las Pruebas , Linfocitos/patología , Próstata/patología , Próstata/diagnóstico por imagen , Biopsia , Estudios RetrospectivosRESUMEN
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.
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Medios de Contraste , Angiografía Coronaria , Inflamación , Humanos , Femenino , Masculino , Angiografía Coronaria/efectos adversos , Angiografía Coronaria/métodos , Persona de Mediana Edad , Medios de Contraste/efectos adversos , Anciano , Inflamación/sangre , Factores de Riesgo , Enfermedades Renales/inducido químicamente , Biomarcadores/sangre , Recuento de Plaquetas/métodos , Recuento de Plaquetas/estadística & datos numéricos , Estudios de CohortesRESUMEN
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.
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Biomarcadores , Angiografía por Tomografía Computarizada , Angiografía Coronaria , Enfermedad de la Arteria Coronaria , Valor Predictivo de las Pruebas , Índice de Severidad de la Enfermedad , Humanos , Masculino , Femenino , Enfermedad de la Arteria Coronaria/diagnóstico por imagen , Enfermedad de la Arteria Coronaria/sangre , Enfermedad de la Arteria Coronaria/inmunología , Enfermedad de la Arteria Coronaria/diagnóstico , Estudios Retrospectivos , Persona de Mediana Edad , Anciano , Biomarcadores/sangre , Mediadores de Inflamación/sangre , Medición de Riesgo , Angina Estable/diagnóstico por imagen , Angina Estable/sangre , Angina Estable/diagnóstico , Angina Estable/inmunología , Pronóstico , Inflamación/sangre , Inflamación/diagnóstico , Inflamación/diagnóstico por imagen , Factores de Riesgo , Vasos Coronarios/diagnóstico por imagen , Área Bajo la CurvaRESUMEN
Background: The prognostic value of an effective biomarker, pan-immune-inflammation value (PIV), for head and neck squamous cell carcinoma (HNSCC) patients after radical surgery or chemoradiotherapy has not been well explored. This study aimed to construct and validate nomograms based on PIV to predict survival outcomes of HNSCC patients. Methods: A total of 161 HNSCC patients who underwent radical surgery were enrolled retrospectively for development cohort. The cutoff of PIV was determined using the maximally selected rank statistics method. Multivariable Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses were performed to develop two nomograms (Model A and Model B) that predict disease-free survival (DFS). The concordance index, receiver operating characteristic curves, calibration curves, and decision curve analysis were used to evaluate the nomograms. A cohort composed of 50 patients who received radiotherapy or chemoradiotherapy (RT/CRT) alone was applied for generality testing of PIV and nomograms. Results: Patients with higher PIV (≥123.3) experienced a worse DFS (HR, 5.01; 95% CI, 3.25-7.72; p<0.0001) and overall survival (OS) (HR, 5.23; 95% CI, 3.34-8.18; p<0.0001) compared to patients with lower PIV (<123.3) in the development cohort. Predictors of Model A included age, TNM stage, neutrophil-to-lymphocyte ratio (NLR), and PIV, and that of Model B included TNM stage, lymphocyte-to-monocyte ratio (LMR), and PIV. In comparison with TNM stage alone, the two nomograms demonstrated good calibration and discrimination and showed satisfactory clinical utility in internal validation. The generality testing results showed that higher PIV was also associated with worse survival outcomes in the RT/CRT cohort and the possibility that the two nomograms may have a universal applicability for patients with different treatments. Conclusions: The nomograms based on PIV, a simple but useful indicator, can provide prognosis prediction of individual HNSCC patients after radical surgery and may be broadly applicated for patients after RT/CRT alone.
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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.
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Neoplasias Colorrectales , Lipoproteínas HDL , Monocitos , Nomogramas , Humanos , Masculino , Femenino , Neoplasias Colorrectales/mortalidad , Neoplasias Colorrectales/cirugía , Neoplasias Colorrectales/sangre , Neoplasias Colorrectales/patología , Neoplasias Colorrectales/inmunología , Estudios Retrospectivos , Persona de Mediana Edad , Anciano , Lipoproteínas HDL/sangre , Pronóstico , Inflamación/sangre , Periodo Preoperatorio , Estadificación de Neoplasias , Adulto , Modelos de Riesgos ProporcionalesRESUMEN
PURPOSE: This study aimed to further evaluate the potential value of Pan-Immune-Inflammation Value (PIV) as a prognostic marker in patients with laryngeal and pharyngeal tumors. METHODS: A total of 545 patients with laryngeal and pharyngeal tumors who underwent surgery at Qilu Hospital of Shandong University were included. We determined the optimal cutoff of PIV and divided the patients into two groups. The relationship between PIV and clinicopathological features was explored by the chi-square test and the Mann-Whitney U test. Survival analysis and Cox regression analysis were used to evaluate the relationship between PIV and overall survival (OS) and disease-free survival (DFS). We also compared the prognostic predictive value of PIV with other inflammation-related markers. Finally, we developed a simple scoring prediction model based on several independent prognostic parameters. RESULTS: We found that PIV was statistically associated with clinicopathological features such as tumor stage (p < 0.001), node stage (p = 0.001), postoperative chemotherapy (p = 0.026), and vascular thrombosis (p = 0.027). Survival analysis demonstrated a significant correlation between elevated PIV and reduced OS and DFS (p < 0.0001). Multivariate Cox regression analysis further confirmed PIV as a prognostic indicator (HR 2.507; 95% CI 1.343-4.681; p = 0.004), which is superior to SII, NLR, MLR and PLR. Three of the independent prognostic factors screened by multivariate Cox regression analysis were selected to be used to create a scoring system with a concordance index of 0.756. CONCLUSIONS: Elevated PIV is associated with poor prognosis in patients with laryngeal and pharyngeal tumors, suggesting that PIV may be an important adjunctive indicator for assessing patient prognosis. REGISTRATION INFORMATION: Registration number: KYLL-202307-001, date: July 2023.