The Association between the Pan-Immune-Inflammation Value and Cancer Prognosis: A Systematic Review and Meta-Analysis

Pan-immune-inflammation value and survival in patients with breast cancer from a Peruvian reference hospital

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.

Comparison of Inflammatory Marker Scoring Systems and Conventional Inflammatory Markers in Patients over 65 Years of Age Admitted to the Intensive Care Unit: A Multicenter, Retrospective, Cohort Study

Background: The aim of the current study is to evaluate the effects of inflammation markers on infection and mortality in patients over 65 years of age monitored in the intensive care unit (ICU). In this study, we attempted to determine the significance of the pan-immune-inflammation value (PIV); the neutrophil-lymphocyte ratio (NLR); the platelet-lymphocyte ratio (PLR); the monocyte-lymphocyte ratio (MLR); the systemic immune-inflammatory index (SII); the systemic immune response index (SIRI); multi-inflammatory indices (MIIs) 1, 2, and 3; and the CRP/albumin ratio (a new biomarker) as prognostic and mortality markers in patients over 65 years of age being monitored in the ICU. Methods: This multicenter, retrospective, cohort study was conducted on patients aged 65 and over who were admitted to two tertiary-level ICUs. Patients with cirrhosis, bone marrow transplantation, hematologic malignancy, steroid intake, current chemotherapy treatment, and neutropenia upon admission to the ICU were excluded from this study. Results: A total of 333 patients were included in this study. The group's 28-day mortality was found to be 31.8%. When each inflammatory marker associated with 28-day mortality was examined, the CRP/albumin ratio was found to be a better indicator than both the NLR and the SIRI, and the results were statistically significant (AUC: 0.665, 95% CI: 0.604-0.726, and p < 0.001). The NLR showed moderate discriminative ability in distinguishing mortality risk (AUC: 0.593, 95% CI: 0.526-0.660, and p = 0.006). Although the SIRI was lower than the NLR, it produced a statistically significant result (AUC: 0.580, 95% CI: 0.514-0.646, and p = 0.019). The CRP/albumin ratio was the most effective inflammatory marker in predicting mortality risk in older patients admitted to the ICU. Conclusions: It is important to monitor inflammatory markers (especially CRP/albumin ratio, NLR, SIRI, and MII 1-2-3) in older patients admitted to the ICU in order to accurately predict 28-day mortality. In the current study, the effects of PIV, MLR, PLR, and SII on the prediction of 28-day mortality in older ICU patients could not be demonstrated. We believe that more clinical studies are needed to determine the effects of PIV, MLR, PLR, and SII on short- and long-term prognoses and survival in older ICU patients.

Association between admission pan-immune-inflammation value and short-term mortality in septic patients: a retrospective cohort study

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.

The Construction of a Nomogram Using the Pan-Immune-Inflammation Value Combined with a PILE Score for Immunotherapy Prediction Prognosis in Advanced NSCLC

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.

Fibrinogen-to-albumin ratio (FAR) is the best biomarker for the overall survival of patients with non-small-cell lung cancer

Objective

The inflammatory response and the nutritional status are associated with overall survival (OS) in patients with non-small cell lung cancer (NSCLC), but it is unclear which biomarkers are better suited to predict prognosis. This study sought to determine which of the commonly existing inflammatory and nutritional indicators best predicted the OS.

Methods

This study included 15 compound indicators based on inflammation or nutrition, with cutoff points obtained through the receiver operating characteristic (ROC) curve. Univariate and multivariate Cox proportional risk models were used to evaluate the relationship between these predictors and OS. Kaplan-Meier curves were used for survival analysis, and log-rank tests were used to compare differences between groups. The C-index was calculated to evaluate the predictive ability of the different indicators.

Results

The study included 899 patients with NSCLC. In the univariate analysis, all 15 measures were significantly associated with the OS of patients (all p < 0.05). The results of the C-index analysis showed that the fibrinogen-to-albumin ratio (FAR), the systemic immune-inflammation index (SII), and the albumin-to-alkaline phosphatase ratio (AAPR) were the three indices with the best predictive performance. Among them, FAR (C-index = 0.639) had the best predictive power for OS in patients with NSCLC. In the different subgroups, FAR had the highest C-index in male, non-smoking, adenocarcinoma, and stage II patients. The C-index of the platelet-to-lymphocyte ratio (PLR) in female patients was the highest. SII was the highest in smokers, in those aged <65 and ≥65 years, and in stage III patients. The C-index of AAPR was the highest in non-adenocarcinomas. The C-index of the pan-immune-inflammation value (PIV) was the highest in stage I patients. In the multivariate Cox regression analysis, among FAR, SII, and AAPR, only FAR was an independent predictor of OS in patients with NSCLC. A high FAR was associated with a higher risk of death in patients with NSCLC (HR = 1.601, 95% CI = 1.028-2.495). In order to further evaluate the potential prognostic value of FAR, SII, and AAPR in patients with different stages, Cox regression analysis was performed for those with stage I-II and stage III NSCLC. The results showed that FAR was an independent prognostic factor for OS in patients with stage I-II NSCLC.

Conclusion

For all patients with NSCLC, the prognostic power of FAR was superior to that of other inflammatory and nutritional indicators.

Prognostic Significance of Pan-Immune-Inflammation Value in Patients with HER2-Positive Metastatic Breast Cancer Treated with Trastuzumab Emtansine

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.

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.

Pan‑immune‑inflammation value as a novel prognostic biomarker in nasopharyngeal carcinoma

The pan-immune-inflammation-value (PIV) is a comprehensive biomarker that integrates different peripheral blood cell subsets. The present study aimed to evaluate the prognostic ability of PIV in patients with nasopharyngeal carcinoma (NPC) undergoing chemoradiotherapy. PIV was assessed using the following equation: (Neutrophil count × platelet count × monocyte count)/lymphocyte count. The Kaplan-Meier method and Cox hazards regression models were used for survival analyses. The optimal cut-off values for PIV and systemic immune-inflammation index (SII) were determined using receiver operating characteristic analysis to be 428.0 and 1032.7, respectively. A total of 319 patients were recruited. Patients with a low baseline PIV (≤428.0) accounted for 69.9% (n=223) and patients with a high baseline PIV (>428.0) accounted for 30.1% (n=96). Compared with patients with low PIV, patients with a high PIV had significantly worse 5-year progression-free survival [PFS; 66.8 vs. 77.1%; hazard ratio (HR), 1.97; 95% confidence interval (CI), 1.22-3.23); P=0.005] and 5-year overall survival (OS; 68.7 vs. 86.9%, HR, 2.71; 95% CI, 1.45-5.03; P=0.001). PIV was also a significant independent prognostic indicator for OS (HR, 2.19; 95% CI, 1.16-4.12; P=0.016) and PFS (HR, 1.86; 95% CI, 1.14-3.04; P=0.013) and outperformed the SII in multivariate analysis. In conclusion, the PIV was a powerful predictor of survival outcomes and outperformed the SII in patients with NPC treated with chemoradiotherapy. Prospective validation of the PIV should be performed to better stratify radical treatment of patients with NPC.

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 the Royal Marsden Hospital (RMH) Score in Patients with Cancer: A Systematic Review and Meta-Analysis

BACKGROUND

Cancer remains a leading cause of death globally, necessitating the identification of prognostic biomarkers to guide treatment decisions. The Royal Marsden Hospital (RMH) score, based on readily available blood tests and clinical features, has emerged as a prognostic tool, although its performance across variable clinical scenarios is not thoroughly delineated. Therefore, we aimed to systematically assess the association between RMH score and survival in cancer patients.

METHODS

We conducted a systematic literature search across Pubmed, Scopus, and Web of Science databases for studies published up to 15 February 2024. We performed a meta-analysis with the generic inverse variance method with a random-effects model and reported hazard ratios (HR) with 95% confidence intervals (CI).

RESULTS

Nineteen studies encompassing 127,230 patients were included. A higher RMH score was significantly associated with worse overall survival (OS) (HR: 2.09, 95% CI: 1.87-2.33, p < 0.001) and progression-free survival (PFS) (HR: 1.80, 95% CI: 1.48-2.18, p < 0.001). This association was consistent across various subgroups, including study population (clinical trial vs. real-world cohort), geographic region, and tumor type.

CONCLUSION

This meta-analysis, including over a hundred thousand patients, demonstrates a negative association between a higher RMH score and survival in cancer patients. The RMH score holds promise as a readily available prognostic tool across diverse cancer types and clinical settings. Future research should focus on validating and refining this score to aid clinical decision-making.

Could Pan-Immune-Inflammation Value be a Marker for the Diagnosis of Coronary Slow Flow Phenomenon?

Inflammation plays a key role in the pathogenesis of the coronary slow flow phenomenon (CSFP). The newly developed inflammatory marker, pan-immune-inflammation value (PIV), is associated with adverse cardiovascular events. This study investigated the predictive value of PIV for diagnosing CSFP in comparison to other inflammation-based markers. A total of 214 patients, 109 in the CSFP group and 105 in the normal coronary flow (NCF) group, were retrospectively included in the study. Coronary flow was calculated using the Thrombolysis in Myocardial Infarction frame count method. In addition to PIV, other inflammatory markers such as neutrophil-lymphocyte ratio, platelet-lymphocyte ratio (PLR), and systemic immune-inflammation index (SII) were calculated for the patients. The average age of patients was 50.3 ± 8.4, with a male ratio of 55.1%. Compared to the NCF group, patients in the CSFP group had higher levels of hyperlipidemia, glucose, triglyceride, NLR, PLR, SII, and PIV, while their high-density lipoprotein cholesterol (HDL-C), was lower (p < 0.05). Logistic regression analysis demonstrated that HDL-C, glucose, triglyceride, and PIV were independent predictor factors for CSFP (p < 0.05). PIV is a strong and independent predictor factor for CSFP and superior in predicting CSFP compared to other inflammatory markers.

High Monocyte-to-Lymphocyte Ratio is Associated with Obstructive Sleep Apnea Hypopnea Syndrome

Objective

This study aims to explore the correlation between serum monocyte-to-lymphocyte ratio (MLR) and other inflammatory parameters with the occurrence of obstructive sleep apnea-hypopnea syndrome (OSAHS) in patients.

Methods

This study included 310 patients who underwent polysomnography monitoring at our hospital between January 2021 and January 2023. Routine blood inflammatory parameters and polysomnography (PSG) results were also evaluated. The differences in inflammatory markers between the OSAHS and normal groups were compared, and OSAHS independent related factors were screened.

Results

The MLR of OSAHS group was significantly higher than that of control group, and the difference was statistically significant. Multivariate logistic regression analysis suggested that MLR is an independent risk factor for OSAHS.

Conclusion

High MLR was correlated with OSAHS. The diagnostic value of MLR was better than that of the other inflammatory parameters.

Association between immune-inflammatory indexes and lower urinary tract symptoms: an analysis of cross-sectional data from the US National Health and Nutrition Examination Survey (2005-2008)

OBJECTIVE

This study aimed to systematically investigate the relationship between immune-inflammatory indexes with lower urinary tract symptoms (LUTSs).

DESIGN

Cross-sectional study.

SETTING

National Health and Nutrition Examination Survey (NHANES) (2005-2008).

PARTICIPANTS

A total of 2709 men with complete information for immune-inflammatory indexes and LUTSs were included from NHANES 2005-2008.

OUTCOMES AND ANALYSES

Automated haematology analysing devices are used to measure blood cell counts, and LUTSs were presented by standard questionnaires. Non-linear and logistic regression analyses were used to estimate their association after adjustment for confounders.

RESULTS

Multivariate logistic regression showed that pan-immune-inflammation value (OR (95% CI)=1.60 (1.14 to 2.23)), systemic inflammation response index (SIRI) (OR (95% CI)=1.82 (1.21 to 2.73)), neutrophil/lymphocyte ratio (NLR) (OR (95% CI)=1.81 (1.31 to 2.49)), derived NLR (dNLR) (OR (95% CI)=1.91 (1.35 to 2.70)) and C reactive protein (CRP) (OR (95% CI)=1.71 (1.05 to 2.79)) was positively associated with LUTS. Additionally, composite immune-inflammation markers exhibited a stronger association with LUTS than any single index, with the ORs for high SIRI+high CRP, high NLR+high CRP and high dNLR+high CRP being 2.26, 2.44 and 2.16, respectively (all p<0.05). Furthermore, subgroup analyses revealed that age, smoking status and hypertension have different effects on the relationship between immune-inflammatory markers and LUTS.

CONCLUSIONS

This study indicated that high levels of immune-inflammatory markers were associated with an increased risk of clinical LUTS. The combination of CRP with SIRI, NLR and dNLR, respectively, showed a stronger positive correlation with clinical LUTS compared with any single index.

Prognostic capacity of PIV (pan-immune-inflammation value) in patients with head and neck squamous cell carcinoma

INTRODUCTION

The pan-immune-inflammation value (PIV), an index that results from the following ratio: (neutrophils × monocytes × platelets)/lymphocytes, has been proposed as a prognostic biomarker in different tumour models. The aim of this study is to analyse the prognostic capacity of PIV in patients with head and neck squamous cell carcinoma (HNSCC).

PATIENTS AND METHODS

Retrospective study of 1187 patients with HNSCC treated at our centre between 2000-2017. PIV value was obtained from an analysis performed within 3 weeks prior to the start of treatment.

RESULTS

PIV value was significantly associated with toxic consumption (0.001), tumour location (0.0001), tumour extension (0.0001), and histological grade (0.016). Four categories were defined based on PIV value using a recursive partitioning analysis: category I: PIV < 136.3 (n = 118, 9.9%), category II: PIV 136.3-451.1 (n = 594, 50.0%), category III: PIV 451.1-1,141.2 (n = 357, 30.1%), and category IV: PIV > 1141.2 (n = 118, 9.9%). A significant and ordered decrease in disease-specific survival was observed as the PIV category increased. This decrease in survival was independent of the type of treatment, tumour extension, or location of the primary tumour. The PIV category was and independent prognostic factor of disease-specific survival in a multivariable study.

CONCLUSIONS

PIV is a prognostic biomarker in patients with HNSCC.

The relationship between disease activity with pan-immune-inflammatory value and systemic immune-inflammation index in rheumatoid arthritis

Rheumatoid arthritis (RA) is a chronic, systemic inflammatory disease. Immune system cells have an important role in RA. Our aim was to investigate the relationship between disease activity, systemic immune-inflammation index (SII), and pan-immune-inflammation value (PIV) levels in RA patients. We planned to investigate whether these 2 measurements have an advantage over each other. About 67 patients diagnosed with RA and 49 healthy controls included in this study. RA was diagnosed based on 2010 ACR classification criteria. In this cross-sectional study, peripheral blood tests, C-reactive protein (CRP), hemogram, and erythrocyte sedimentation rate levels were noted after the physical examination of all participants. PIV was calculated with the formula: (neutrophil count × platelet count × monocyte count) / lymphocyte count. SII was calculated as follows: (neutrophil count × monocytes count) / lymphocyte count. The disease activity score 28 (DAS28) were noted in patients with RA. CRP values of active RA group were significantly higher than remission RA and control groups (P < .001), control and remission RA groups were similar (P = .86). PIV and SII are significantly higher in active RA than remission RA and control (P < .001, P < .001) higher in remission RA than control (P < .001, P < .001). Receiver operating characteristic curve analysis in predicting remission compared to the control group, CRP was not significant, PIV and SII was significant and PIV has higher sensitivity and sensitivity, a PIV value of > 217.31 have sensitivity 75.0% and specificity 85.7%. CRP, PIV, and SII are statistically significant in predicting active RA compared to the remission RA and control group. Our findings show that PIV, and SII are easy, inexpensive and reliable markers predicting remission in RA patients. CRP was not significant compared to remission RA and control group, PIV and SII was significant and PIV has higher sensitivity and specificity than SII in the remission group in RA. Patients with high disease activity, PIV, SII, and CRP levels were effective in showing disease activity compared to RA remission group and healthy controls.

The association between inflammation-related biomarkers and the subtypes of cancer-related cognitive impairment in colorectal cancer patients: A latent profile analysis

PURPOSE

Cancer-related cognitive impairment (CRCI) has garnered considerable attention, yet limited research has delved into nuanced distinctions among varying degrees of CRCI in colorectal cancer survivors. This study aimed to identify distinct subgroups based on the patterns of CRCI, assess the heterogeneity among different subgroups, and investigate the potential correlations between the subgroups of CRCI and inflammation-related biomarkers.

METHODS

268 colorectal cancer patients were enrolled in this cross-sectional study, followed by the Functional Assessment of Cancer Therapy-Cognitive Function. The determination of CRCI subgroups was accomplished by the latent profile analysis (LPA). The effects of inflammation-related biomarkers on CRCI were examined using the binary logistic regression analysis. The receiver operating characteristic (ROC) curves assessed the diagnostic efficacy of inflammation-related biomarkers.

RESULTS

Two latent profiles were identified: CRCI (n = 64, 23.88%) and non-CRCI (n = 204, 76.12%). Independent factors for CRCI in colorectal cancer patients were SIRI (OR = 3.248, 95%CI [1.197-8.807], P = 0.021) and ALI (OR = 0.962, 95%CI [0.937-0.989], P = 0.005). The areas under the curve (AUCs) for SIRI and ALI in predicting CRCI were 0.781 and 0.774, with the optimal cut-off values being 0.70 and 37.04, respectively.

CONCLUSIONS

Colorectal cancer patients exhibited divergent cognitive performance profiles, categorized into two subgroups based on LPA. SIRI and ALI were identified as independent factors for CRCI, demonstrating strong diagnostic accuracy. These two inflammation-related biomarkers may potentially be novel indicators to identify and manage the development of CRCI among colorectal cancer patients.

Saliva as a potential non-invasive liquid biopsy for early and easy diagnosis/prognosis of head and neck cancer

Head and neck squamous cell carcinomas (HNSCCs) are the most devastating diseases in India and southeast Asia. It is a preventable and curable disease if detected early. Tobacco and alcohol consumption are the two major risk-factors but infection of high-risk HPVs are also associated with development of predominantly oral and oropharyngeal carcinomas. Interestingly, unlike cervical cancer, HPV-induced HNSCCs show good prognosis and better survival in contrast, majority of tobacco-associated HPV-ve HNSCCs are highly aggressive with poor clinical outcome. Biomarker analysis in circulatory body-fluids for early cancer diagnosis, prognosis and treatment monitoring are becoming important in clinical practice. Early diagnosis using non-invasive saliva for oral or other diseases plays an important role in successful treatment and better prognosis. Saliva mirrors the body's state of health as it comes into direct contact with oral lesions and needs no trained manpower to collect, making it a suitable bio-fluid of choice for screening. Saliva can be used to detect not only virus, bacteria and other biomarkers but variety of molecular and genetic markers for an early detection, treatment and monitoring cancer and other diseases. The performance of saliva-based diagnostics are reported to be highly (≥95 %) sensitive and specific indicating the test's ability to correctly identify true positive or negative cases. This review focuses on the potentials of saliva in the early detection of not only HPV or other pathogens but also identification of highly reliable gene mutations, oral-microbiomes, metabolites, salivary cytokines, non-coding RNAs and exosomal miRNAs. It also discusses the importance of saliva as a reliable, cost-effective and an easy alternative to invasive procedures.

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.

A Novel Prognostic Model Using Pan-Immune-Inflammation Value and Programmed Death Ligand 1 in Patients with Recurrent or Metastatic Head and Neck Squamous Cell Carcinoma Receiving Immune Checkpoint Inhibitors: A Retrospective Multicenter Analysis

BACKGROUND

Little is known regarding the prognostication of the Pan-Immune-Inflammation Value (PIV) in patients with recurrent or metastatic head and neck squamous cell carcinoma (R/M HNSCC).

OBJECTIVES

This study aimed to investigate the prognostic role of PIV in patients with R/M HNSCC receiving immune checkpoint inhibitors (ICI).

PATIENTS AND METHODS

Patients who were diagnosed to have R/M HNSCC and treated with ICI were reviewed retrospectively. The cutoff value of PIV was set at the median. Patients were stratified into high PIV and low PIV. Kaplan-Meier curves were estimated for progression-free survival (PFS) and overall survival (OS).

RESULTS

A total of 192 patients were included in our study for oncologic outcomes evaluation. For the total population, the median PFS was 5.5 months and OS was 18.2 months. After stratification by PIV, median PFS was 11.7 months in the low PIV and 2.8 months in the high PIV groups (p < 0.001). The median OS was 21.8 months in the low PIV and 11.5 months in the high PIV groups (p < 0.001). Multivariate analysis demonstrated that PIV and PD-L1 were independent predictors associated with survival. A prognostic model using both PIV and PD-L1 was constructed. The median PFS was 12.2, 6.4, and 3.0 months for patients with risk scores of 0, 1, and 2, respectively (p < 0.001). The median OS was 23.7, 18.1, and 11.4 months for patients with risk scores of 0, 1, and 2, respectively (p < 0.001).

CONCLUSIONS

PIV is a prognostic biomarker in patients with R/M HNSCC treated with ICI. A prognostic model using PIV and PD-L1 could provide outcome prediction and risk stratification.

Pretreatment Pan-Immune-Inflammation Value (PIV) in Predicting Therapeutic Response and Clinical Outcomes of Neoadjuvant Immunochemotherapy for Esophageal Squamous Cell Carcinoma

PURPOSE

The pan-immune-inflammation value (PIV), which reflects the balance between the host immune and inflammatory status, is a readily available index for evaluating cancer outcomes. Until now, however, no study has demonstrated the clinical response of PIV to neoadjuvant immunochemotherapy (NICT) in esophageal squamous cell carcinoma (ESCC).

METHODS

This retrospective study included 218 patients with ESCC who underwent NICT. The relationship between PIV and therapeutic response (pathological complete response [PCR]) and clinical outcomes (overall survival [OS] and disease-free survival [DFS]) was examined. Cox proportional, hazard-regression analyses and the Kaplan-Meier method were used for survival analyses. Recursive partitioning analysis (RPA) was used to establish a novel risk stratification model.

RESULTS

Sixty-six patients (30.3%) achieved PCR after NICT. Using PCR as the endpoint of interest, patients were compared in groups based on the optimal threshold. PIV was closely related to PCR (odds ratio [OR] 0.311, 95% confidence interval [CI] 0.140-0.690, P = 0.004). Compared with patients in the low PIV cohort, patients with high PIV had worse 3-year OS (58.7% vs. 83.6%, P < 0.001) and DFS (51.9% vs. 79.1%, P < 0.001). PIV was an independent predictor of OS (hazard ratio [HR] 2.364, 95% CI 1.183-4.724, P = 0.015) and DFS (HR 1.729, 95% CI 1.026-2.913, P = 0.040). Three risk groups with varied DFS and OS were staged by using an RPA method, and the prognostication accuracy was considerably improved.

CONCLUSIONS

Pretreatment PIV can predict the therapeutic efficacy of NICT for ESCC. Because of better prognostic stratification, pretreatment PIV is a novel, sensitive, and effective indicator in ESCC receiving NICT. The prognostic results of PIV need to be verified in additional prospective studies.

High pre-chemoradiotherapy pan-immune-inflammation value levels predict worse outcomes in patients with stage IIIB/C non-small-cell lung cancer

BACKGROUND AND OBJECTIVES

We explored the prognostic usefulness of the pan-immune-inflammation value (PIV) in patients with stage IIIB/C non-small-cell lung cancer (NSCLC) who underwent concurrent chemoradiotherapy (CCRT).

METHODS AND PATIENTS

For all patients, the PIV was calculated using platelet (P), monocyte (M), neutrophil (N), and lymphocyte (L) measures obtained on the first day of CCRT: PIV = P × M × N ÷ L. Using receiver operating characteristic (ROC) curve analysis, we searched for the existence of an ideal cutoff that may partition patients into two groups with unique progression-free- (PFS) and overall survival (OS) results. The primary endpoint of this retrospective cohort research was to determine whether there were any significant relationships between pretreatment PIV measures and post-CCRT OS outcomes.

RESULTS

The present research included a total of 807 stage IIIB/C NSCLC patients. According to ROC curve analysis, the ideal PIV cutoff was 516 [area under the curve (AUC): 67.7%; sensitivity: 66.4%; specificity: 66.1%], which divided the whole cohort into two: low PIV (L-PIV: PIV < 516; N = 436) and high PIV (H-PIV: PIV ≥ 516; N = 371). The comparisons between the PIV groups indicated that either the median PFS (9.2 vs. 13.4 months; P < 0.001) or OS (16.7 vs. 32.7 months; P < 0.001) durations in the H-PIV group were substantially inferior to their L-PIV counterpart. Apart from the H-PIV (P < 0.001), the N3 nodal stage (P = 0.006), IIIC disease stage (P < 0.001), and receiving only one cycle of concurrent chemotherapy (P = 0.005) were also determined to be significant predictors of poor PFS (P < 0.05, for each) and OS (P < 0.05, for each) outcomes in univariate analysis. The multivariate analysis findings revealed that all four variables had independent negative impacts on PFS (P < 0.05, for each) and OS (P < 0.05, for each).

CONCLUSIONS

The findings of this hypothesis-generating retrospective analysis claimed that the novel PIV was an independent and steadfast predictor of PFS and OS in stage IIIB/C NSCLC patients.

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.

Peripheral blood inflammatory indexes in breast cancer: A review

Immune and inflammatory responses play an important role in tumorigenesis and metastasis. Inflammation is an important component of the tumor microenvironment, and the changes in inflammatory cells may affect the occurrence and development of tumors. Complete blood count at the time of diagnosis and treatment can reflect the inflammatory status within the tumor. Studies have shown that the number of certain inflammatory cells in peripheral blood and their ratios are important prognostic factors for many malignancies, including neutrophil, lymphocyte, monocyte, and platelet counts, as well as neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, lymphocyte-to-monocyte ratio, systemic immune-inflammation index, systemic inflammation response index and pan-immune-inflammation-value. The value of peripheral blood inflammation indexes in predicting the efficacy and prognosis of breast cancer neoadjuvant therapy is worth recognizing. This review details the application of peripheral blood inflammation indexes in the evaluation of efficacy and prediction of prognosis in neoadjuvant therapy for breast cancer, aiming to provide a more comprehensive reference for the comprehensive diagnosis and treatment of breast cancer.

Prognostic role of neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, systemic immune-inflammation index, and pan-immune-inflammation value in metastatic castration-resistant prostate cancer patients who underwent 177Lu-PSMA-617

This study is aimed to investigate the prognostic significance of inflammation indices, including neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), and pan-immune-inflammation value (PIV) in metastatic castration-resistant prostate cancer (mCRPC) patients who had received lutetium labeled prostate-specific membrane antigen (177Lu-PSMA-617) therapy. Sixty-one mCRPC patients who received 177Lu-PSMA-617 treatment and followed up in Kocaeli University were included. The relationship between overall survival (OS) and progression-free survival (PFS) and clinical and laboratory parameters was analyzed by multivariate analyses. The mean age was 69.8 ± 6.9 years. The mean follow-up time was 53.2 ± 24 months. The median OS was 14 (95% CI: 8.8-18.1) and the median PFS was 10.4 (95% CI: 4.7-17.2) months. NLR ≥ 2.7, PLR ≥ 134.27, SII ≥ 570.39, PIV ≥ 408.59 were considered as elevated levels. In the multivariate analysis for OS, baseline ECOG performance score (HR: 1.92, 95% CI: 1.01-3.65, P = .046), high albümin (HR: 0.36, 95% CI: 0.16-0.82, P = .015), primary resistant total prostate-specific-antigen (PSA) (HR: 4.37, 95% CI: 1.84-10.35, P = .001), high NLR (HR: 3.32, 95% CI: 1.66-6.65, P = .001), high MLR (HR: 2.53, 95% CI: 1.35-4.76, P = .004), high PLR (HR: 2.47, 95% CI: 1.23-4.96, P = .01), and high SII (HR: 2.17, 95% CI: 1.09-4.32, P = .027) were associated with shorter OS. However, PIV was not associated with survival (P = .69). No factor other than the primer-resistant PSA could be identified as having an impact on PFS (for the PSA, HR: 4.52, 95% CI: 1.89-10.76, P = .001). In this study, pretreatment NLR, MLR, PLR, and SII demonstrate as powerful independent prognostic indices predicting survival in patients with mCRPC receiving 177Lu-PSMA-617 therapy.

Is Systemic Immune-Inflammation Index a Real Non-Invasive Biomarker to Predict Oncological Outcomes in Patients Eligible for Radical Cystectomy?

Background and Objectives: To assess the potential prognostic role of the systemic immune-inflammation index (SII) in predicting oncological outcomes in a cohort of patients treated with radical cystectomy (RC). Materials and Methods: From 2016 to 2022, a retrospective monocentric study enrolled 193 patients who were divided into two groups based on their SII levels using the optimal cutoff determined by the Youden index. The SII was obtained from a preoperative blood test approximately one month before RC. Univariable and multivariable logistic regression analyses were conducted to investigate the capacity of SII to predict lymph node invasion (N), advanced pT stage (pT3/pT4), and locally advanced condition at the time of RC. Multivariable Cox regression models adjusted for preoperative and postoperative features were used to analyze the prognostic effect of SII on recurrence-free survival (RFS), cancer-specific survival (CSS), and overall survival (OS). Results: The optimal cutoff value of the SII was 640.27. An elevated SII was seen in 113 (58.5%) patients. Using the multivariable preoperative logistic regression models, an elevated SII was correlated with nodal invasion (N; p = 0.03), advanced pT stage (p = 0.04), and locally advanced disease (p = 0.005), with enhancement of AUCs for predicting locally advanced disease (p = 0.04). In multivariable Cox regression models that considered preoperative clinicopathologic factors, an elevated SII was linked to poorer RFS (p = 0.005) and OS (p = 0.01). Moreover, on multivariable Cox regression postoperative models, a high SII was linked to RFS (p = 0.004) and to OS (p = 0.01). Conclusions: In this monocentric retrospective study, higher preoperative SII values predicted worse oncological outcomes in patients with bladder cancer (BCa) who underwent RC.

Mean Platelet Volume to Lymphocyte Ratio: A New Biomarker Predicting Response in Patients with Solid Tumors Treated with Nivolumab

Introduction

Although immune checkpoint inhibitors (ICIs) are widely used in cancer treatment, identifying factors that predict treatment response remains a challenge in clinical practice. There is a need for biomarkers to identify patients who may not benefit from these treatments. It is crucial to identify a simple and cost-effective biomarker that can be easily incorporated into clinical practice. This study aims to investigate the mean platelet volume to lymphocyte ratio (MPVLR), as measured by a hemogram test, and median overall survival (mOS) in patients with cancer treated with nivolumab.

Methods

A total of 131 adult patients with metastatic cancer, including malignant melanoma (MM), renal cell carcinoma (RCC), non-small cell lung cancer (NSCLC), and head and neck cancer (HNC), were included in this study. Baseline demographics, ECOG (Eastern Cooperative Oncology Group) performance status, tumor type, and blood count parameters were recorded. Univariate and multivariate analyses were conducted to evaluate potential risk factors.

Results

The median age of the patients was 59.87 ± 11.97 years, and the median follow-up period was 20.20 months (IQR, 12.80-27.60). RCC (43.5%) and MM (25.9%) were the most common diagnoses. Patients with ECOG scores of 0-1 had a longer mOS than those with scores of 2-3 (mOS: 20.60 months [95% CI, 14.94-25.29] vs. 5.24 months [95% CI, 0-16.42], p < 0.001). Additionally, patients with lactate dehydrogenase (LDH) levels within the normal range had a longer mOS than those with high LDH levels (mOS: 24.54 months [95% CI, 14.13-34.96] vs. 13.10 months [95% CI, 4.49-21.72], p = 0.038). Patients with low MPVLR also had a longer mOS than those with high MPVLR (mOS: 33.70 months [95% CI, 25.99-41.42] vs. 11.07 months [95% CI, 6.89-15.24], p < 0.001). In the multivariate Cox regression analysis, high MPVLR, ECOG score of 2-3, and high LDH level were associated with shorter mOS (p < 0.001, p = 0.001, and p = 0.046, respectively).

Conclusion

This study demonstrates that MPVLR could serve as a novel biomarker for predicting response to nivolumab treatment. Incorporating MPVLR into clinical practice may aid in identifying patients who are less likely to benefit from the treatment.

Association between a four-parameter inflammatory index and all-cause mortality in critical ill patients with non-traumatic subarachnoid hemorrhage: a retrospective analysis of the MIMIC-IV database (2012-2019)

Background

Non-traumatic subarachnoid hemorrhage (SAH), primarily due to the rupture of intracranial aneurysms, contributes significantly to the global stroke population. A novel biomarker, pan-immune-inflammation value (PIV) or called the aggregate index of systemic inflammation (AISI), linked to progression-free survival and overall survival in non-small-cell lung cancer and mortality in Coronavirus Disease 2019 (COVID-19) patients, has surfaced recently. Its role in non-traumatic SAH patients, however, remains under-researched. This study aims to determine the relationship between PIV and all-cause mortality in non-traumatic SAH patients.

Methods

A retrospective analysis was conducted using data from the Medical Information Mart for Intensive Care (MIMIC-IV) database to examine the association between PIV and all-cause mortality in critically ill patients with non-traumatic SAH. PIV measurements were collected at Intensive Care Unit (ICU) admission, and several mortality measures were examined. To control for potential confounding effects, a 1:1 propensity score matching (PSM) method was applied. The optimal PIV cutoff value was identified as 1362.45 using X-tile software that is often used to calculate the optimal cut-off values in survival analysis and continuous data of medical or epidemiological research. The relationship between PIV and short- and long-term all-cause mortality was analyzed using a multivariate Cox proportional hazard regression model and Kaplan-Meier (K-M) survival curve analysis. Interaction and subgroup analyses were also carried out.

Results

The study included 774 non-traumatic SAH patients. After PSM, 241 pairs of score-matched patients were generated. The Cox proportional hazard model, adjusted for potential confounders, found a high PIV (≥ 1362.45) independently associated with 90-day all-cause mortality both pre- (hazard ratio [HR]: 1.67; 95% confidence intervals (CI): 1.05-2.65; P = 0.030) and post-PSM (HR: 1.58; 95% CI: 1.14-2.67; P = 0.042). K-M survival curves revealed lower 90-day survival rates in patients with PIV ≥ 1362.45 before (31.1% vs. 16.1%%, P < 0.001) and after PSM (68.9% vs. 80.9%, P < 0.001). Similarly, elevated PIV were associated with increased risk of ICU (pre-PSM: HR: 2.10; 95% CI: 1.12-3.95; P = 0.02; post-PSM: HR: 2.33; 95% CI: 1.11-4.91; P = 0.016), in-hospital (pre-PSM: HR: 1.91; 95% CI: 1.12-3.26; P = 0.018; post-PSM: 2.06; 95% CI: 1.10-3.84; P = 0.034), 30-day (pre-PSM: HR: 1.69; 95% CI: 1.01-2.82; P = 0.045; post-PSM: 1.66; 95% CI: 1.11-2.97; P = 0.047), and 1-year (pre-PSM: HR: 1.58; 95% CI: 1.04-2.40; P = 0.032; post-PSM: 1.56; 95% CI: 1.10-2.53; P = 0.044) all-cause mortality. The K-M survival curves confirmed lower survival rates in patients with higher PIV both pre- and post PSM for ICU (pre-PSM: 18.3% vs. 8.4%, P < 0.001; post-PSM:81.7 vs. 91.3%, P < 0.001), in-hospital (pre-PSM: 25.3% vs. 12.8%, P < 0.001; post-PSM: 75.1 vs. 88.0%, P < 0.001), 30-day (pre-PSM: 24.9% vs. 11.4%, P < 0.001; post-PSM:74.7 vs. 86.3%, P < 0.001), and 1-year (pre-PSM: 36.9% vs. 20.8%, P < 0.001; P = 0.02; post-PSM: 63.1 vs. 75.1%, P < 0.001) all-cause mortality. Stratified analyses indicated that the relationship between PIV and all-cause mortality varied across different subgroups.

Conclusion

In critically ill patients suffering from non-traumatic SAH, an elevated PIV upon admission correlated with a rise in all-cause mortality at various stages, including ICU, in-hospital, the 30-day, 90-day, and 1-year mortality, solidifying its position as an independent mortality risk determinant. This study represents an attempt to bridge the current knowledge gap and to provide a more nuanced understanding of the role of inflammation-based biomarkers in non-traumatic SAH. Nevertheless, to endorse the predictive value of PIV for prognosticating outcomes in non-traumatic SAH patients, additional prospective case-control studies are deemed necessary.

Blood-based biomarkers: diagnostic value in brain tumors (focus on gliomas)

Background

Brain tumors, especially gliomas, are known for high lethality. It is currently understood that the correlations of tumors with coagulation and inflammation have been gradually revealed.

Objective

This study aimed to explore the potential value of several reported peripheral blood parameters as comprehensively as possible, with preoperative diagnosis and identification of brain tumors (focus on gliomas).

Methods

Patients with central nervous system tumors (craniopharyngioma, ependymoma, spinal meningioma, acoustic neuroma, brain metastases, meningioma, and glioma) or primary trigeminal neuralgia admitted to our hospital were retrospectively analyzed. The results of the routine coagulation factor test, serum albumin test, and blood cell test in peripheral blood were recorded for each group of patients on admission. Neutrophil-lymphocyte ratio (NLR), derived NLR (dNLR), platelet-lymphocyte ratio (PLR), lymphocyte-monocyte ratio (LMR), prognostic nutritional index (PNI), the systemic immune-inflammation index (SII), pan-immune-inflammation value (PIV), and their pairings were calculated. Their ability to identify brain tumors and their correlation with glioma grade were analyzed.

Results

A total of 698 patients were included in this retrospective case-control study. Glioma patients had higher NLR, SII, and PIV but lower LMR. The NLR in the brain metastasis group was lower than that in the control, meningioma, and acoustic neuroma groups, but the SII and PIV were higher than those in the ependymoma group. Fibrinogen, white blood cell count, neutrophil count, NLR, SII, and PIV in the GBM group were higher than those in the control group. In all comparisons, NLR and NLR + dNLR showed the greatest accuracy, with areas under the curve (AUCs) of 0.7490 (0.6482-0.8498) and 0.7481 (0.6457-0.8505), respectively. PIV, dNLR + PIV, and LMR + PIV ranked second, with AUCs of 0.7200 (0.6551-0.7849), 0.7200 (0.6526-0.7874), 0.7204 (0.6530-0.7878) and 0.7206 (0.6536-0.7875), respectively.

Conclusion

NLR, PIV, and their combinations show high sensitivity and specificity in the diagnosis of brain tumors, especially gliomas. Overall, our results provide evidence for these convenient and reliable peripheral blood markers.

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.

Prognostic significance of the pretreatment pan-immune-inflammation value in cancer patients: an updated meta-analysis of 30 studies

Background

The pan-immune-inflammation value (PIV) has been reported as a promising prognostic biomarker in multiple cancers but still remains inconclusive. The objective of this study is to systematically investigate the association of the pretreatment PIV with survival outcomes in cancer patients, based on available literature.

Methods

Online databases including PubMed, Embase and the Web of Science were thoroughly searched for studies evaluating the prognostic role of the pretreatment PIV in cancers from the inception to June 2023. Hazard ratios (HRs) with 95% confidence intervals (CIs) were always assessed using a random-effects model. Statistical analyses were performed using Stata 12.0.

Results

Thirty studies were finally included after comprehensively study searching. In total, 8,799 cancer patients were enrolled in this meta-analysis. The pooled results demonstrated that patients in the high PIV group had a significantly poorer overall survival (HR = 2.07; 95%CI: 1.77-2.41; I2 = 73.0%) and progression-free survival (HR = 1.83; 95%CI: 1.37-2.45; I2 = 98.2%) than patients in the low PIV group. The prognostic significance of the PIV score on overall survival and progression-free survival was observed across various geographical regions, tumor stages and treatment strategies. Sensitivity analyses supported the stability of the above combined results.

Conclusion

This meta-analysis demonstrated that the pretreatment PIV could be a non-invasive and efficacious prognostic biomarker for cancer patients.

Clinical utility of preoperative pan-immune-inflammation value (PIV) for prognostication in patients with esophageal squamous cell carcinoma

BACKGROUND

Several researches have shown that pan-immune-inflammation value (PIV) is related to cancer prognosis in recent years. In esophageal squamous cell carcinoma (ESCC), nevertheless, the prognostic impact of PIV remains unclear. The present study sought to investigate the prognostic impact of preoperative PIV in ESCC with radical resection.

METHODS

The data of 294 ESCC patients who received radical resection were retrospectively analyzed. Based on analyzing the non-linear relationship between PIV and cancer-specific survival (CSS), the optimal cutoff value for PIV was calculated by the restricted cubic spline (RCS) model. Cox proportional hazards regression was carried out to identify the prognostic factors. A risk stratification model was established by recursive partitioning analysis (RPA). The performance of the RPA-based model was assessed by the decision curve analysis (DCA) and receiver operating characteristic (ROC).

RESULTS

The RCS visualized the non-linear relationship between PIV and CSS (P < 0.0001). Then patients were then divided into high and low groups based on the optimal threshold of 308.2. The 5-year CSS (17.7 % vs. 48.3 %, P < 0.001) was significantly worse in patients with high PIV than those in the low group. Subgroup analyses confirmed that patients with low PIV also achieved better 5-year survival at different pathological tumor node metastasis (pTNM) stages (pTNM I: P = 0.022; pTNM II: P = 0.001; pTNM III: P = 0.011). PIV served as an independent prognostic factor of CSS (hazard ratio = 1.983, P < 0.001). A new staging involving three risk groups with significantly different CSS was developed using RPA algorithms based on pTNM and PIV. Compared with the pTNM classification, the RPA-based model exhibited significantly superior performance for prognostication.

CONCLUSION

The present study confirmed the prognostic impact of PIV in ESCC who treated with radical resection. PIV was associated with the tumor stage and prognosis, which might be useful in the preoperative assessment of ESCC.

Inflammatory Index as a Predictor of Mortality in Elderly Patients With Intracapsular Femoral Neck Fracture

A femoral neck fracture is a major cause of mortality in the elderly population, and intracapsular femoral neck fractures (ICFNFs) are commonly treated with hemiarthroplasty. The 30-day mortality rate for elderly hip fracture patients ranges from 1.0% to 6.5%, and one-year mortality increases significantly to 37.3%. Identifying predictors of mortality in these patients is crucial for better management. Inflammatory indices, such as neutrophil-to-lymphocyte ratio (NLR), systemic immune-inflammation index (SII), and monocyte-to-lymphocyte ratio (MLR), have gained popularity for assessing mortality risk in various diseases. Several studies have demonstrated the value of these indices in predicting mortality after hip fracture. The pan-inflammatory immune value (PIV), which combines hematological parameters, has been shown to predict mortality in cancer patients. However, its role in predicting mortality in ICFNF patients treated with hemiarthroplasty has yet to be explored. This study aimed to assess the association of PIV, SII, NLR, and MLR with 30-day and one-year mortality in ICFNF patients. We also investigated the impact of surgical delay time (≤24h, 24-48h, ≥48h) on these inflammatory indices and mortality. Data from 522 patients with ICFNF treated with hemiarthroplasty were retrospectively collected. We observed 30-day and one-year mortality rates of 5.24% and 21.2%, respectively. Age, gender, and American Society of Anesthesiologists (ASA) score were identified as significant predictors of mortality. Preoperative PIV, SII, NLR, and MLR were significant predictors in the evaluation of early mortality. However, postoperatively, only NLR on the third day (NLR3rd) demonstrated statistical significance. Stepwise logistic regression further confirmed NLR3rd as the most effective predictor for early mortality. For mortality occurring between 30 to 365 days, NLR3rd remained statistically significant, albeit with diminished sensitivity. No other inflammatory index demonstrated significant predictive power for mortality during this later period. Our findings suggest different inflammatory indices may have varying predictive abilities depending on the mortality period. We recommend considering NLR3rd as a valuable and reliable predictor for early mortality in ICFNF patients treated with hemiarthroplasty. Respiratory system disease and preoperative chronic obstructive pulmonary disease (COPD) were identified as risk factors for mortality in our study, in line with previous research. In conclusion, our study highlights the potential of specific inflammatory indexes, particularly NLR3rd, in predicting mortality in elderly patients with ICFNFs treated with hemiarthroplasty. Further research is needed to validate these findings and optimize risk assessment in orthopedic practice.

Prognostic Performance of Inflammatory Biomarkers Based on Complete Blood Counts in COVID-19 Patients

With the end of the pandemic, COVID-19 has entered an endemic phase with expected seasonal spikes. Consequently, the implementation of easily accessible prognostic biomarkers for patients with COVID-19 remains an important area of research. In this monocentric study at a German tertiary care hospital, we determined the prognostic performance of different clinical and blood-based parameters in 412 COVID-19 patients. We evaluated the neutrophil-to-lymphocyte ratio (NLR), systemic immune-inflammation index (SII), pan-immune-inflammation value (PIV), and absolute eosinopenia (AEP, 0/µL) of COVID-19 patients (n = 412). The Siddiqui and Mehra staging proposal, the WHO clinical progression scale, and COVID-19-associated death were used as COVID-19 outcome measures. With respect to Siddiqi and Mehra staging, patient age of older than 75 years, high C-reactive protein (CRP), absolute eosinopenia (AEP), cardiovascular comorbidities, and high ferritin were significant independent predictors for severe COVID-19. When outcome was determined according to the WHO clinical progression scale, patient age of older than 75 years, high CRP, high LDH, AEP, high neutrophil-to-lymphocyte ratio (NLR), and the presence of pulmonal comorbidities were significant independent predictors for severe COVID-19. Finally, COVID-19-associated death was predicted independently by patient age of older than 75 years, high LDH, high NLR, and AEP. Eosinopenia (< 40/µL) was observed in 74.5% of patients, and AEP in almost 45%. In conclusion, the present real-world data indicate that the NLR is superior to more complex systemic immune-inflammation biomarkers (e.g., SII and PIV) in COVID-19 prognostication. A decreased eosinophil count emerged as a potential hallmark of COVID-19 infection, whereas AEP turned out to be an accessible independent biomarker for COVID-19 severity and mortality.

The Prognostic Value of the Novel Global Immune-Nutrition-Inflammation Index (GINI) in Stage IIIC Non-Small Cell Lung Cancer Patients Treated with Concurrent Chemoradiotherapy

BACKGROUND

We sought to determine the prognostic value of the newly developed Global Immune-Nutrition-Inflammation Index (GINI) in patients with stage IIIC non-small cell lung cancer (NSCLC) who underwent definitive concurrent chemoradiotherapy (CCRT).

METHODS

This study was conducted on a cohort of 802 newly diagnosed stage IIIC NSCLC patients who underwent CCRT. The novel GINI created first here was defined as follows: GINI = [C-reactive protein × Platelets × Monocytes × Neutrophils] ÷ [Albumin × Lymphocytes]. The receiver operating characteristic (ROC) curve analysis was used to determine the optimal pre-CCRT GINI cut-off value that substantially interacts with the locoregional progression-free (LRPFS), progression-free (PFS), and overall survival (OS).

RESULTS

The optimal pre-CCRT GINI cutoff was 1562 (AUC: 76.1%; sensitivity: 72.4%; specificity: 68.2%; Youden index: 0.406). Patients presenting with a GINI ≥ 1562 had substantially shorter median LRPFS (13.3 vs. 18.4 months; p < 0.001), PFS (10.2 vs. 14.3 months; p < 0.001), and OS (19.1 vs. 37.8 months; p < 0.001) durations than those with a GINI < 1562. Results of the multivariate analysis revealed that the pre-CCRT GINI ≥ 1562 (vs. <1562), T4 tumor (vs. T3), and receiving only 1 cycle of concurrent chemotherapy (vs. 2-3 cycles) were the factors independently associated with poorer LRPS (p < 0.05 for each), PFS (p < 0.05 for each), and OS (p < 0.05 for each).

CONCLUSION

The newly developed GINI index efficiently divided the stage IIIC NSCLSC patients into two subgroups with substantially different median and long-term survival outcomes.

Effect of Microsatellite Status and Pan-Immune-Inflammation Score on Pathological Response in Patients with Clinical Stage III Stomach Cancer Treated with Perioperative Chemotherapy

Background and Objective: This study evaluated the relationship between microsatellite status (MSI) and pan-immune-inflammation score (PIV) in tumor response to neoadjuvant chemotherapy (NAC) in patients with clinical stage III gastric cancer (cStage III GC). Materials and Methods: Microsatellite instability (MSI) status was evaluated based on pathology preparations. Pan-immune-inflammation score (PIV) was obtained from pre-treatment blood tests. The relationship of both parameters with pathological complete response (pCR) was evaluated. Results: A total of 104 patients were included in this study. All the patients were stage III GC patients receiving perioperative treatment. There were 13 patients in total who achieved a pCR response. While CNS was detected in 11 of the patients who achieved a pCR, the MSI status of the other two patients was unknown. No pCR was observed in any patient with MSI-H. According to the cut-off value for PIV, 25 (24%) patients were in the PIV-low (≤53.9) group, while 79 (76%) were in the PIV-high (>53.9) group. Based on univariate analysis, a higher PIV was associated with worse outcomes for pathological response, disease recurrence, and survival (p < 0.05). Conclusions: In patients with clinically stage III GC, the presence of MSI-H may predict no benefit from perioperative treatment. Conversely, a pre-treatment PIV score using specific cut-off values may provide a positive prediction of pathological response and survival.

Diagnostic Efficiency of Pan-Immune-Inflammation Value to Predict Prostate Cancer in Patients with Prostate-Specific Antigen between 4 and 20 ng/mL

INTRODUCTION

To evaluate the predictive value of the pan-immune-inflammation value (PIV) and other systemic inflammatory markers, including the neutrophil-to-lymphocyte ratio (NLR), derived neutrophil-to-lymphocyte ratio (dNLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR), and systemic immune-inflammation index (SII), for prostate cancer (PCa) and clinically significant prostate cancer (CSPCa) in patients with a prostate-specific antigen (PSA) value between 4 and 20 ng/mL.

PATIENTS AND METHODS

The clinical data of 319 eligible patients who underwent prostate biopsies in our hospital from August 2019 to June 2022 were retrospectively analyzed. CSPCa was defined as a "Gleason grade group of ≥2". A univariable logistic regression analysis and multivariable logistic regression analysis were conducted to analyze the association between the PIV, SII, MLR, and PCa/CSPCa. For the inflammatory indicators included in the multivariable logistic regression analysis, we constructed models by combining the separate inflammatory indicator and other significant predictors and compared the area under the curve (AUC). A nomogram based on the PIV for PCa was developed.

RESULTS

We included 148 PCa patients (including 127 CSPCa patients) and 171 non-PCa patients in total. The patients with PCa were older, had higher MLR, SII, PIV, and total PSA (TPSA) values, consumed more alcohol, and had lower free/total PSA (f/T) values than the other patients. Compared with the non-CSPCa group, the CSPCa group had higher BMI, MLR, PIV, TPSA values, consumed more alcohol, and had lower f/T values. The univariable regression analysis showed that drinking history, higher MLR, PIV, and TPSA values, and lower f/T values were independent predictors of PCa and CSPCa. The AUC of the PIV in the multivariable logistic regression model was higher than those of the MLR and SII. In addition, the diagnostic value of the PIV + PSA for PCa was better than the PSA value. However, the diagnostic value for CSPCa was not significantly different from that of using PSA alone, while the AUC of the PIV + PSA was higher than the individual indicator of the PSA value.

CONCLUSIONS

Our study suggests that for the patients who were diagnosed with PSA values between 4 and 20 ng/mL, the PIV and MLR are potential indicators for predicting PCa and CSPCa. In addition, our study indicates that the new inflammatory index PIV has clinical value in the diagnosis of PCa and CSPCa.

Discovering the Clinical and Prognostic Role of Pan-Immune-Inflammation Values on Oral Cavity Squamous Cell Carcinoma

A newly introduced pan-immune-inflammation value (PIV) was not evaluated for its role in oral cavity squamous cell carcinoma (OSCC). In this study, the PIV was calculated with the following equation (neutrophil count × platelet count × monocyte count)/lymphocyte count from the results of the automated hematology analyzers in 853 OSCC patients from 2005 to 2017. The optimal cutoff for the preoperative PIV was 268, as determined by a receiver operating characteristic curve. Significant differences were observed for alcohol consumption, smoking, pT status, pN status, overall pathological status, extranodal extension, cell differentiation, depth of invasion, and perineural invasion between higher and lower PIV patients (all p values < 0.05). Kaplan-Meier and univariate regression analyses indicated that higher PIV was associated with worse overall survival, disease-free survival, locoregional recurrence-free survival, and distant metastasis-free survival (all p values < 0.001). Multivariate analyses adjusted by various factors further demonstrated that PIV was an independent prognostic factor for overall and distant metastasis-free survival (p = 0.027, HR: 1.281 and p = 0.031, HR: 1.274, respectively). In conclusion, a higher PIV level was associated with poor clinicopathological factors in OSCC patients and could be used to predict poor posttreatment outcomes, especially for overall and distant metastasis-free survival.

Pan-Immune-Inflammatory Value Predicts the 3 Months Outcome in Acute Ischemic Stroke Patients after Intravenous Thrombolysis

BACKGROUND AND PURPOSE

Immune and inflammatory response plays a central role in the clinical outcomes of stroke. This study is aimed to explore the clinical significance of the new inflammation index named pan-immune-inflammation value (PIV) in patients with acute ischemic stroke (AIS) after intravenous thrombolysis therapy (IVT).

METHODS

Data were collected from 717 patients who received IVT at the First Affiliated Hospital of Soochow University. Baseline data were collected before intravenous thrombolysis. Multivariate logistic regression analysis was used to assess the association between PIV and 3 months clinical outcome after intravenous thrombolysis. We also used receiver operating characteristic (ROC) curves analysis to assess the discriminative ability of PIV, platelet to lymphocyte ratio (PLR), neutrophil to lymphocyte ratio (NLR), and systemic immune-inflammation index (SII) in predicting 3 months poor outcome.

RESULTS

Of 717 patients, 182 (25.4%) patients had poor outcomes at 3 months. Patients with 3 months of poor outcome had significantly higher PIV levels compared to those with favorable outcomes [316.32 (187.42-585.67) vs. 223.80 (131.76-394.97), p < 0.001)]. After adjusting for potential confounders, the risk of 3 months of poor outcome was significantly higher among patients whose PIV fell in the third quartile (244.21-434.49) and the fourth quartile (> 434.49) than those in the first quartile (< 139.93) (OR = 1.905, 95% CI: 1.040-3.489; OR = 2.229, 95%CI: 1.229-4.044). The area under the ROC curve of PIV to predict 3 months of poor outcome was 0.607 (95%CI: 0.560-0.654; p < 0.001). The optimal cut-off values of PIV were 283.84 (59% sensitivity and 62% specificity).

CONCLUSION

The higher levels of PIV were independently associated with 3 months of poor outcomes in AIS patients receiving IVT. PIV like other inflammatory factors (PLR, NLR, and SII), can also predict adverse outcomes after IVT in AIS patients.

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.

Prognostic value of pan-immune-inflammation value in colorectal cancer patients: A systematic review and meta-analysis

Background

The pan-immune-inflammation value (PIV) has been reported as a novel prognostic biomarker in multiple malignancies. The aim of this study is to investigate the prognostic value of the PIV in patients with colorectal cancer.

Methods

We comprehensively searched electronic databases including PubMed, Embase and Web of Science up to August 2022. The endpoints were survival outcomes. Hazard ratios (HRs) with 95% confidence intervals (CIs) for survival data were collected for analysis.

Results

Six studies including 1879 participants were included. A significant heterogeneity in the PIV cut-off value among studies was observed. The combined results indicated that patients in the high baseline PIV group had a worse overall survival (HR=2.09; 95%CI: 1.67-2.61; P<0.0001; I^{2 =} 7%) and progression-free survival (HR=1.82; 95%CI: 1.49-2.22; P<0.0001; I^{2 =} 15%). In addition, early PIV increase after treatment initiation was significantly associated with decreased overall survival (HR=1.79; 95%CI: 1.13-2.93; P=0.01; I^{2 =} 26%), and a trend toward poor progression-free survival (HR=2.00; 95%CI: 0.90-4.41; P=0.09; I^{2 =} 70%).

Conclusion

Based on existing evidence, the PIV could act as a valuable prognostic index in patients with colorectal cancer. However, the heterogeneity in the PIV cut-off value among studies should be considered when interpreting these findings.

The association between albumin levels and survival in patients treated with immune checkpoint inhibitors: A systematic review and meta-analysis

Background: The albumin levels may potentially be used as a prognostic biomarker in patients with cancertreated with immune checkpoint inhibitors (ICIs) due to its close relationship with nutritional and inflammatory status. However, the available data is limited with heterogeneous patient cohorts, sample sizes and variable cut-offs. Therefore, we conducted a systematic review and meta-analysis to evaluate the association between survival outcomes and albumin levels in patients treated with ICIs. Methods: We conducted a systematic review using the PubMed, Web of Science, and Embase databases to filter the published studies up to 1 June 2022. The meta-analyses were performed with the generic inverse-variance method with a random-effects model due to the high degree of heterogeneity. The primary outcome measure was hazard ratio (HR) with 95% confidence intervals (CI). The study protocol was registered with the PROSPERO registry (Registration Number: CRD42022337746). Results: Thirty-six studies encompassing 8406 cancer patients with advanced disease were included in the meta-analyses. Almost half of the studies were conducted in NSCLC cohorts (n = 15), and 3.5 gr/dL was the most frequently used albumin cut-off in the included studies (n = 20). Patients with lower albumin levels had a significantly increased risk of death (HR: 1.65, 95% CI: 1.52-1.80, p < 0.0001) than patients with higher albumin levels. Subgroup analyses for study location, sample size, tumor type and albumin cut-off were demonstrated consistent results. Furthermore, in the subgroup analysis of eight studies using albumin levels as a continuous prognostic factor, every 1 gr/dL decrease in albumin levels was associated with significantly increased risk of death by a factor of 10% (HR: 1.10, 95% CI: 1.05-1.16, p = 0.0002). Similar to analyses with overall survival, the patients with lower albumin levels had an increased risk of progression or death compared to patients with higher albumin levels (HR: 1.76, 95% CI: 1.40-2.21, p < 0.001). Conclusion: The available evidence demonstrates that albumin levels may be a prognostic biomarker in advanced cancer patients treated with ICIs. Further research is needed to delineate the role of albumin levels in patients treated with ICIs in the adjuvant setting, as well as the possible benefit of therapeutic approaches to improve hypoalbuminemia.

Low Pre-ChemoradiotherapyPan-Immune-Inflammation Value (PIV) Measures Predict Better Survival Outcomes in Locally Advanced Pancreatic Adenocarcinomas

Objective

This study sought to determine whether pretreatment pan-immune-inflammation value (PIV) could be used to predict prognosis in patients with locally advanced pancreatic adenocarcinoma (LA-PAC) following definitive concurrent chemoradiotherapy (C-CRT).

Methods

The outcomes of 178 LA-PAC patients who received definitive C-CRT were analyzed retrospectively. For all patients, the PIV was calculated using the peripheral blood platelet (P), monocyte (M), neutrophil (N), and lymphocyte (L) counts obtained on the first day of C-CRT: PIV=P×M×N÷L. The optimum cutoff values for PIV connected to progression-free (PFS) and overall survival (OS) results were sought using receiver operating characteristic (ROC) curve analysis. The OS and PFS differences between the PIV groups constituted the primary and secondary endpoints, respectively.

Results

ROC curve analysis indicated that the ideal PIV cutoff was 464 (AUC: 75.9%, sensitivity: 74.1%, specificity: 71.9%), which categorized patients into two groups based on PFS and OS results: low PIV (L-PIV; N = 69) and high PIV (H-PIV; N = 109). According to comparative survival analyses, patients in the L-PIV group had significantly longer median PFS (14.3 vs 7.3 months; HR: 3.04; P<0.001) and OS (25.9 vs 13.3 months; HR: 2.86; P<0.001) than those in the H-PIV group. Although none of the H-PIV patients could survive beyond 5 years, the estimated 5-year OS rate was 29.7% in the L-PIV cohort. In multivariate analyses, besides the L-PIV, N₀ nodal stage, and CA 19–9 ≤ 90 U/mL appeared to be the independent predictors of better PFS (P < 0.05 for each) and OS (P < 0.05 for each) results.

Conclusion

The present results indicated that pre-C-CRT L-PIV measures were associated with favorable median and long-term PFS and OS results in LA-PAC patients, suggesting that the PIV is a potent and independent novel prognostic biomarker.

Prognostic Potential of the Baseline Pan-Immune-Inflammation Value and Neutrophil/Lymphocyte Ratio in Stage I to III Melanoma Patients

Prognostic biomarkers derived from complete blood count (CBC) have received marked interest as an indirect measure of the inflammatory pressure in cancers such as metastatic melanoma. Here, we evaluated the novel pan-immune-inflammation value (PIV) and the frequently assessed neutrophil/lymphocyte ratio (NLR) in a large cohort of patients with cutaneous melanoma (CM) without distant metastases (stages I to III). PIV and NLR were calculated at CM diagnosis. Healthy controls were also included. We used the Kaplan-Meier method to estimate crude survival probabilities and used Cox proportional hazards regression for multiple adjustment of hazard ratios. We observed that higher PIV (HR: 1.72, 95% CI 1.14 to 2.58 and HR: 1.696, 95% CI 1.029 to 2.795, respectively) and NLR (HR: 1.70, 95% CI 1.10 to 2.62) values were associated with CM relapse and CM-specific death in the crude analysis. However, when adjusting for potential confounders, in particular age and tumor thickness, the total effect of PIV and NLR on CM-relapse-free (HR: 1.28, 95% CI 0.83 to 1.98 and HR: 1.26, 95% CI 0.80 to 1.98, respectively) and CM-specific survival (HR: 1.36, 95% CI 0.80 to 2.30 and HR: 1.37, 95% CI 0.80 to 2.33, respectively) was substantially reduced. However, both PIV and NLR were positively correlated with age and tumor thickness, which are important independent predictors for CM relapse and CM-specific death. In conclusion, in stage I to III CM patients PIV as well as NLR appear to be confounded by age and tumor thickness and probably have no potential to further improve the prediction of survival of stage I to III CM patients beyond standard prognostic factors.

The Association between Early Changes in Neutrophil-Lymphocyte Ratio and Survival in Patients Treated with Immunotherapy

Dynamic changes in the blood-based biomarkers could be used as a prognostic biomarker in patients treated with immune checkpoint inhibitors (ICIs), although the data are limited. We evaluated the association between the neutrophil−lymphocyte ratio (NLR) and early NLR changes with survival in ICI-treated patients. We retrospectively evaluated the data of 231 patients with advanced-stage cancer. We recorded baseline clinical characteristics, baseline NLR and fourth-week NLR changes, and survival data. A compound prognostic score, the NLR2-CEL score, was developed with the following parameters: baseline NLR (<5 vs. ≥5), ECOG status (0 vs. ≥1), Charlson Comorbidity Index (CCI, <9 vs. ≥9), LDH (N vs. ≥ULN), and fourth-week NLR change (10% or over NLR increase). In the multivariable analyses, higher NLR (HR: 1.743, p = 0.002), 10% or over NLR increase in the fourth week of treatment (HR: 1.807, p = 0.001), higher ECOG performance score (HR: 1.552, p = 0.006), higher LDH levels (HR: 1.454, p = 0.017), and higher CCI (HR: 1.400, p = 0.041) were associated with decreased OS. Compared to patients with the lowest scores, patients in the highest score group had significantly lower OS (HR: 7.967, 95% CI: 3.531−17.979, p < 0.001) and PFS. The composite score had moderate success for survival prediction, with an AUC of 0.702 (95% CI: 0.626−0.779, p < 0.001). We observed significantly lower survival in patients with higher baseline NLR values and increased NLR values under treatment.

Study of PD-1 Customization and Autoimmune T Cells for Advanced Colorectal Cancer with High MSI Expression

Objective

To evaluate the significance of PD-1 customization and autoimmune T-cell therapy for advanced colorectal cancer with high MSI expression.

Methods

One hundred and eight patients with advanced colorectal cancer with high MSI expression admitted to our hospital between August 2019 and January 2022 were divided into control and study groups, and PD-1 customization and autoimmune T-cell therapy were administered to the two groups, respectively. Trends in immune indexes, PD-1 exposure, and survival rates were studied in both groups.

Results

The treatment efficiency of the study group was 90.74%, which was higher than that of the control group (61.11%) (P < 0. 05); after treatment, the presence of CDl07a, perforin, and GranB cells was significantly higher in both groups compared with that before treatment, but the expression of PD-1 was more pronounced in the study group (P < 0. 05); that is, the expression of PD-1 in peripheral T lymphocytes in the study group compared with that of the control group was higher in patients with grade III-IV, and peripheral T lymphocytes were also higher in patients with grade III-IV compared with patients with grade I-II (P < 0. 05).

Conclusion

PD-1 customization combined with autoimmune T-cell therapy is a novel therapeutic modality that can substantially improve.