Pan-immune-inflammation Value and Prognosis in Patients With Esophageal Cancer

Pan-immune-inflammation value: a new prognostic index in operative laryngeal and pharyngeal carcinomas

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.

The Importance of Pan-Immune Inflammation Value (PIV) in Predicting Coronary Collateral Circulation in Stable Coronary Artery Patients

In this study, the correlation between pan-immune-inflammation value (PIV) and coronary collateral circulation (CCC) in patients with chronic coronary syndrome (CCS) was analyzed. The study included 663 patients with CCS who underwent coronary angiography and had coronary stenosis of ≥95% in at least one major coronary vessel. The participants were divided into two groups: good CCC (Rentrop score 2-3) and poor CCC (Rentrop score 0-1). PIV score was calculated as monocyte x platelet x neutrophil/lymphocyte count. When the patient groups who developed good and poor CCC were compared, neutrophil/lymphocyte ratio (NLR) (P < .001), C-reactive protein (CRP) levels, CRP/albumin ratio (CAR) (P < .001), systemic immune-inflammation index (SII) (P < .001), and PIV (P < .001) were higher in patients with poor CCC. In multivariate logistic regression analysis, age, SII, NLR, CRP, CAR, and PIV were found to be independent predictors of poor CCC (P < .001, for all). Receiver operating characteristic (ROC) analysis demonstrated that a cut-off value of 442.2 for PIV predicted poor CCC slightly better compared to other markers, with 76.8% sensitivity and 70.1% specificity (area under ROC curve = 0.808 (95% CI: 0.764-0.851), P < .001). These findings suggest that PIV can be used as an independent predictor of CCC development.

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.

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

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

Influence of systemic inflammatory indices on hospital stay and dialysis post-earthquake: A clinical study

Natural disasters pose significant challenges to medical response due to the surge of patients and emergent injuries. Amid such scenarios, where personnel for patient monitoring might be scarce, effective biomarkers are crucial for guiding treatment plans and predicting patient prognosis. We aimed to evaluate the correlation between systemic inflammatory indices and morbidity in earth-quake-induced crush injuries. Additionally, we assessed the potential of these indices as prognostic markers for adverse outcomes. We studied 140 patients with earthquake-related crush injuries (ECR) admitted between February and March 2023 and compared them to 200 healthy controls (CG) chosen using a simple random method. Using the complete blood count data upon admission, we computed and statistically compared indices including NLR (neutrophil lymphocyte ratio), PLR (platelet lymphocyte ratio), MLR (monocyte lymphocyte ratio), SII (systemic immune-inflammatory index), SIRI (systemic inflammatory response index), and PIV (pan-immune inflammation value). Regression analyses determined the prediction of hospitalization duration and dialysis necessity. PLR and MLR upon admission significantly predicted the length of hospital stay. MLR and SIRI were significant predictors for dialysis requirement, with Exp(B) values of 0.306 (p = 0.024) and 1.261 (p = 0.038), respectively. Systemic inflammatory indices can serve as valuable prognostic tools in disaster scenarios. Utilizing these indices can enhance patient management, effectively allocate resources, and potentially save lives in the aftermath of earthquakes.

The Role of Pan-Immune-Inflammation Value in Determining the Severity of Coronary Artery Disease in NSTEMI Patients

BACKGROUND

Even though medication and interventional therapy have improved the death rate for non-ST elevation myocardial infarction (NSTEMI) patients, these patients still have a substantial residual risk of cardiovascular events. Early identification of high-risk individuals is critical for improving prognosis, especially in this patient group. The focus of recent research has switched to finding new related indicators that can help distinguish high-risk patients. For this purpose, we examined the relationship between the pan-immune-inflammation value (PIV) and the severity of coronary artery disease (CAD) defined by the SYNTAX score (SxS) in NSTEMI patients.

METHODS

Based on the SxS, CAD patients were split into three groups. To evaluate the risk variables of CAD, multivariate logistic analysis was employed.

RESULTS

The PIV (odds ratio: 1.003; 95% CI: 1.001-1.005; p = 0.005) was found to be an independent predictor of a high SxS in the multivariate logistic regression analysis. Additionally, there was a positive association between the PIV and SxS (r: 0.68; p < 0.001). The PIV predicted the severe coronary lesion in the receiver-operating characteristic curve analysis with a sensitivity of 91% and specificity of 81.1%, using an appropriate cutoff value of 568.2.

CONCLUSIONS

In patients with non-STEMI, the PIV, a cheap and easily measured laboratory variable, was substantially correlated with a high SxS and the severity of CAD.

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

Introduction

Geriatric patients with metastatic renal cell carcinoma (mRCC) are underrepresented in clinical trials. Evaluation of the efficacy of the treatment and assignation of individuals to proper prognostic groups is an absolute necessity to guarantee them the best possible care.

Material and methods

A total of 138 geriatric patients with mRCC treated with first-line tyrosine kinase inhibitors (TKIs) at the Maria Skłodowska-Curie National Research Institute of Oncology were retrospectively analyzed to determine whether the body mass index (BMI) and pan-immune-inflammation value (PIV) are prognostic values for overall survival (OS) and progression-free survival (PFS) in this type of cancer. For this purpose, Cox's proportional hazard model was used.

Results

The median duration of follow-up for surviving patients was 46.6 (95% CI: 17.4-75.8) months. The median OS and PFS were respectively 33.8 months (95% CI: 23.8-47.8) and 19.1 months (95% CI: 15.0-23.3). BMI (p = 0.034) and PIV (p < 0.001) were statistically significantly associated with OS, and PIV (p = 0.001) was statistically significantly associated with PFS. The risk of death for patients from the high-PIV group (cut-off point: 548) was 3.4 times higher than for those with lower PIV values. The corresponding risk of progression for patients from the high-PIV group was 2.2 times higher. The G8 geriatric screening tool was not identified as a prognostic factor.

Conclusions

Lower PIV and obesity are associated with longer OS in geriatric mRCC patients treated with TKIs in the first line. These factors may be considered while making treatment decisions if further studies show the same results.

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.

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.

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.

Pan-Immune-Inflammation Index as a Biomarker for Rheumatoid Arthritis Progression and Diagnosis

Introduction Rheumatoid arthritis (RA) is a chronic autoimmune condition that causes systemic inflammation and affects multiple joints. It is characterized by joint warmth, swelling, pain, and the formation of invasive synovial tissue known as pannus, which contributes to cartilage and bone degradation. Pan-immune-inflammation value (PIV), a marker derived from complete blood count parameters, has shown promise in predicting prognosis in various cancer types and pediatric conditions associated with immune abnormalities. This study aims to explore the relationship between RA, characterized by chronic inflammation and immune system involvement, and PIV, potentially shedding light on novel insights into RA's clinical implications. Methods One hundred four participants, including 64 RA patients (both newly diagnosed and established cases) and 40 healthy controls, were included in the study. Exclusion criteria for RA patients included acute infection, cancer, diabetes, or chronic illness, while control participants were excluded for inflammatory disorders, active infection, diabetes, or malignancy. We assessed disease severity using Disease Activity Score 28 (DAS 28) and obtained complete blood count values, including neutrophil, lymphocyte, platelet, monocyte, and red cell distribution width. C-reactive peptide (CRP) and erythrocyte sedimentation rate were also added. Statistical analyses included correlation assessments, t-tests, Mann-Whitney U tests, and multivariate linear regression. A multiclass receiver operating characteristic analysis determined optimal PIV cut-off values for distinguishing control, remission, and active RA groups, with sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy, and odds ratios calculated. Results This study comprised a cohort of 104 participants, with a median age of 43.5±17.5. The Remission group was significantly younger than the Control group (p=0.006) but not compared to the Active RA group (p=0.393). CRP levels were significantly higher in the Active RA group (p<0.001). Neutrophil counts were highest in the Active RA group (p<0.001), as were monocyte counts. Lymphocyte counts were significantly lower in the Active RA group (p<0.001). There were no significant differences in sedimentation rate, hemoglobin, platelet count, and mean platelet volume. PIV was significantly elevated in the Active RA group (p<0.001) and higher in the Remission group than in the Control group (p=0.001). A PIV value of 353.48 exhibited 71.4% sensitivity, 86.2% specificity, 86.2% PPV, 71.4% NPV, and 78.13% test accuracy for distinguishing active rheumatoid arthritis (p<0.001). A PIV value exceeding 353.48 substantially increased the likelihood of a patient belonging to the active rheumatoid arthritis group, with a 14.62-fold higher probability. Furthermore, the study explored the relationship between clinical and laboratory variables and disease activity in RA patients, finding significant differences in PIV among DAS groups (p=0.025). Conclusions The PIV offers a notable advantage as its constituent parameters are routinely assessed in rheumatoid arthritis and involve cost-effective and straightforward tests. We demonstrated that PIV serves as a valuable marker for distinguishing between remission and active RA when compared to healthy individuals. Additionally, it proved to be an effective tool for assessing disease activity in patients with active rheumatoid arthritis.

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.

Pretreatment Pan-Immune-Inflammation Value Efficiently Predicts Survival Outcomes in Glioblastoma Multiforme Patients Receiving Radiotherapy and Temozolomide

Objectives

The purpose of this study was to determine the predictive significance of pretreatment pan-immune-inflammation value (PIV) in patients with newly diagnosed glioblastoma multiforme (GBM) who received postsurgical radiation (RT) and concurrent plus adjuvant temozolomide (TMZ).

Methods

The outcomes of 204 newly diagnosed GBM patients were analyzed retrospectively. Each eligible patient's PIV was calculated using the findings of peripheral blood platelet (P), monocyte (M), neutrophil (N), and lymphocyte (L) counts obtained on the first day of therapy: PIV = P × M × N ÷ L. We used receiver operating characteristic (ROC) curve analysis to discover the ideal cutoff values for PIV concerning progression-free (PFS) and overall survival (OS) outcomes. The primary and secondary end-points were the OS and PFS divergences across the PIV groups.

Results

In ROC curve analysis, the optimal PIV cutoff was 385, which substantially interacted with PFS and OS results and categorized patients into low PIV (L-PIV; N = 75) and high PIV (H-PIV; N = 129) groups. Comparative survival analyses showed that the patients in the H-PIV group had significantly shorter median PFS (6.0 vs. 16.6 months; P < 0.001) and OS (11.1 vs. 22.9 months; P < 0.001) durations than those in the L-PIV group. The results of multivariate Cox regression analysis indicated an independent and significant connection between an H-PIV measure and shorter PFS and OS outcomes.

Conclusions

The novel PIV was able to independently stratify newly diagnosed GBM patients into two groups with fundamentally different PFS and OS outcomes following RT and concurrent plus adjuvant TMZ.

The CONUT score is prognostic in esophageal cancer treated with chemoradiotherapy

BACKGROUND

Malnutrition is a frequent issue in esophageal cancer (EC). The Controlling Nutritional Status (CONUT) Score has been established as a prognostic indicator in EC patients who underwent surgery. We aimed to investigate the role of the CONUT Score in EC patients treated with chemoradiotherapy (CRT).

METHODS

The trial included 101 non-metastatic EC patients. Receiver operating characteristic (ROC) curve analyses were used to determine cut-off values for the CONUT Score and other indices. Cox regression analyses were performed to determine prognostic markers.

RESULTS

Of 101 patients, 59.4% (n = 60) and 40.6% (n = 41) of patients were treated with CRT alone and CRT plus surgery, respectively. ROC curve analyses determined an optimal cut-off for CONUT Score in overall survival (OS), which was 3.5 (AUC = 0.63, CI 95%: 0.51-0.76, P = 0.05). The sensitivity and specificity of CONUT were 66% and 61%, respectively. Low CONUT (≤3.5) patients had significantly longer median OS than high CONUT (>3.5) patients (57.1 vs. 23 months; P = 0.009). Multivariate regression analysis revealed a CONUT Score hazard ratio (HR) of 1.96 for OS (CI 95%: 1.03-3.75, P = 0.04).

CONCLUSION

The CONUT Score might be a useful prognostic tool in EC patients treated with CRT. Appropriate nutritional support might provide a better prognosis, which underlines the importance of multidisciplinary assessment of malnutrition in EC patients.

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.

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

Background: Prognostic scores derived from the blood count have garnered significant interest as an indirect measure of the inflammatory pressure in cancer. The recently developed pan-immune-inflammation value (PIV), an equation including the neutrophil, platelet, monocyte, and lymphocyte levels, has been evaluated in several cohorts, although with variations in the tumor types, disease stages, cut-offs, and treatments. Therefore, we evaluated the association between survival and PIV in cancer, performing a systematic review and meta-analysis. Methods: We conducted a systematic review from the Pubmed, Medline, and Embase databases to filter the published studies until 17 May 2022. The meta-analyses were performed with the generic inverse-variance method with a random-effects model. Results: Fifteen studies encompassing 4942 patients were included. In the pooled analysis of fifteen studies, the patients with higher PIV levels had significantly increased risk of death than those with lower PIV levels (HR: 2.00, 95% CI: 1.51−2.64, p < 0.001) and increased risk of progression or death (HR: 1.80, 95% CI: 1.39−2.32, p < 0.001). Analyses were consistent across several clinical scenarios, including non-metastatic or metastatic disease, different cut-offs (500, 400, and 300), and treatment with targeted therapy or immunotherapy (p < 0.001 for each). Conclusion: The available evidence demonstrates that PIV could be a prognostic biomarker in cancer. However, further research is needed to explore the promise of PIV as a prognostic biomarker in patients with non-metastatic disease or patients treated without immunotherapy or targeted therapy.