The Pan-Immune-Inflammation Value predicts the survival of patients with anaplastic lymphoma kinase-positive non-small cell lung cancer treated with first-line ALK inhibitor

The association of immune-inflammation indices at multiple time points with treatment response and survival in advanced non-small cell lung cancer patients receiving immune checkpoint inhibitors

BACKGROUND

Immune and inflammation participate in the progression of non-small cell lung cancer (NSCLC) and some immune-inflammation indexes may serve as prognostic biomarkers in NSCLC patients. This study aimed to investigate the association between immune-inflammation indices at multiple time points and prognosis in advanced NSCLC patients treated with immune checkpoint inhibitors (ICIs).

METHODS

This retrospective study included 102 advanced NSCLC patients treated with ICIs and collected their blood indices within 7 days before treatment (T1), before the 3rd treatment cycle (T2), and before the 5th treatment cycle (T3) to calculate neutrophil-to-lymphocyte ratio (NLR), derived neutrophil-to-lymphocyte ratio (dNLR), pan-immune-inflammatory value (PIV), systemic immune-inflammation index (SII), prognostic nutritional index (PNI), and lung immune prognostic index (LIPI).

RESULTS

dNLR (P = 0.006), SII (P = 0.005), PIV (P = 0.010), and LIPI (P = 0.001) reduced, while PNI increased (P = 0.009) from T1 to T3; NLR was not different among T1, T2, and T3 (P = 0.282). A lower NLR (P = 0.011) and higher PNI (P = 0.026) at T3, and lower LIPI at T2 (P = 0.023) were related to better disease control rate, but these immune-inflammation indices were not linked with objective response rate at any timepoint. Multivariate Cox regression analysis showed that high NLR at T1 was independently related to worse PFS (hazard ratio: 4.187, P = 0.008), while high PNI at T3 was independently associated with better PFS (hazard ratio: 0.454, P = 0.021).

CONCLUSION

NLR before and after treatment, as well as PNI and LIPI after treatment may serve as potential biomarkers for treatment response or survival in advanced NSCLC patients receiving ICIs.

Inflammatory indices reflect distinct pathogenic cellular programs driving sepsis progression: The role of mmp9 protein macromolecules

Sepsis is a severe systemic inflammatory response syndrome in which matrix metalloproteinase 9 (MMP9) plays a key role in inflammatory response and cell migration. In this study, we analyzed different sepsis phenotypes to explore the role of MMP9 in promoting the progression of sepsis, especially how it affects the inflammatory index and related pathogenic cell programs. A standardized cecal ligation puncture (CLP) model was used to evaluate the inflammatory response in sepsis. The experiments followed animal ethical principles and extracted proteins and performed SDS-PAGE analysis for mass spectrometry identification. The samples were separated using filter-assisted sample preparation (FASP) and peptide digestion techniques, and the peptides were separated by ultra-high performance liquid chromatography (UHPLC). Subsequently, proteomic analysis, RNA extraction and differential expression analysis were performed on the data, and bioinformatics and machine learning methods were combined to evaluate the inflammatory index of both in vivo and in vitro samples. Through the integration of admission parameters, different sepsis endotypes and their clinical phenotypes were identified. Significantly, elevated MMP9 expression was found to be strongly associated with inflammatory indices such as NLR and PLR in patients with sepsis, suggesting that MMP9 may be involved in the proliferation of immune cells and the activation of their pro-inflammatory and hypoxic programs. Experimental CLP models validate the pathogenic cellular programs associated with NLR and PLR, demonstrating the critical role of MMP9 in the dynamic progression of sepsis.

Correlation between pan immune inflammation value and testosterone deficiency risk increase

Testosterone deficiency seriously affects male reproductive function, growth and development, and quality of life. There is a certain association between inflammation and testosterone. PIV, a novel immune-inflammatory biomarker, has emerged. However, little is known about the relationship between PIV and serum testosterone. This study aims to investigate the relationship between PIV and serum testosterone. In this cross-sectional study, we analyzed data from 7389 participants in the National Health and Nutrition Examination Survey (NHANES) from 2011 to 2016. Serum total testosterone levels were measured using precise isotope dilution liquid chromatography and tandem mass spectrometry. PIV was calculated as (neutrophil count × monocyte count × platelet count)/lymphocyte count. Weighted t tests or chi-square tests were utilized to analyze the basic characteristics of the population. Weighted logistic regression analysis, smooth-fit curves, threshold effects, and subgroup analysis were conducted to investigate the correlation between the PIV and testosterone deficiency. Using PIV Quartile 1 as the reference, in the fully adjusted model, the odds ratios (OR) and 95% confidence intervals (CI) for Quartile 2 to Quartile 4 participants were 1.14 (0.93, 1.40), 1.28 (0.99, 1.65), and 1.51 (1.18, 1.95), respectively (P for trend < 0.001), with participants in the highest quartile of PIV having a 51% increased risk of testosterone deficiency compared to those in the lowest quartile of PIV. Smooth-fit curves and threshold effect analysis revealed a nonlinear relationship between PIV and testosterone deficiency, with a turning point at 565.89. The subgroup analysis results showed that, except for obesity, there was no statistically significant difference in the relationship between PIV and testosterone deficiency among different subgroups (P > 0.05). Our study results indicate a positive correlation between PIV and the risk of testosterone deficiency. This suggests that PIV may serve as a potential indicator for testosterone deficiency.

Predictive and prognostic value of preoperative pan-immune-inflammation value in patients with locally advanced rectal cancer

This study aimed to investigate the prognostic value of the pan-immune-inflammation value (PIV) in patients with locally advanced rectal cancer (LARC) who received neoadjuvant chemoradiotherapy (nCRT) followed by total mesorectal excision. We retrospectively collected and analyzed the clinicopathological data of 215 resected LARC patients. X-tile software was used to determine the optimal threshold value for PIV in predicting overall survival (OS). The predictive ability of PIV for pathological complete regression (pCR), OS, and disease-free survival (DFS) was evaluated and compared with other inflammation markers. Univariate and multivariate logistic regression analyses for pCR and Cox regression analyses for OS and DFS were conducted. The optimal threshold value for PIV was determined to be 454.7 based on the X-tile software. Patients were then categorized into low (≤ 454.7) and high (> 454.7) PIV groups comprising 153 and 62 patients, respectively. PIV demonstrated superior predictive ability for pCR, OS, and DFS compared to other inflammation markers. LARC patients with low PIV had significantly higher pCR (P = 0.029), OS (P = 0.002), and DFS (P = 0.001) rates compared to those with high PIV. Multivariate regression analysis identified PIV as an independent prognostic factor for pCR (odds ratio = 0.32; 95% confidence interval [CI], 0.10-0.80; P = 0.014), OS (hazard ratio = 3.08; 95% CI, 1.77-5.35; P = 0.001), and DFS (hazard ratio = 2.53; 95% CI, 1.58-4.06; P = 0.002). This study confirmed that preoperative PIV could serve as a useful independent prognostic factor in LARC patients treated with nCRT.

Clinical value of inflammatory indices in predicting poor prognosis and post-hemorrhagic hydrocephalus in patients with intraventricular hemorrhage

BACKGROUND

Hemorrhagic stroke has a high mortality and disability rate. Among them, intraventricular hemorrhage (IVH) is an important factor leading to adverse outcomes. IVH can induce acute obstructive hydrocephalus and chronic communicating hydrocephalus. However, there are currently no effective predictive factors for the early prediction of post-hemorrhage hydrocephalus (PHH).

OBJECTIVES

To assess the role of inflammatory indicators in predicting PHH and poor prognostic outcomes in patients with ventricular hemorrhage.

DESIGN

Single center retrospective case-control study.

METHODS

We retrospectively examined IVH patients treated at our institution from April 2017 to March 2022. Patient characteristics, laboratory data, imaging findings, and 3-month follow-up results were recorded and analyzed.

RESULTS

Among the 145 patients included in the analysis, 102 eventually developed adverse outcomes. There were significant differences between patients with good and poor prognosis in terms of age at admission, GCS score, prevalence of hypertension, lymphocyte count, albumin level, red blood cell distribution width, neutrophil count, NLR, PLR, NAR, PIV, and SII; in addition, among the 110 surviving patients, 36 eventually developed posthemorrhagic hydrocephalus within 3 months. Multivariate logistic regression showed that age and NAR are independent predictors of poor prognosis in IVH patients, while albumin is an independent predictor of posthemorrhagic hydrocephalus within 3 months.

CONCLUSION

The NLR and NAR are independent risk factors for poor prognosis in IVH patients. Additionally, albumin is an independent predictor of chronic hydrocephalus development within 3 months in IVH patients. The NLR, NAR and albumin level could provide prognostic information about IVH patients.

Assessing the prognostic role of panimmune inflammation in high-grade gliomas

OBJECTIVE

High-grade gliomas are aggressive brain tumors with poor prognoses. Understanding the factors that influence their progression is crucial for improving treatment outcomes. This study investigates the prognostic significance of panimmune inflammation in patients diagnosed with high-grade gliomas.

MATERIALS-METHODS

Data from 89 high-grade glioma patients were analysed retrospectively. The Panimmune inflammation Value (PIV) of each patient meeting the eligibility criteria was calculated on the basis of platelet, monocyte, neutrophil, and lymphocyte counts obtained from peripheral blood samples taken on the first day of treatment. PIV is calculated using the following formula: PIV = T × M × N ÷ L. A receiver operating characteristic (ROC) analysis was employed to identify the optimal cut-off value for PIV about progression-free survival (PFS) and overall survival (OS) outcomes. The primary and secondary endpoints were the differences in OS and PFS between the PIV groups. The Kaplan‒Meier method was used for survival analyses.

RESULTS

The ROC analysis indicated that the optimal PIV threshold was 545.5, which exhibited a significant interaction with PFS and OS outcomes. Patients were subsequently divided into two groups based on their PIV levels: a low PIV (L-PIV) group comprising 45 patients and a high PIV (H-PIV) group comprising 44 patients. A comparative analysis of survival rates indicated that patients with elevated PIV had a shorter median PFS of 4.0 months compared to 8.0 months in the low PIV group (P = 0.797), as well as a reduced median OS of 19.0 months versus not available (NA) in the low PIV group (P = 0.215).

CONCLUSION

Our study results did not reveal a statistically significant association between H-PIV measurements and reduced PFS or OS. However, PIV effectively stratified newly diagnosed high-grade glioma patients into two distinct groups with significantly different PFS and OS outcomes.

Pre-treatment pan-immune-inflammation value as a prognostic marker of pazopanib in soft tissue sarcoma

Background

Increasingly, more evidence has shown that inflammation stress and the tumor microenvironment pose a negative effect on targeted therapy. The neutrophil-to-lymphocyte ratio is considered to be a surrogate biomarker of inflammation and can predict pazopanib treatment effect in non-adipocytic soft-tissue sarcoma (STS). The role of the pan-immune-inflammation value (PIV) in STS is still yet to be determined.

Objectives

We sought whether the pre-treatment PIV could be applied to predict the response of pazopanib in STS.

Design

We conducted a retrospective analysis of 75 patients who had been treated with pazopanib for recurrent or metastatic non-adipocytic STS.

Methods

Our cohort was stratified into either a pre-treatment high PIV group with PIV ⩾310 (n = 45) or a low PIV group with PIV <310 (n = 30). We compared their clinical features and outcomes. Cox regression analysis was employed to determine the risk factors of disease progression and mortality. Kaplan-Meier survival curves were utilized to assess both the progression-free survival (PFS) and overall survival (OS).

Results

The results revealed that a pre-treatment high PIV (⩾310) is a risk factor for progression under pazopanib (hazard ratio: 1.91; 95% confidence interval: 1.08-3.36; p = 0.025). The median PFS and OS of the pre-treatment high PIV group were found to be significantly lower than the low PIV group (0.33 vs 0.75 years; p = 0.023, 0.46 vs 1.63 years; p = 0.025).

Conclusion

High pre-treatment PIV in STS patients may indicate an elevated risk of disease progression and mortality. Pre-treatment PIV reflects inflammation stress and acts as a practical biomarker for STS patients treated with pazopanib.

The Baseline Pan-Immune‑Inflammation Value (PIV) and PILE in Predicting Clinical Outcomes and Therapeutic Response for Primary Central Nervous System Lymphoma

Purpose

To investigate the prognostic significance of pan-immune-inflammation value (PIV) and PILE score (based on PIV, lactate dehydrogenase (LDH), and Eastern Cooperative Oncology Group Performance Status (ECOG PS)) in patients with primary central nervous system lymphoma (PCNSL).

Patients and Methods

A total of 109 patients were enrolled. PIV was calculated as follows: (neutrophil count × platelet count × monocyte count)/lymphocyte count. The PILE score was incorporated based on PIV, LDH levels, and ECOG PS. The Kaplan-Meier curves and Cox hazards regression models were applied for survival analyses. The relationship between PIV, PILE, and therapeutic response was examined.

Results

Baseline high PIV was significantly associated with worse overall survival (OS) in univariate (HR 3.990, 95% CI 1.778-8.954, p < 0.001) and multivariate (HR 3.047, 95% CI 1.175-7.897, p = 0.022) analyses. High PIV was also associated with worse progression-free survival (PFS) in univariate (HR 2.121, 95% CI 1.075-4.186, p = 0.030) but not significant in multivariate analyses. PIV outperformed other systemic inflammation parameters. The patients in the high PILE group (PILE score 2-3) had worse OS (p = 0.008) and PFS (p < 0.001) compared to the low PILE group (PILE score 0-1). PILE was independently associated with therapeutic response to initial treatment (OR 0.17, 95% CI 0.05-0.46; p < 0.001).

Conclusion

High PIV and PILE were correlated with worse clinical outcomes in PCNSL patients, indicating that PIV and PILE might be a powerful predictor of prognosis and a potential predictive indicator for therapeutic response in PCNSL.

Association of Pan Immune-Inflammation Value with Long Term Outcomes of Acute Decompensated Heart Failure

BACKGROUND

Although there have been significant improvements in the treatment of heart failure (HF) in recent decades, its prognosis remains poor. Although there are many biomarkers that can help predict the prognosis of patients with HF, there is a need for simpler, cheaper, and more easily available biomarkers.

OBJECTIVE

To evaluate the predictive value of pan-immune-inflammation value (PIV) in patients with acute decompensated HF.

METHODS

We analyzed 409 patients with HF with reduced ejection fraction who were hospitalized for acute decompensated HF. Patients were divided into 3 groups according to tertiles of PIV: tertile 1 (PIV < 357.25), tertile 2 (PIV ≥ 357.25 and < 834.55), and tertile 3 (PIV ≥ 834.55). P values < 0.05 were considered statistically significant. Kaplan-Meier curves and Cox proportional hazards regression models were used to evaluate the association between PIV and all-cause mortality. The primary outcome was 5-year all-cause mortality, and the secondary outcomes were in-hospital 30 days,, 180-day, and 1-year all-cause mortality.

RESULTS

We showed that higher PIV value was associated with both primary and secondary outcomes. The Kaplan-Meier curve showed that patients with higher PIV values had an increased risk of short- and long-term all-cause mortality (log-rank p < 0.001). In the multivariate analysis, PIV was identified as an independent predictor of long-term all-cause mortality in patients with acute decompensated HF, and we observed a 1.96-fold increase in the hazard of an event (odds ratio: 1.96, 95% confidence interval: 1.330 to 2.908, p = 0.001).

CONCLUSIONS

Our study showed that the novel biomarker PIV can be used as a predictor of prognosis in patients with acute decompensated HF.

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.

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.

Prognostic Value of Pre-Chemoradiotherapy Pan-Immune-Inflammation Value (PIV) in Locally Advanced Nasopharyngeal Cancers

BACKGROUND

To examine the prognostic relevance of pan-immune-inflammation value (PIV) in locally advanced nasopharyngeal carcinomas (LA-NPC) patients treated with concurrent chemoradiotherapy (CCRT) definitively.

METHODS

We used receiver operating characteristic (ROC) curve analysis to determine an optimal PIV cutoff that could effectively divide the patient cohort into two distinct groups based on distant metastasis-free (DMFS) and overall survival (OS) results. For this purpose, receiver operating characteristic (ROC) curve analysis was employed. Our primary and secondary endpoints were to investigate the potential correlations between pre-CCRT PIV measurements and post-CCRT OS and DMFS outcomes, respectively.

RESULTS

This retrospective cohort study included 179 LA-NPC patients. The optimal PIV cutoff was 512 (area under the curve: 74.0%; sensitivity: 70.8%, specificity: 68.6%; J-index: 0.394) in ROC curve analysis, creating two patient groups: Group-1: PIV < 512 (N = 108); vs Group-2: PIV ≥ 512 (N = 71). In the comparative analysis, although there were no significant differences between the two groups regarding the patient, disease, and treatment characteristics, the PIV ≥ 512 group had significantly poorer median OS [74.0 months vs not reached yet (NR); HR: 2.81; P < 0.001] and DMFS (27.0 months vs NR; HR: 3.23; P < 0.001) than the PIV < 512 group. Apart from PIV ≥ 512, the N2-3 nodal stage and ≥ 5% weight loss within the preceding 6 months were significant predictors of unfavorable outcomes for DMFS (P < 0.05 for each) and OS (P < 0.05 for each) in univariate analyses. The results of the multivariate analysis showed that each of the three variables had independent negative impacts on both DMFS and OS outcomes (P < 0.05 for each).

CONCLUSIONS

The present findings indicate that PIV, which classifies these patients into two groups with significantly different DMFS and OS, might be a potent prognostic biological marker for LA-NPC patients.

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.

Predictive value of platelet-to-lymphocyte ratio combined with CA199 levels in postoperative survival of patients with gastric cancer: A retrospective study

OBJECTIVE

To develop a new scoring system based on platelet-to-lymphocyte ratio (PLR) and CA199 to predict the prognosis of gastric cancer.

METHODS

PLR-CA199 was identified in a retrospective study that was conducted in a training cohort of 990 gastric cancer patients who underwent curable resection from 2012 to 2014 and validated in a validation cohort of 625 patients between 2015 and 2016.

RESULTS

In the training cohort, PLR-CA199 was related to gender (P = 0.041), age (P = 0.014), tumor location (P = 0.015), tumor size (P < 0.001), Bormann type (P < 0.001), vascular invasion (P < 0.001), perineural invasion (P < 0.001), and TNM staging (P < 0.001). In the validation cohort, PLR-CA199 was related to tumor size (P < 0.001), Bormann type (P = 0.007), vascular invasion (P < 0.001), perineural invasion (P < 0.001), and TNM staging (P < 0.001). Survival analysis showed that in the training cohort the mean disease-free survival (DFS) was 70.699 months for patients PLR-CA199 = 0, 51.223 months for patients PLR-CA199 = 1, and 32.152 months for patients PLR-CA199 = 2 (P < 0.001). The correlation between PLR-CA199 and DFS was further confirmed in the validation cohort (50.640 vs. 41.842 vs. 22.382, P < 0.001). Survival analysis showed that the mean disease special survival (DSS) was 76.668 months for patients PLR-CA199 = 0, 61.218 months for patients PLR-CA199 = 1, and 44.665 months for patients PLR-CA199 = 2 in the training cohort (P < 0.001). The correlation between PLR-CA199 and DSS was further confirmed in the validation cohort (53.858 vs. 46.385 vs. 44.665, P < 0.001). Furthermore, univariate and multivariate analyses showed that PLR-CA199 was an independent prognostic factor for DFS and DSS.

CONCLUSIONS

Preoperative PLR-CA199 may be a useful prognostic indicator, and is a promising tool for predicting the prognosis for gastric cancer.

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.

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.

Integrated circulating tumour DNA and cytokine analysis for therapy monitoring of ALK-rearranged lung adenocarcinoma

BACKGROUND

Detection of circulating tumour DNA (ctDNA) in biological fluids is a minimally invasive alternative to tissue biopsy for therapy monitoring. Cytokines are released in the tumour microenvironment to influence inflammation and tumorigenic mechanisms. Here, we investigated the potential biomarker utility of circulating cytokines vis-à-vis ctDNA in ALK-rearranged+ lung adenocarcinoma (ALK + NSCLC) and explored the optimal combination of molecular parameters that could indicate disease progression.

METHODS

Longitudinal serum samples (n = 296) were collected from ALK + NSCLC patients (n = 38) under tyrosine kinase inhibitor (TKI) therapy and assayed to quantify eight cytokines: IFN-γ, IL-1β, IL-6, IL-8, IL-10, IL-12p70, MCP1 and TNF-α. Generalised linear mixed-effect modelling was performed to test the performance of different combinations of cytokines and previously determined ctDNA parameters in identifying progressive disease.

RESULTS

Serum IL-6, IL-8 and IL-10 were elevated at progressive disease, with IL-8 having the most significant impact as a biomarker. Integrating changes in IL-8 with ctDNA parameters maximised the performance of the classifiers in identifying disease progression, but this did not significantly outperform the model based on ctDNA alone.

CONCLUSIONS

Serum cytokine levels are potential disease progression markers in ALK + NSCLC. Further validation in a larger and prospective cohort is necessary to determine whether the addition of cytokine evaluation could improve current tumour monitoring modalities in the clinical setting.

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.

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.

A high pan-immune-inflammation value before chemoradiotherapy indicates poor outcomes in patients with small-cell lung cancer

Objectives: The objective of our study was to assess the prognostic significance of the Pan-Immune-Inflammation Value (PIV) before concurrent chemoradiation (C-CRT) and prophylactic cranial irradiation (PCI) in patients with limited-stage small-cell lung cancer (SCLC). Methods: The medical records of LS-SCLC patients who underwent C-CRT and PCI between January 2010 and December 2021 were retrospectively analyzed. PIV values were calculated using the peripheral blood samples obtained within the past 7 days before the initiation of treatment: PIV = [neutrophils × platelets × monocytes] ÷ lymphocytes. Using receiver operating characteristic (ROC) curve analysis, the optimal pretreatment PIV cutoff values that can partition the study population into two groups with substantially distinct progression-free survival (PFS) and overall survival (OS) outcomes were determined. The relationship between PIV values and OS outcomes was the primary outcome measure. Results: Eighty-nine eligible patients were divided into two PIV groups at an optimal cutoff of 417 [Area under curve (AUC): 73.2%; sensitivity: 70.4%; specificity: 66.7%]: Group 1: PIV < 417 (N = 36) and Group 2: PIV ≥ 417 (N = 53). Comparative analyses revealed that patients with PIV < 417 had significantly longer OS (25.0 vs 14.0 months, p < .001) and PFS (18.0 vs 8.9 months, p = .004) compared to patients with PIV ≥ 417. The outcomes of the multivariate analysis have verified the independent significance of pretreatment PIV concerning PFS (p < .001) and OS (p < .001) outcomes. Conclusion: The findings of this retrospective study indicate that the pretreatment PIV is a reliable and independent prognostic biomarker for patients with LS-SCLC who were treated with C-CRT and PCI.

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; I2 = 7%) and progression-free survival (HR=1.82; 95%CI: 1.49-2.22; P<0.0001; I2 = 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; I2 = 26%), and a trend toward poor progression-free survival (HR=2.00; 95%CI: 0.90-4.41; P=0.09; I2 = 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.

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 Landscape of ALK-Rearranged Non-Small Cell Lung Cancer: A Comprehensive Review of Clinicopathologic, Genomic Characteristics, and Therapeutic Perspectives

During the last decade, the identification of oncogenic driver mutations and the introduction of tyrosine kinase inhibitors (TKIs) in daily clinical practice have substantially revamped the therapeutic approach of oncogene-addicted, non-small cell lung cancer (NSCLC). Rearrangements in the anaplastic lymphoma kinase (ALK) gene are detected in around 3-5% of all NSCLC patients. Following the promising results of Crizotinib, a first-generation ALK inhibitor (ALK-i), other second-generation and more recently third-generation TKIs have been developed and are currently a landmark in NSCLC treatment, leading to a significant improvement in patients prognosis. As clinical trials have already demonstrated high efficacy of each ALK-i, both in terms of systemic and intracranial disease control, comparative studies between second and third generation ALK-i are still lacking, and primary or secondary ALK-i resistance inevitably limit their efficacy. Resistance to ALK-i can be due to ALK-dependent or ALK-independent mechanisms, including the activation of bypass signaling pathways and histological transformation: these findings may play an important role in the future to select patients' subsequent therapy. This review aims to provide an overview of underlying molecular alterations of ALK-i resistance and point out promising role of liquid biopsy in predicting tumor response and monitoring resistance mutations. The purpose of this review is also to summarize current approval for ALK-rearranged NSCLC patients, to help clinicians in making decisions on therapeutic sequence, and to deepen the role of clinicopathological and genomic characteristics influencing patients' prognosis during treatment with ALK-i.

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 Relationship Between Systemic Immune Inflammatory Index and Prognosis of Patients With Non-Small Cell Lung Cancer: A Meta-Analysis and Systematic Review

Background

The relationship between systemic immune inflammation index (SII) and the prognosis of cancer has always been a subject of intense interest. However, the prognostic value of SII in non-small cell lung cancer (NSCLC) patients remains a controversial topic.

Objective

To evaluate the effect of SII index on prognosis of NSCLC.

Methods

We conducted a comprehensive search of PubMed, EMBASE, and the Cochrane Library databases to determine correlation between SII index, clinicopathological features, overall survival (OS), and progression-free survival (PFS). Odds ratio (ORs) and 95% confidence interval (CIs) were used to assess the connection between SII and clinicopathological parameters, and HRs and 95% CIs were used to assess the connection between SII and survival.

Results

Seventeen studies with 8,877 cases were included in the analysis. Compared with NSCLC patients with low SII level, patients with NSCLC with high SII level had a poor OS (HR = 1.75, 95% CI, 1.50–2.00; P < 0.001) and had a poor PFS (HR = 1.61, 95% CI, 1.25–1.96; P < 0.001). In addition, patients with higher pathological stage (II–III) had higher SII levels (OR = 2.32, 95% CI, 2.06–2.62; P < 0.001).

Conclusions

The SII index is a promising prognostic biomarker for NSCLC and may help clinicians choose appropriate NSCLC treatments.

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.

Pan-Immune-Inflammation Value: A New Prognostic Index in Operative Breast Cancer

Background

To build a predictive scoring model based on simple immune and inflammatory parameters to predict postoperative survival in patients with breast cancer.

Methods

We used a brand-new immuno-inflammatory index-pan-immune-inflammation value (PIV)-to retrospectively evaluate the relationship between PIV and overall survival (OS), and based on the results of Cox regression analysis, we established a simple scoring prediction model based on several independent prognostic parameters. The predictive accuracy of the model was evaluated and independently validated.

Results

A total of 1,312 patients were included for analysis. PIV was calculated as follows: neutrophil count (10⁹/L) × platelet count (10⁹/L) × monocyte count (10⁹/L)/lymphocyte count (10⁹/L). According to the best cutoff value of PIV, we divided the patients into two different subgroups, high PIV (PIV > 310.2) and low PIV (PIV ≤ 310.2), associated with significantly different survival outcomes (3-year OS, 80.26% vs. 86.29%, respectively; 5-year OS, 62.5% vs. 71.55%, respectively). Six independent prognostic factors were identified and used to build the scoring system, which performed well with a concordance index (C-index) of 0.759 (95% CI: 0.715-0.802); the calibration plot showed good calibration.

Conclusions

We have established and verified a simple scoring system for predicting prognosis, which can predict the survival of patients with operable breast cancer. This system can help clinicians implement targeted and individualized treatment strategies.