The Pan-Immune-Inflammation-Value Predicts the Survival of Patients with Human Epidermal Growth Factor Receptor 2 (HER2)-Positive Advanced Breast Cancer Treated with First-Line Taxane-Trastuzumab-Pertuzumab

Systemic immune-inflammation and prognostic immune nutritional index in oral squamous cell carcinoma patients

Aim: To investigate the systemic immune-inflammation index and prognostic immune nutritional index in the prognostic evaluation of oral squamous cell carcinoma.Materials & methods: We analyzed retrospectively the relationship between systemic immune-inflammation index, prognostic immune nutritional index and clinicopathological variables and the overall survival of 262 patients who underwent radical surgery.Results: Multivariate analysis showed high systemic immune-inflammation index (Hazard ratio = 3.062, 95% CI: 1.021-8.251), low prognostic immune nutritional index (Hazard ratio = 0.297, 95% CI: 0.139-0.636), tumor node metastasis classification 3-4 (Hazard ratio = 9.862, 95% CI: 4.658-20.880) patients have worse overall survival.Conclusion: Preoperative systemic immune-inflammation index and prognostic immune nutritional index are independent risk factors for prognostic survival status in oral squamous cell carcinoma.

Pan-immune-inflammation value as a prognostic biomarker for colon cancer and its variation by primary tumor location

BACKGROUND

A growing body of research indicates significant differences between left-sided colon cancers (LCC) and right-sided colon cancers (RCC). Pan-immune-inflammation value (PIV) is a systemic immune response marker that can predict the prognosis of patients with colon cancer. However, the specific distinction between PIV of LCC and RCC remains unclear.

AIM

To investigate the prognostic and clinical significance of PIV in LCC and RCC patients.

METHODS

This multicenter retrospective cohort study included 1510 patients with colon cancer, comprising 801 with LCC and 709 with RCC. We used generalized lifting regression analysis to evaluate the relative impact of PIV on disease-free survival (DFS) in these patients. Kaplan-Meier analysis, as well as univariate and multivariate analyses, were used to examine the risk factors for DFS. The correlation between PIV and the clinical characteristics was statistically analyzed in these patients.

RESULTS

A total of 1510 patients {872 female patients (58%); median age 63 years [interquartile ranges (IQR): 54-71]; patients with LCC 801 (53%); median follow-up 44.17 months (IQR 29.67-62.32)} were identified. PIV was significantly higher in patients with RCC [median (IQR): 214.34 (121.78-386.72) vs 175.87 (111.92-286.84), P < 0.001]. After propensity score matching, no difference in PIV was observed between patients with LCC and RCC [median (IQR): 182.42 (111.88-297.65) vs 189.45 (109.44-316.02); P = 0.987]. PIV thresholds for DFS were 227.84 in LCC and 145.99 in RCC. High PIV (> 227.84) was associated with worse DFS in LCC [PIV-high: Adjusted hazard ratio (aHR) = 2.39; 95% confidence interval: 1.70-3.38; P < 0.001] but not in RCC (PIV-high: aHR = 0.72; 95% confidence interval: 0.48-1.08; P = 0.114).

CONCLUSION

These findings suggest that PIV may predict recurrence in patients with LCC but not RCC, underscoring the importance of tumor location when using PIV as a colon cancer biomarker.

Pan-immune-inflammation value: a new prognostic index in epithelial ovarian cancer

BACKGROUND

Epithelial ovarian cancer (EOC) is one of the deadliest gynaecological malignancies worldwide. The aim of this retrospective study was to create a predictive scoring model based on simple immunological and inflammatory parameters to predict overall survival (OS) and progression-free survival (PFS) in patients with EOC.

METHODS

We obtained 576 EOC patients and randomly assigned them to the training set (n = 405) and the validation set (n = 171) in a ratio of 7:3. We retrospectively evaluated the association between PIV and OS and PFS using a novel immunoinflammatory marker, according to the optihmal treshold of PIV, we divided the patients into two different subgroups, high PIV (PIV > 254.9) and low PIV (PIV ≤ 254.9). Pan-immune Inflammatory Value (PIV) was computed as follows: neutrophil count (109/L) × platelet count (109/L) × monocyte count (109/L)/lymphocyte count (109/L). Then developed a simple score prediction model based on several independent prognostic parameters using Cox regression analysis. We used receiver operator characteristic (ROC) curves, calibration plots, and decision analysis (DCA) curves to evaluate the performance of the model. Finally, we used Kaplan-Meier curves to ensure that the model could distinguish well between low- and high-risk groups.

RESULTS

There was a significant difference in survival outcomes between high PIV (PIV > 310.2) and low PIV (PIV ≤ PIV310.2) (3-year survival rates of 61.34% and 76.71%, respectively); 5-year OS, 25.21% and 51.14%, respectively; 3-year PFS, 40.90% and 65.30%; 5-year PFS, 19.33% and 39.73%, respectively). Column plots of OS and PFS were constructed using independent prognostic factors. In the training module, the 3-, 5-, and 10-year AUCs for OS and PFS column charts were 0.713, 0.796, 0.839, and 0.730, 0.799, 0.826, respectively.In the validation cohort, the 3-, 5-, and 10-year AUCs for OS and PFS column charts were 0.676, 0.803, 0.685, and 0.700, respectively, 0.754, 0.727. The calibration curves showed good agreement between predicted survival and actual observations. The decision analysis curves also showed that the current model has good accuracy and clinical applicability. 3-year OS was 61.34% and 76.71%, respectively; 5-year OS was 25.21% and 51.14%, respectively; 3-year PFS was 40.90% and 65.30%, respectively; 5-year PFS was 19.33% and 39.73%, respectively.

CONCLUSIONS

We constructed and validated a PIV-based nomogram to predict OS and PFS in EOC patients, with a view to helping gynaecologists converge on oncologists in their treatment and follow-up expertise in epithelial ovarian cancer.

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.

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.

Predictive value of inflammation and nutritional index in immunotherapy for stage IV non-small cell lung cancer and model construction

Identifying individuals poised to gain from immune checkpoint inhibitor (ICI) therapies is a pivotal element in the realm of tailored healthcare. The expression level of Programmed Death Ligand 1 (PD-L1) has been linked to the response to ICI therapy, but its assessment typically requires substantial tumor tissue, which can be challenging to obtain. In contrast, blood samples are more feasible for clinical application. A number of promising peripheral biomarkers have been proposed to overcome this hurdle. This research aims to evaluate the prognostic utility of the albumin-to-lactate dehydrogenase ratio (LAR), the Pan-immune-inflammation Value (PIV), and the Prognostic Nutritional Index (PNI) in predicting the response to ICI therapy in individuals with advanced non-small cell lung cancer (NSCLC). Furthermore, the study seeks to construct a predictive nomogram that includes these markers to facilitate the selection of patients with a higher likelihood of benefiting from ICI therapy. A research initiative scrutinized the treatment records of 157 advanced NSCLC patients who received ICI therapy across two Jiangxi medical centers. The cohort from Jiangxi Provincial People's Hospital (comprising 108 patients) was utilized for the training dataset, while the contingent from Jiangxi Cancer Hospital (49 patients) served for validation purposes. Stratification was based on established LAR, PIV, and PNI benchmarks to explore associations with DCR and ORR metrics. Factorial influences on ICI treatment success were discerned through univariate and multivariate Cox regression analysis. Subsequently, a Nomogram was devised to forecast outcomes, its precision gauged by ROC and calibration curves, DCA analysis, and cross-institutional validation. In the training group, the optimal threshold values for LAR, PIV, and PNI were identified as 5.205, 297.49, and 44.6, respectively. Based on these thresholds, LAR, PIV, and PNI were categorized into high (≥ Cut-off) and low (< Cut-off) groups. Patients with low LAR (L-LAR), low PIV (L-PIV), and high PNI (H-PNI) exhibited a higher disease control rate (DCR) (P < 0.05) and longer median progression-free survival (PFS) (P < 0.05). Cox multivariate analysis indicated that PS, malignant pleural effusion, liver metastasis, high PIV (H-PIV), and low PNI (L-PNI) were risk factors adversely affecting the efficacy of immunotherapy (P < 0.05). The Nomogram model predicted a concordance index (C-index) of 0.78 (95% CI: 0.73-0.84). The areas under the ROC curve (AUC) for the training group at 6, 9, and 12 months were 0.900, 0.869, and 0.866, respectively, while the AUCs for the external validation group at the same time points were 0.800, 0.886, and 0.801, respectively. Throughout immunotherapy, PIV and PNI could act as prospective indicators for forecasting treatment success in NSCLC patients, while the devised Nomogram model exhibits strong predictive performance for patient prognoses.

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.

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.

Novel pretreatment nomograms based on pan-immune-inflammation value for predicting clinical outcome in patients with head and neck squamous cell carcinoma

Background

The prognostic value of an effective biomarker, pan-immune-inflammation value (PIV), for head and neck squamous cell carcinoma (HNSCC) patients after radical surgery or chemoradiotherapy has not been well explored. This study aimed to construct and validate nomograms based on PIV to predict survival outcomes of HNSCC patients.

Methods

A total of 161 HNSCC patients who underwent radical surgery were enrolled retrospectively for development cohort. The cutoff of PIV was determined using the maximally selected rank statistics method. Multivariable Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses were performed to develop two nomograms (Model A and Model B) that predict disease-free survival (DFS). The concordance index, receiver operating characteristic curves, calibration curves, and decision curve analysis were used to evaluate the nomograms. A cohort composed of 50 patients who received radiotherapy or chemoradiotherapy (RT/CRT) alone was applied for generality testing of PIV and nomograms.

Results

Patients with higher PIV (≥123.3) experienced a worse DFS (HR, 5.01; 95% CI, 3.25-7.72; p<0.0001) and overall survival (OS) (HR, 5.23; 95% CI, 3.34-8.18; p<0.0001) compared to patients with lower PIV (<123.3) in the development cohort. Predictors of Model A included age, TNM stage, neutrophil-to-lymphocyte ratio (NLR), and PIV, and that of Model B included TNM stage, lymphocyte-to-monocyte ratio (LMR), and PIV. In comparison with TNM stage alone, the two nomograms demonstrated good calibration and discrimination and showed satisfactory clinical utility in internal validation. The generality testing results showed that higher PIV was also associated with worse survival outcomes in the RT/CRT cohort and the possibility that the two nomograms may have a universal applicability for patients with different treatments.

Conclusions

The nomograms based on PIV, a simple but useful indicator, can provide prognosis prediction of individual HNSCC patients after radical surgery and may be broadly applicated for patients after RT/CRT alone.

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.

Development and internal validation of a nomogram based on peripheral blood inflammatory markers for predicting prognosis in nasopharyngeal carcinoma

BACKGROUND

Inflammatory markers, including the product of neutrophil count, platelet count, and monocyte count divided by lymphocyte count (PIV) and the platelet-to-white blood cell ratio (PWR), have not been previously reported as prognostic factors in nasopharyngeal carcinoma (NPC) patients. In order to predict overall survival (OS) in NPC patients, our goal was to create and internally evaluate a nomogram based on inflammatory markers (PIV, PWR).

METHODS

A retrospective study was done on patients who received an NPC diagnosis between January 2015 and December 2018. After identifying independent prognostic indicators linked to OS using Cox proportional hazards regression analysis, we created a nomogram with the factors we had chosen.

RESULTS

A total of 630 NPC patients in all were split into training (n = 441) and validation sets (n = 189) after being enrolled in a population-based study in 2015-2018 and monitored for a median of 5.9 years. In the training set, the age, PIV, and PWR, selected as independent predictors for OS via multivariate Cox's regression model, were chosen to develop a nomogram. Both training and validation cohorts had C-indices of 0.850 (95% confidence interval [CI]: 0.768-0.849) and 0.851 (95% CI: 0.765-0.877). Furthermore, compared with traditional TNM staging, our nomogram demonstrated greater accuracy in predicting patient outcomes. The risk stratification model derived from our prediction model may facilitate personalized treatment strategies for NPC patients.

CONCLUSION

Our findings confirmed the prognostic significance of the PWR and PIV in NPC. High PIV levels (>363.47) and low PWR (≤36.42) values are associated with worse OS in NPC patients.

Association between pan-immune inflammatory value and ulcerative colitis

OBJECTIVE

Ulcerative colitis is a chronic idiopathic disease that causes inflammation of the colon and rectum, progressing with relapses and remissions. Systemic inflammatory index (SII) and pan-immune inflammatory value (PIV) are newly developed biomarkers. There are many studies in the literature showing the relationship between SII and PIV with malignancies and inflammatory diseases. In this study we aimed to determine the relationship between SII and PIV with the activity of ulcerative colitis.

MATERIALS AND METHODS

146 Ulcerative colitis patients were retrospectively investigated by the time of diagnosis based on clinical, endoscopic and histolopathological findings. Patients and healthy individuals SII and PIV levels were calculated and compared with each other; and Mayo, DUBLIN, UCIES endoscopic subscores of patients were also obtained. Roc curve analysis were used to determine the cut-off value for PIV.

RESULTS

SII (468.6 ± 203.5 vs. 823.1 ± 555.1; p < .001), PIV (288.2 ± 159.9 vs. 912.2 ± 924.1; p < .001), were statistically different between groups. PIV (OR: 1.157; (1.041-1.432), p = .036), was also observed to be the independent predictor of ulcerative colitis. The best cut off value of PIV in the prediction of ulcerative colitis was ≥ 506 with 89.6% sensitivity and 63.7% specificity (AUC = 0.812; 95% CI 0.763-0.854, p < .001).

CONCLUSION

Based on the results of our study, we found that SII and PIV levels were significantly increased in ulcerative colitis patients at the time of diagnosis and were associated with disease severity in the endoscopic scores RACHMILEWITZ, UCEIS and DUBLIN scores, but not for MES score.

Effect of preoperative pan-immune-inflammation value on clinical and oncologic outcomes after colorectal cancer surgery: a retrospective study

Purpose

Surgical resection, the primary treatment for colorectal cancer (CRC), is often linked with postoperative complications that adversely affect the overall survival rates (OS). The pan-immune-inflammation value (PIV), a novel biomarker, is promising in evaluating cancer prognoses. We aimed to explore the impact of preoperative immune inflammation status on postoperative and long-term oncological outcomes in patients with CRC.

Methods

A retrospective analysis of 203 patients with CRC who underwent surgery (January 2016-June 2020) was conducted. The preoperative PIV was calculated as [(neutrophil count + platelet count + monocyte count) / lymphocyte counts]. The PIV optimal cutoff value was determined based on the OS using the Contal and O'Quigley methods.

Results

A PIV value ≥155.90 was defined as high. Patients were categorized into low-PIV (n = 85) and high-PIV (n = 118) groups. Perioperative clinical outcomes (total operation time, time to gas out, sips of water, soft diet, and hospital stay) were not significantly different between the groups. The high-PIV group exhibited more postoperative complications (P = 0.024), and larger tumor size compared with the low-PIV group. Multivariate analysis identified that American Society of Anesthesiologists grade III (P = 0.046) and high-PIV (P = 0.049) were significantly associated with postoperative complications. The low-PIV group demonstrated higher OS (P = 0.001) and disease-free survival rates (DFS) (P = 0.021) compared with the high-PIV group. Advanced N stage (P = 0.005) and high-PIV levels (P = 0.047) were the identified independent prognostic factors for OS, whereas advanced N stage (P = 0.045) was an independent prognostic factor for DFS.

Conclusion

Elevated preoperative PIV was associated with an increased incidence of postoperative complications and served as an independent prognostic factor for OS.

Pan-immune inflammation value as a prognostic biomarker for cancer patients treated with immune checkpoint inhibitors

Background

Immune checkpoint inhibitors (ICIs) represent a paradigm shift in the development of cancer therapy. However, the improved efficacy of ICIs remains to be further investigated. We conducted a systematic review and meta-analysis to evaluate the pan-immunoinflammatory value (PIV) and PILE score used to predict response to ICI therapy.

Methods

We searched selected databases for studies on pan-immune inflammation values and their association with outcomes of treatment with immune checkpoint inhibitors. We used hazard ratios (HRS) and 95% confidence intervals (CI) to summarize survival outcomes. All data analyses were performed using STATA 15.0.

Results

7 studies comprising 982 patients were included in the meta-analysis. The pooled results showed that higher PIV was significantly associated with shorter overall survival OS (HR = 1.895, 95%CI: 1.548-2.318) and progression-free survival (PFS) (HR = 1.582, 95%CI: 1.324-1.890). Subgroup analyses also confirmed the reliability of the results.

Conclusions

High PIV and PILE metrics are associated with lower survival in cancer patients receiving ICIs.

Systemic inflammation and its relationship with pruritus in early-stage mycosis fungoides

The underlying mechanisms mycosis fungoides (MF)-related pruritus remain unclear, and the link between pruritus and systemic inflammation in MF is unexplored. We aimed to investigate systemic inflammation in MF patients and its potential connection to pruritus. In this retrospective study, demographic characteristics, MF stage, clinical and laboratory findings, and neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), monocyte-lymphocyte ratio (MLR), systemic immune-inflammation index (SII), systemic inflammation response index (SIRI) and pan-immune inflammation value (PIV) were assessed for all participants. Additionally, mSWAT scores, Dermatology Life Quality Index (DLQI), and pruritus presence and intensity via Visual Analogue Scale (VAS) scoring were recorded for MF patients. A total of 81 patients with early-stage MF and 50 controls were enrolled. Itching was present in 41 patients (50.6%). NLR, PLR, SII, SIRI and CRP values in the MF group were significantly higher. CRP, NLR, mSWAT and DLQI score were significantly higher in MF patients with pruritus than those without. Pruritus was positively correlated with DLQI, mSWAT, CRP, NLR, MLR and SIRI. VAS score was positively correlated with eosinophil count and DLQI. In the multivariate logistic regression model, only NLR was an independent and significant associate of pruritus in patients with MF. This study provides evidence of enhanced systemic inflammation in early-stage MF patients. Additionally, the correlation between pruritus with mSWAT scores and systemic inflammation parameters suggests a potential link between pruritus and the inflammatory milieu in MF.

Prognostic significance of pan-immune-inflammation value (PIV) in nasopharyngeal carcinoma patients

Background

Blood-based immune-inflammation indexes have been widely used to predict survival in a variety of cancers. In this research, we seeked to evaluate a novel immune-inflammation marker, named the pan-immune-inflammation value (PIV), in patients with nasopharyngeal carcinoma (NPC) undergoing definitive radiotherapy.

Methods

A group of 377 patients with NPC was retrospectived analyzed. Clinical data and laboratory data were collected. Receiver operating characteristic (ROC) curve analysis was performed in order to determine the optimal PIV cut-off value. Survival curves were estimated by Kaplan-Meier method, and prognostic variables were identified using a Cox regression model. Additionally, we developed a nomogram and assessed its acuracy using the concordance index (C-index) and a calibration curve.

Results

The optimal PIV cut-off value was 146.24 according to ROC analysis. High PIV was related to poorer Eastern Cooperative Oncology Group Performance Status (ECOG PS) score (p = 0.017), more advanced T (p＜0.001) and clinical stages (p = 0.024). In univariate analysis, older Age, poorer ECOG PS, higher Epstein-Barr virus DNA (EBV-DNA), advanced T, N and clinical stage, and higher PIV levels were related to patients' poorer overall survival (OS). Poorer ECOG PS, higher EBV-DNA, later T stage, later clinical stage, and higher PIV were associated with patients' poorer progression free survival (PFS). Male sex and later T stage were associated with patients' poorer locoregional recurrence free survival (LRRFS). Poorer ECOG PS, higher EBV-DNA, later T stage, later clinical stage, and higher PIV were associated with patients' poorer distant metastasis free survival (DMFS). Multivariate analysis demonstrated that PIV was an independent prognostic index for OS (HR 2.231, 95 % CI 1.241-4.011, P = 0.007), PFS (HR 1.664, 95 % CI 1.003-2.760, P = 0.049), and DMFS(HR 2.081, 95 % CI 1.071-4.044, P = 0.031). Nomogram C-indexes for the nomogram of OS were 0.684, and PFS were 0.62, respectively. Survival predictions and actual survival were consistent according to the calibration curve.

Conclusions

Pre-treatment PIV is a promising biomarker for predicting survival in patients with NPC.

Predictive potential of pan-immune-inflammation value / hemoglobin index as biomarker for osteoradionecrosis risk in locally advanced nasopharyngeal carcinomas

OBJECTIVE

We aimed to investigate whether the Pan-Immune-Inflammation-Value/Hemoglobin (PIV/Hb) index could predict the risk of osteoradionecrosis (ORN) in patients receiving concurrent chemoradiotherapy (CCRT) for locally advanced nasopharyngeal cancer (LA-NPC).

MATERIALS AND METHODS

This retrospective analysis included LA-NPC patients who underwent CCRT and pre-CCRT oral exams at our institution's Departments of Radiation Oncology and Dentistry between January 2010 and December 2022. The relationship between ORN rates and PIV-Hb levels was explored using receiver operating characteristic curve analysis. The primary objective was to establish a correlation between pre-CCRT PIV-Hb levels and ORN rates, while the secondary objective was to identify other risk factors for ORN.

RESULTS

Of 249 eligible patients, 21 (8.4 %) were diagnosed with ORN. The optimal pre-CCRT PIV/Hb cutoff was 73.8, which divided patients into two subgroups with distinctive ORN risk estimates: Group 1: PIV/Hb < 73.8 (N = 206), and Group 2: PIV/Hb ≥ 73.8 (N = 43). The results of the comparative analysis indicated that the cohort with PIV/Hb ≥ 73.8 exhibited substantially higher rates of ORN than the PIV/Hb < 73.8 cohort (44.2 % vs. 1.0 %; P < 0.001). The multivariate logistic regression analysis indicated that the pretreatment PIV/Hb ≥ 73.8 was independently associated with higher ORN rates (P < 0.001).

CONCLUSION

The results of our current investigation indicate that higher levels of pretreatment PIV/Hb were associated with a significant independent increase in ORN rates in LA-NPC patients who received CCRT.

Prognostic value of baseline neutrophil/lymphocyte ratio in HER2-positive metastatic breast cancer: exploratory analysis of data from the CLEOPATRA trial

PURPOSE

This study aimed to evaluate the prognostic role of the baseline neutrophil/lymphocyte ratio (NLR) in HER2-positive metastatic breast cancer (MBC) patients treated with trastuzumab/pertuzumab.

EXPERIMENTAL DESIGN

Data from 780 patients from the CLEOPATRA trial and 248 local patients were collected. Patients were divided into the low and high NLR subgroups by the NLR cutoff value. Propensity score matching (PSM) and inverse probability of treatment weighting (IPTW) methods were used to control bias. Associations between the NLR and progression-free survival (PFS) and overall survival (OS) were analyzed.

RESULTS

The baseline characteristics of the subgroups were well balanced after PSM and IPTW. A low baseline NLR was associated with better PFS and OS in the trastuzumab and docetaxel (TH) group in the unadjusted, PSM and IPTW models. After IPTW, a low NLR, versus a high NLR, was associated with improved PFS (HR 1.35, 95% CI 1.07-1.70, P = 0.012) and OS (HR 1.47, 95% CI 1.12-1.94, P = 0.006) in the TH group. In patients undergoing treatment with trastuzumab and pertuzumab and docetaxel (THP), a low baseline NLR was also correlated with better PFS but not OS across the three models. After IPTW, a low NLR was associated with better PFS (HR 1.52, 95% CI 1.20-1.93, P = 0.001) than a high NLR in the THP group. Multivariate analyses showed that a low baseline NLR was a predictor for PFS and OS in the TH group and for PFS in the THP group in all three models. In the real-world setting, a low baseline NLR was a predictor of better PFS among patients treated with docetaxel plus trastuzumab without or with pertuzumab in the multivariate model (P = 0.015 and 0.008, respectively).

CONCLUSIONS

A low baseline NLR is associated with better survival outcomes among HER2-positive MBC patients receiving docetaxel plus trastuzumab/pertuzumab as first-line therapy.

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.

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.

Peripheral blood lymphocytes predict clinical outcomes in hormone receptor-positive HER2-negative advanced breast cancer patients treated with CDK4/6 inhibitors

Background

Cyclin-Dependent Kinase 4/6 inhibitors (CDK4/6i) combined with Endocrine Therapy (ET) are the standard treatment for patients with Hormone Receptor-positive/HER2-negative advanced breast cancer (HR+/HER2- aBC).

Objectives

While CDK4/6i are known to reduce several peripheral blood cells, such as neutrophils, lymphocytes and platelets, the impact of these modulations on clinical outcomes is unknown.

Design

A multicenter, retrospective-prospective Italian study.

Methods

We investigated the association between baseline peripheral blood cells, or their early modifications (i.e. 2 weeks after treatment initiation), and the progression-free survival (PFS) of HR+/HER2- aBC patients treated with ETs plus CDK4/6i. Random Forest models were used to select covariates associated with patient PFS among a large list of patient- and tumor-related variables.

Results

We evaluated 638 HR+/HER2- aBC patients treated with ET plus CDK4/6i at six Italian Institutions between January 2017 and May 2021. High baseline lymphocyte counts were independently associated with longer PFS [median PFS (mPFS) 20.1 versus 13.2 months in high versus low lymphocyte patients, respectively; adjusted Hazard Ratio (aHR): 0.78; 95% confidence interval (CI): 0.66-0.92; p = 0.0144]. Moreover, patients experiencing a lower early reduction of lymphocyte counts had significantly longer PFS when compared to patients undergoing higher lymphocyte decrease (mPFS 18.1 versus 14.5 months; aHR: 0.82; 95% CI: 0.73-0.93; p = 0.0037). Patients with high baseline lymphocytes and undergoing a lower reduction, or even an increase, of lymphocyte counts during CDK4/6i therapy experienced the longest PFS, while patients with lower baseline lymphocytes and undergoing a higher decrease of lymphocytes had the lowest PFS (mPFS 21.4 versus 11 months, respectively).

Conclusion

Baseline and on-treatment modifications of peripheral blood lymphocytes have independent prognostic value in HR+/HER2- aBC patients. This study supports the implementation of clinical strategies to boost antitumor immunity in patients with HR+/HER2- aBC treated with ETs plus CDK4/6i.

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.

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.

Association between platelet-to-lymphocyte ratio and outcomes in HER2-positive advanced breast cancer patients treated with pyrotinib: a retrospective study

Background

Peripheral blood biomarkers have been reported to be associated with the prognosis of breast cancer (BC) patients, but a few findings remain controversial. This study aimed to explore the correlation between peripheral blood indicators and treatment outcomes in human epidermal growth factor receptor 2 (HER2)-positive advanced BC patients treated with pyrotinib.

Methods

This was a retrospective cohort study including 156 HER2-positive advanced BC patients who treated with pyrotinib between March 2019 and May 2021. The baseline clinical characteristics including age, hormone receptor (HR) status, Ki-67, sites of metastasis, antitumor therapies and peripheral blood parameters including neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), monocyte to lymphocyte ratio (MLR), the product of neutrophil, platelet, and monocyte counts divided by lymphocyte count [pan-immune-inflammation value (PIV)] were collected. Tumor response was assessed every two cycles during treatment period. Follow-up was performed every 2 months to record survival status. All patients were followed up until death or time of data lock.

Results

Low PLR was associated with better disease control rate (P=0.005). Univariate analysis showed that high MLR (P=0.004), PLR (P=0.003), or PIV (P=0.02), low lymphocyte count (P=0.025), more than two metastatic sites (P<0.001), and presence of liver metastasis (P<0.001) or brain metastasis (P<0.001) were associated with poor progression-free survival (PFS). Multivariate analysis showed that only high PLR was an independent factor for poor PFS [hazard ratio =0.63; 95% confidence interval (CI): 0.41-0.97; P=0.038]. For overall survival (OS), univariate analysis showed that high NLR (P=0.001), MLR (P=0.005), PLR (P<0.001), or PIV (P=0.018), more than two metastatic sites (P=0.001), presence of liver metastasis (P=0.004) or brain metastasis (P=0.007), and pyrotinib monotherapy (P=0.036) were associated with worse OS. Multivariate analysis showed that PLR (hazard ratio =0.37; 95% CI: 0.14-0.94; P=0.037), number of metastatic sites (hazard ratio =2.84; 95% CI: 1.02-7.94; P=0.046) and treatment regimens (hazard ratio =0.15; 95% CI: 0.03-0.73; P=0.019) were independent factors.

Conclusions

High PLR is associated with poor treatment response and is an independent unfavorable prognostic factor in HER2-positive advanced BC patients treated with pyrotinib. The findings herein indicate that patients with higher PLR are less likely to benefit from pyrotinib-based therapy and may be helpful in identifying the effective population in clinical practice.

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.

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

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

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.

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

PURPOSE

The aim of this retrospective study was to explore whether pretreatment Pan-Immune-Inflammation-Value (PIV) measurements might predict the risk of mandibular osteoradionecrosis (ORN) in patients receiving concurrent chemoradiotherapy (CCRT) for locally advanced nasopharyngeal cancer (LA-NPC).

METHODS

The platelet, monocyte, neutrophil, and lymphocyte counts acquired on the first day of CCRT were used to compute pretreatment PIV levels: PIV = (Platelets × Monocytes × Neutrophils) ÷ Lymphocytes. Receiver operating characteristic curve analysis was used to determine the association between ORN rates and PIV levels. Spearman correlation analysis was used to examine the probable intergroup correlations. The potential link between the pretreatment PIV levels and the post-treatment ORN rates was determined as the primary objective.

RESULTS

21 (10.0%) of 210 eligible patients were diagnosed with ORN. The optimal pre-CCRT PIV cutoff was 833, which separated patients into two PIV groups with divergent ORN prevalence estimates: Group 1: PIV < 833 (N = 153), and Group 2: PIV ≥ 833 (N = 57). The comparison analysis found that the PIV ≥ 833 cohort had significantly higher ORN rates than the PIV < 833 cohort (29.8% vs. 2.6%; P < 0.001). Other characteristics linked to significantly higher ORN rates were the patient's continuing smoking, the use of the Three-dimensional conformal radiation therapy technique, the mean mandibular dose of ≥ 58.1 Gy, the number of tooth extractions before CCRT ≥ 4, and the presence of tooth extractions after CCRT. The independent importance of all factors on higher ORN occurrence rates were retained in multivariate analysis (P < 0.05).

CONCLUSIONS

Our findings revealed a strong link between aggravated inflammatory response and ORN genesis, with high pretreatment PIV levels related to significantly higher ORN rates.

Low neutrophil-to-lymphocyte ratio and pan-immune-inflammation-value predict nodal pathologic complete response in 1274 breast cancer patients treated with neoadjuvant chemotherapy: a multicenter analysis

Background

Systemic inflammatory markers draw great interest as potential blood-based prognostic factors in several oncological settings.

Objectives

The aim of this study is to evaluate whether neutrophil-to-lymphocyte ratio (NLR) and pan-immune-inflammation value (PIV) predict nodal pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC) in node-positive (cN+) breast cancer (BC) patients.

Design

Clinically, cN+ BC patients undergoing NAC followed by breast and axillary surgery were enrolled in a multicentric study from 11 Breast Units.

Methods

Pretreatment blood counts were collected for the analysis and used to calculate NLR and PIV. Logistic regression analyses were performed to evaluate independent predictors of nodal pCR.

Results

A total of 1274 cN+ BC patients were included. Nodal pCR was achieved in 586 (46%) patients. At multivariate analysis, low NLR [odds ratio (OR) = 0.71; 95% CI, 0.51-0.98; p = 0.04] and low PIV (OR = 0.63; 95% CI, 0.44-0.90; p = 0.01) were independently predictive of increased likelihood of nodal pCR. A sub-analysis on cN1 patients (n = 1075) confirmed the statistical significance of these variables. PIV was significantly associated with axillary pCR in estrogen receptor (ER)-/human epidermal growth factor receptor 2 (HER2)+ (OR = 0.31; 95% CI, 0.12-0.83; p = 0.02) and ER-/HER2- (OR = 0.41; 95% CI, 0.17-0.97; p = 0.04) BC patients.

Conclusion

This study found that low NLR and PIV levels predict axillary pCR in patients with BC undergoing NAC.

Registration

Eudract number NCT05798806.

Clinical utility of the pan-immune-inflammation value in breast cancer patients

Background

The newly discovered pan-immune-inflammation value (PIV) has been illustrated to have good prognostic value for cancer patient prognosis. However, the prognostic usefulness of PIV in breast cancer patients is unknown. As a result, to aid the clinic in providing a distinctive and trustworthy biomarker to better assess breast cancer patient's prognosis, we conducted this meta-analysis to investigate the relationship between PIV and the survival of breast cancer patients.

Methods

We conducted a systematic search of Pubmed, Embase, the Cochrane Library, and the CNKI databases to screen for eligible studies published up to April 2023. Outcomes included overall survival (OS), progression-free survival (PFS), and pathological complete response (pCR). The hazard ratio (HR) and the corresponding 95% confidence interval (CI) were used as the indicators. STATA 15.0 software was used to perform meta-analysis, sensitivity analysis, and publication bias analysis.

Results

A total of eight articles, involving 2953 patients, met the inclusion criteria and were included in this meta-analysis. The results showed that patients with higher PIV levels had a significantly shorter OS (HR: 2.045, 95% CI: 1.355-3.086, P = 0.001) and PFS (HR: 1.466, 95% CI: 1.163-1.848, P = 0.001). Besides, the PIV value was negatively correlated with the efficacy of neoadjuvant chemotherapy. Sensitivity analysis showed that the results of this study were reliable and stable.

Conclusions

PIV has a good prognostic value in breast cancer patients and is expected to be a prognostic biomarker for breast cancer.

Pan-Immune-Inflammatory Value in Patients with Non-Small-Cell Lung Cancer Undergoing Neoadjuvant Immunochemotherapy

Background

We aimed to investigate the predictive value of a systematic serum inflammation index, pan-immune-inflammatory value (PIV), in pathological complete response (pCR) of patients treated with neoadjuvant immunotherapy to further promote ideal patients' selection.

Methods

The clinicopathological and baseline laboratory information of 128 NSCLC patients receiving neoadjuvant immunochemotherapy between October 2019 and April 2022 were retrospectively reviewed. We performed least absolute shrinkage and selection operator (LASSO) algorithm to screen candidate serum biomarkers for predicting pCR, which further entered the multivariate logistic regression model to determine final biomarkers. Accordingly, a diagnostic model for predicting individual pCR was established. Kaplan-Meier method was utilized to estimate curves of disease-free survival (DFS), and the Log rank test was analyzed to compare DFS differences between patients with and without pCR.

Results

Patients with NSCLC heterogeneously responded to neoadjuvant immunotherapy, and those with pCR had a significant longer DFS than patients without pCR. Through LASSO and the multivariate logistic regression model, PIV was identified as a predictor for predicting pCR of patients. Subsequently, a diagnostic model integrating with PIV, differentiated degree and histological type was constructed to predict pCR, which presented a satisfactory predictive power (AUC, 0.736), significant agreement between actual and our nomogram-predicted pathological response.

Conclusion

Baseline PIV was an independent predictor of pCR for NSCLC patients receiving neoadjuvant immunochemotherapy. A significantly longer DFS was achieved in patients with pCR rather than those without pCR; thus, the PIV-based diagnostic model might serve as a practical tool to identify ideal patients for neoadjuvant immunotherapeutic guidance.

Association of Circulating Tumor Cells, Megakaryocytes and a High Immune-Inflammatory Environment in Metastatic Breast Cancer

Liquid biopsy is becoming an important source of new biomarkers during the treatment of metastatic cancer patients. Using size-based microfluid technology, we isolated circulating tumor cells (CTCs) from metastatic breast cancer patients to evaluate their presence and cluster formation, as well as the presence of megakaryocytes and immune-inflammatory blood cells, and to correlate their presence with clinicopathological data and overall survival (OS). In total, 59 patients (median age 60.4 years) were included in the study: 62.7% luminal A/B-like, 20.3% HER2-positive, and 17% triple-negative. Our results showed that at least one CTC was present in 79.7% and ≥5 CTCs in 35.2% of the patients. CTC clusters were present in patients with ≥5 CTCs only (in 19.2% of them), and megakaryocytes were present in 52% of all patients. The presence of CTC clusters and megakaryocytes was positively associated with the CTC count. Patients with low pan-inflammatory value (PIV), low systemic immune-inflammatory index (SII), and low relative change from baseline (ΔPIV%, ΔSII%) were associated with significantly higher OS than their counterparts. ΔPIV%, the presence of infection in the last month, and a long duration of metastatic disease were identified as independent prognostic factors for OS. The interplay of CTCs, CTC clusters, megakaryocytes, and PIV needs to be further explored.

Biomarkers for Outcome in Metastatic Melanoma in First Line Treatment with Immune Checkpoint Inhibitors

Introduction: A high proportion of metastatic melanoma patients do not respond to immune checkpoint inhibitors (ICI), and until now, no validated biomarkers for response and survival have been known. Methods: We performed a retrospective analysis of outcomes in patients with metastatic melanoma treated with first-line ICI at the Institute of Oncology Ljubljana from January 2018 to December 2020. The immune-related adverse events (irAEs) and serum immune-inflammation parameters (neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (LR), systemic immune-inflammation index (SII) and pan-immune-inflammation value (PIV)) were analyzed as potential biomarkers for response and survival. Survival rates were calculated using the Kaplan–Meier method and then compared with the log-rank test. Multivariate regression Cox analysis was used to determine independent prognostic factors for progression-free survival (PFS) and overall survival (OS). Results: Median follow-up was 22.5 months. The estimated median progression-free survival (PFS) was 15 months (95% CI 3.3–26.2). The two-year survival rate (OS) was 66.6%. Among 129 treated patients, 24 (18.6%) achieved complete response, 28 (21.7%) achieved partial response, 26 (20.2%) had stable disease and 51 (39.5%) patients experienced a progressive disease. There was a higher response rate in patients with irAEs (p < 0.001) and high NLR before the second cycle of ICI (p = 0.052). Independent prognostic factors for PFS were irAE (HR 0.41 (95% CI 0.23–0.71)), SII before the first cycle of ICI (HR 1.94 (95% CI 1.09–3.45)) and PLR before the second cycle of ICI (HR 1.71 (95% CI 1.03–2.83)). The only independent prognostic factor for OS was SII before the first cycle of ICI (HR 2.60 (95% CI 0.91–7.50)). Conclusions: Patients with high pre-treatment levels of SII had a higher risk of progression and death; however, patients with irAEs in the high-SII group might respond well to ICI. Patients who develop irAEs and have high NLRs before the second ICI application have higher rates of CR and PR, which implicates their use as early biomarkers for responsiveness to ICI.

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.

The pan-immune-inflammation value is associated with clinical outcomes in patients with advanced TNBC treated with first-line, platinum-based chemotherapy: an institutional retrospective analysis

Background

Advanced triple-negative breast cancer (aTNBC) has a poor prognosis; thus, there is a need to identify novel biomarkers to guide future research and improve clinical outcomes.

Objectives

We tested the prognostic ability of an emerging, complete blood count (CBC)-based inflammatory biomarker, the pan-immune-inflammation value (PIV), in patients with aTNBC treated with first-line, platinum-based chemotherapy.

Design

This was a retrospective, monocentric, observational study.

Methods

We included consecutive aTNBC patients treated with platinum-based, first-line chemotherapy at our Institution, and for whom baseline (C1) CBC data were available. We collected CBC data early on-treatment, when available. PIV was calculated as: (neutrophil count × platelet count × monocyte count)/lymphocyte count. Patients with hormone receptor-positive (HR+), human epidermal growth factor receptor 2 (HER2)-negative advanced breast cancer (aBC) were included in a control, non-TNBC cohort.

Results

A total of 78 aTNBC patients were included. When evaluated as a continuous variable, PIV-C1 was associated with worse overall survival (OS; p < 0.001) and progression-free survival (PFS; p < 0.001). On the other hand, when PIV-C1 was assessed on the basis of its quantile distribution, patients with 'high PIV-C1' experienced worse OS [adjusted hazard ratio (HR): 4.46, 95% confidence interval (CI): 2.22-8.99; adjusted p < 0.001] and PFS (adjusted HR: 2.03, 95% CI: 1.08-3.80; adjusted p = 0.027) when compared to patients with 'low PIV-C1'. Higher PIV-C1 was also associated with primary resistance to chemotherapy. Similarly, a higher PIV calculated from CBC at C2D1 (PIV-C2) was associated with worse survival outcomes. We also created a PIV-based score combining information about both PIV-C1 and PIV-C2 and allowing the stratification of patients at low, intermediate, and high risk of death. No association was observed between PIV-C1 and clinical outcomes of HR+/HER2- aBC patients.

Conclusion

PIV has a promising prognostic discrimination ability in aTNBC patients treated with first-line, platinum-based chemotherapy. Both baseline and early on-treatment PIV are associated with clinical outcomes and may be exploited for creating PIV-based risk classifiers if further validated.

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.

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.

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

AIM

To assess the prognostic effect of pan-immune inflammation value (PIV) in patients with metastatic castration-resistant prostate cancer (mCRPC) treated with abiraterone acetate (AA) or enzalutamide.

METHODS

Patients with mCRPC treated with AA or enzalutamide between January 2010 and June 2021 were included in this study. The most recently examined complete blood count values in the 1-month period before treatment were used for calculating PIV. The relationship between overall survival (OS) and PIV was evaluated by multivariate analysis. By using PIV and lactate dehydrogenase (LDH) levels which had shown survival effect at multivariate analysis, PIV-LDH combined score was established.

RESULTS

A total of 114 patients were included in this study. At the median follow-up of 34.6 months (95% confidence interval [CI]: 32.4-36.8), the median OS was 21 months (95% CI: 17.6-21.3). The median OS in the low-PIV group was significantly higher than in the high-PIV group (34.4 months (95% CI: 21.3-47.5) vs. 14.3 months (95% CI: 10.0-18.7), p < 0.001). In the multivariate analysis for OS, high PIV (hazard ratio [HR]: 1.86, 95% CI: 1.11-3.13, p = 0.018) and LDH value 1.5 times the upper limit of normal and above (HR: 3.65 95%, CI: 1.86-7.16, p < 0.001) were associated with shorter OS. When survival analysis was performed according to the PIV-LDH combined score, the median OS was 34.4 months (95% CI: 22.2-46.6) in the low-risk group, 17.7 months (95% CI: 11.7-23.6) in the intermediate-risk group, and 8.4 months (95% CI: 5.1-11.7) in the high-risk group (p < 0.001). The C-index of the combined PIV-LDH score was higher than the C-index of PIV (0.65 vs. 0.61).

CONCLUSION

In this study, we demonstrated that PIV was an independent prognostic factor for OS in patients with mCRPC treated with AA or enzalutamide. Additionally, PIV-LDH combined score may be considered a promising composite peripheral blood-based biomarker to predict OS in those patients.

Evaluation of systemic inflammatory and nutritional indexes in locally advanced gastric cancer treated with adjuvant chemoradiotherapy after D2 dissection

BACKGROUND

Many studies have shown that the peripheral blood inflammatory index and nutritional index, such as the platelet lymphocyte ratio (PLR), neutrophil lymphocyte ratio (NLR), lymphocyte monocyte ratio (LMR), systemic inflammation response index (SIRI), pan-immune-inflammation value (PIV), systemic immune-inflammation index (SII), and prognostic nutrition index (PNI), are independent prognostic factors for tumors. The present study aimed to investigate the prognostic role of these peripheral blood indexes before treatment in locally advanced gastric cancer (LAGC) treated with adjuvant chemoradiotherapy after D2 dissection.

METHODS

A total of 89 patients with LAGC who underwent D2 gastrectomy and adjuvant chemoradiotherapy at our hospital from 2010-2018 were eligible. Systemic inflammatory indicators before treatment were evaluated. Receiver operating characteristic curve (ROC), Kaplan-Meier analysis, and Cox regression were utilized for prognosis evaluation.

RESULTS

The median follow-up time was 29.1 (4.1-115.8) months. The overall survival at 3 years (OS) and the disease-free survival (DFS) were 78.9% and 59.1%, respectively. According to the ROC curve for 3-year DFS, the best cut-off values of pre-treatment NLR, PLR, LMR, SII, SIRI, PIV and PNI were 1.7, 109.3, 2.9, 369.2, 0.58, 218.7, and 48, respectively. Multivariate Cox regression analysis showed that NLR was an independent prognostic factor for DFS (HR 2.991, 95%CI 1.085-8.248, P = 0.034). Kaplan-Meier analysis showed that a higher NLR (>1.70) was significantly associated with a poorer OS (3-year OS: 68.8% vs 92.9%, P = 0.045) and DFS (3-year DFS: 47.5% vs 80.9%, P = 0.005). In terms of the free locoregional recurrence rate (LRR), the prognosis of patients with high NLR was also significantly worse than those with low NLR (70.2% vs 96.0%, P = 0.017). Paraaortic lymph nodes were the most common site of LRR (7/14 patients). The seven cases of paraaortic lymph node metastasis occurred in patients with high NLR.

CONCLUSIONS

In our retrospective analysis, we found that pretreatment NLR could serve as a prognostic factor for survival in LAGC treated with adjuvant chemoradiotherapy after D2 dissection, especially for the prediction of LRR and paraaortic lymph node metastasis. Prospective studies are needed to confirm our findings.

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

Simple Summary

In recent years, prognosis of non-small cell lung cancer (NSCLC) patients significantly improved thanks to the introduction of tyrosine kinase inhibitors (TKIs) in clinical practice. ALK-rearranged NSCLC patients benefit from treatment with ALK inhibitors (ALK-i), which have shown a greater efficacy and a better intracranial activity than chemotherapy. Comparative studies between next-generation ALK-i are still lacking and clinicians are looking for reliable tools to determine which drug suits best for each patient. The aim of this review is to deepen the role of clinical and pathological characteristics influencing patients’ prognosis during treatment with ALK-i and to provide an overview of molecular mechanisms of ALK-i resistance. In this setting, liquid biopsy may play an important role in predicting tumor response and monitoring resistance mutations. We will summarize ongoing trials developing new ALK-i or combinations between ALK-i and other agents, which may represent future scenarios in the field of NSCLC research.

Abstract

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.

Platelet-to-lymphocyte ratio associated with the clinicopathological features and prognostic value of breast cancer: A meta-analysis

OBJECTIVE

The association of platelet-to-lymphocyte ratio (PLR) with the clinicopathological features and prognosis in patients with breast cancer was evaluated.

METHOD

Related studies were searched from PubMed, Embase, Cochrane Library, and Web of Science up to July 1, 2021. Then, basic characteristic and prognostic data were extracted from the included studies. We synthesized and compared primary outcomes such as overall survival. Subgroups analyses in pathology, geographical area, follow-up time, and sample size were conducted. The pooled hazard ratio (HR), odds ratio (OR), and 95% confidence interval (CI) served as measures to assess the relationship of PLR with prognosis and clinicopathological features of breast cancer patients. After literature retrieval and selection, 20 studies with 7484 patients were included in this meta-analysis.

RESULTS

High PLR was significantly related to poor overall survival (HR = 1.88; 95% CI 1.61, 2.19; P < 0.001) in breast cancer patients. Also, high PLR was associated with lymph node metastasis (LNM) (OR = 1.82; 95% CI 1.32, 2.52; P < 0.001), advanced tumor-node-metastasis (TNM) stage (OR = 1.89; 95% CI 1.25, 2.87; P = 0.003), and distant metastasis (OR = 1.76; 95% CI 1.14, 2.72; P = 0.01) in breast cancer. The stability and reliability of results in this meta-analysis were confirmed by sensitivity analysis.

CONCLUSION

Elevated PLR is related to a poor prognosis and a higher risk of LNM, advanced TNM stage, and distant metastasis in breast cancer patients. Therefore, PLR can be identified as a biomarker with potential prognostic value in breast cancer.

Pan-immune-inflammation value is associated with the clinical stage of colorectal cancer

Objective

We investigated the clinical significance of preoperative pan-immune-inflammation value (PIV) in patients with colorectal cancer (CRC).

Methods

In this retrospective study, 366 cases who underwent surgery for CRC were enrolled. Their clinical data were collected. PIV was calculated with the formula PIV = [neutrophil count (109/L)× platelet count (109/L) × monocyte count (109/L) /lymphocyte count (109/L). Patients were divided into high PIV (&gt; median PIV) and low PIV (&lt; median PIV) groups. The relationship between PIV and clinicopathological features of CRC was investigated. Receiver operating characteristic (ROC) curve was plotted to indicate the value of immune-inflammatory biomarkers (IIBs) in predicting the TNM stage of CRC, and the area under the curve (AUC) was calculated to evaluate the actual clinical value of IIBs. AUC &gt; 0.5 and closer to 1 indicated the better predictive efficacy. The influencing factors of PIV in CRC were analyzed.

Results

We found that PIV was positively correlated with tumor size (r = 0.300, p &lt; 0.05), carcinoembryonic antigen (CEA) (r = 0.214, p &lt; 0.05) and carbohydrate antigen 125 (CA-125) (r = 0.249, p &lt; 0.05), but negatively correlated with albumin (Alb) (r = −0.242, p &lt; 0.05). PIV was significantly different in patients with different tumor locations (left or right), surgical methods (laparotomy versus laparoscopic surgery) (p &lt; 0.05), and patients with different pathological T stages, N-stage and TNM stages (p &lt; 0.05). ROC curve analysis of IIBs showed the AUC of PIV was greater than other markers when combined with CEA or carbohydrate antigen 19–9 (CA19–9). Multivariate regression analysis identified T stage, CEA, Alb, and tumor size as the independent influential factors of PIV in CRC.

Conclusion

PIV is associated with the tumor stage in patients with CRC, which may be useful in preoperative assessment of CRC.

Predictive Biomarkers of Response to Neoadjuvant Chemotherapy in Breast Cancer: Current and Future Perspectives for Precision Medicine

Pathological complete response (pCR) after neoadjuvant chemotherapy in patients with early breast cancer is correlated with better survival. Meanwhile, an expanding arsenal of post-neoadjuvant treatment strategies have proven beneficial in the absence of pCR, leading to an increased use of neoadjuvant systemic therapy in patients with early breast cancer and the search for predictive biomarkers of response. The better prediction of response to neoadjuvant chemotherapy could enable the escalation or de-escalation of neoadjuvant treatment strategies, with the ultimate goal of improving the clinical management of early breast cancer. Clinico-pathological prognostic factors are currently used to estimate the potential benefit of neoadjuvant systemic treatment but are not accurate enough to allow for personalized response prediction. Other factors have recently been proposed but are not yet implementable in daily clinical practice or remain of limited utility due to the intertumoral heterogeneity of breast cancer. In this review, we describe the current knowledge about predictive factors for response to neoadjuvant chemotherapy in breast cancer patients and highlight the future perspectives that could lead to the better prediction of response, focusing on the current biomarkers used for clinical decision making and the different gene signatures that have recently been proposed for patient stratification and the prediction of response to therapies. We also discuss the intratumoral phenotypic heterogeneity in breast cancers as well as the emerging techniques and relevant pre-clinical models that could integrate this biological factor currently limiting the reliable prediction of response to neoadjuvant systemic therapy.

Circulating inflammatory cells in patients with metastatic breast cancer: Implications for treatment

Adaptive and innate immune cells play a crucial role as regulators of cancer development.

Inflammatory cells in blood flow seem to be involved in pro-tumor activities and contribute to breast cancer progression. Circulating lymphocyte ratios such as the platelet-lymphocytes ratio (PLR), the monocyte-lymphocyte ratio (MLR) and the neutrophil-lymphocyte ratio (NLR) are new reproducible, routinely feasible and cheap biomarkers of immune response. These indexes have been correlated to prognosis in many solid tumors and there is growing evidence on their clinical applicability as independent prognostic markers also for breast cancer.

In this review we give an overview of the possible value of lymphocytic indexes in advanced breast cancer prognosis and prediction of outcome. Furthermore, targeting the immune system appear to be a promising therapeutic strategy for breast cancer, especially macrophage-targeted therapies. Herein we present an overview of the ongoing clinical trials testing systemic inflammatory cells as therapeutic targets in breast cancer.

Prognostic value of neutrophil-to-lymphocyte ratio for patients with triple-negative breast cancer: A meta-analysis

We aimed to evaluate the prognostic role of the neutrophil-to-lymphocyte ratio (NLR) in patients with triple-negative breast cancer (TNBC). We searched the PubMed Database, Cochrane Library, Web of science, and Embase. Overall survival (OS), disease-free survival (DFS), and hazard ratio (HR) were the endpoints of the study. Eleven studies involving 2355 patients with TNBC were included in this meta-analysis. Among them, 10 studies involving 2069 patients with TNBC investigated the role of NLR in predicting OS; elevated NLR was associated with poor prognosis (hazard ratio [HR]: 2.48, 95% confidence interval [CI]: 2.03-3.03, P < 0.001). Ten studies involving 2054 patients with TNBC explored the role of NLR in predicting DFS; elevated NLR was associated with a significantly worse prognosis with a pooled HR of 2.20 (95% CI: 1.88-2.58, P < 001). This meta-analysis suggests that patients with TNBC who have a higher NLR have poorer prognoses. As a clinical parameter that we can easily obtain, NLR might be a potential predictor of patients' survival, and may be useful for physicians' treatment decisions.

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.

The relationship between pan-immune-inflammation value and survival outcomes in patients with metastatic renal cell carcinoma treated with nivolumab in the second line and beyond: a Turkish oncology group kidney cancer consortium (TKCC) study

BACKGROUND

Pan-immune-inflammation value (PIV) is an easily accessible immune marker based on peripheral blood to estimate prognosis in patients with cancer. This study evaluates the prognostic value of PIV in patients with metastatic renal cell carcinoma (mRCC) treated with nivolumab.

METHODS

In this retrospective cohort study, patients with mRCC treated with nivolumab in the second line and beyond were selected from the Turkish Oncology Group Kidney Cancer Consortium (TKCC) database. PIV was calculated using the following formula: neutrophil (10³/mm³) x monocyte (10³/mm³) x platelet (10³/mm³)/lymphocyte (10³/mm³).

RESULTS

A total of 152 patients with mRCC were included in this study. According to cut-off value for PIV, 77 (50.7%) and 75 (49.3%) patients fell into PIV-low ([Formula: see text] 372) and PIV-high (> 372) groups, respectively. In multivariate analysis, PIV-high (HR: 1.64, 95% CI 1.04-2.58, p = 0.033 for overall survival (OS); HR: 1.55, 95% CI 1.02-2.38, p = 0.042 for progression-free survival (PFS)) was independent risk factor for OS and PFS after adjusting for confounding variables, such as performance score, the International mRCC Database Consortium (IMDC) risk score, and liver metastasis.

CONCLUSION

This study established that pre-treatment PIV might be a prognostic biomarker in patients with mRCC treated with nivolumab in the second line and beyond.