Systemic immune-inflammation index predicting chemoradiation resistance and poor outcome in patients with stage III non-small cell lung cancer

Prognostic value of neutrophil-to-lymphocyte ratio change in patients with locally advanced non-small cell lung cancer treated with thoracic radiotherapy

In prior investigations, a correlation was established between patient outcomes in locally advanced non-small cell lung cancer (LA-NSCLC) following thoracic irradiation and parameters, such as pre/post-treatment neutrophil-to-lymphocyte ratio (NLR) and NLR change (ΔNLR). However, these parameters could potentially be influenced by radiation-related variables, such as gross tumor volume (GTV). The primary aim of this study was to elucidate the factors impacting post-treatment NLR and ΔNLR and to further assess their prognostic relevance. In this retrospective study, a cohort of 188 LA-NSCLC patients who underwent thoracic radiation between 2012 and 2017 was assessed. The calculation of pre/post-treatment NLR involved the use of absolute neutrophil and lymphocyte counts. ΔNLR was defined as the difference between post- and pre-treatment NLR values. To assess the relationships between various variables and overall survival (OS), local progression-free survival (LPFS), and distant metastasis-free survival (DMFS), the Kaplan-Meier technique and Cox proportional hazards regression were employed. Additionally, Spearman's rank correlation analysis was carried out to investigate correlations between the variables. The analysis revealed that both post-treatment NLR (r = 0.315, P < 0.001) and ΔNLR (r = 0.156, P = 0.032) were associated with GTV. However, OS, LPFS, and DMFS were not independently correlated with pre/post-treatment NLR. ΔNLR, on the other hand, exhibited independent associations with OS and DMFS (HR = 1.054, P = 0.020, and P = 0.046, respectively). Elevated ΔNLR values were linked to poorer OS (P = 0.023) and DMFS (P = 0.018) in the Kaplan-Meier analysis. Furthermore, when stratifying by GTV, a higher ΔNLR remained to be associated with worse OS and DMFS (P = 0.047 and P = 0.035, respectively) in the GTV ≤ 67.41 cm3 group, and in the GTV > 67.41 cm3 group (P = 0.028 and P = 0.042, respectively), highlighting ΔNLR as the sole independent predictive factor for survival and metastasis, irrespective of GTV.

Prognostic significance of systemic immune inflammatory index in NSCLC: a meta-analysis

Aim: The aim of this meta-analysis was to investigate the relationship between the baseline systemic immune inflammatory index (SII) and prognosis in patients with NSCLC. Materials & methods: The relation between pretreatment SII and overall survival, disease-free survival, cancer-specific survival, progression-free survival and recurrence-free survival in NSCLC patients was analyzed combined with hazard ratio and 95% CI. Results: The results showed that high SII was significantly correlated with overall survival and progression-free survival of NSCLC patients, but not with disease-free survival, cancer-specific survival and recurrence-free survival. Conclusion: The study suggests that a higher SII has association with worse prognosis in NSCLC patients. PROSPERO registration number: CRD42022336270.

Clinical significance of the advanced lung cancer inflammation index in patients with limited-stage small cell lung cancer treated with chemoradiotherapy

The aim of the study was to investigate the prognostic significance of the advanced lung cancer inflammation index (ALI) in patients with limited-stage small-cell lung cancer (LS-SCLC) undergoing definite chemo-radiotherapy (CRT). We included 87 patients with LS-SCLC from South Korea, treated between 2005 and 2019 with definite CRT. ALI was calculated using body mass index, serum albumin, and neutrophil-lymphocyte ratio. We categorized 38 patients into the high ALI group (ALI ≥ 44.3) and 48 into the low ALI group (ALI < 44.3). Patients in the high ALI group exhibited longer overall survival (OS) than patients in the low ALI group. In multivariate analysis, prophylactic cranial irradiation (hazard ratio [HR] = 0.366, 95% confidence interval [CI] 0.20-0.66, P = 0.0008), and high ALI (HR = 0.475, 95% CI 0.27-0.84, P = 0.0103) were identified as independent prognostic factors for predicting better OS. Notably, a high ALI score was particularly indicative of longer survival in patients treated with the combination of etoposide and cisplatin. In conclusion, this study demonstrated that a high pretreatment ALI was significantly associated with better OS in patients with LS-SCLC undergoing definite CRT. This suggests that ALI could be a useful tool for predicting prognosis and guiding chemotherapy regimen selections in clinical practice for LS-SCLC.

Advances in systemic immune inflammatory indices in non-small cell lung cancer: A review

Lung cancer is one of the most prevalent cancers globally, with non-small cell lung cancers constituting the majority. These cancers have a high incidence and mortality rate. In recent years, a growing body of research has demonstrated the intricate link between inflammation and cancer, highlighting that inflammation and cancer are inextricably linked and that inflammation plays a pivotal role in cancer development, progression, and prognosis of cancer. The Systemic Immunoinflammatory Index (SII), comprising neutrophil, lymphocyte, and platelet counts, is a more comprehensive indicator of the host's systemic inflammation and immune status than a single inflammatory index. It is widely used in clinical practice due to its cost-effectiveness, simplicity, noninvasiveness, and ease of acquisition. This paper reviews the impact of SII on the development, progression, and prognosis of non-small cell lung cancer.

The Systemic Inflammation Index: A New Candidate Minor Criterion in the Diagnosis of Polycythemia Vera

AIM

To investigate inflammation indices and erythropoietin levels for their potential role in distinguishing polycythemia vera from secondary polycythemia and to compare different parameter combinations in terms of the diagnostic accuracy.

METHODS

This retrospective cohort was created from patients assessed for polycythemia from January 2020 to December 2023. Polycythemia vera diagnosis was made according to the 2016 World Health Organization criteria (n = 145). Those who did not fulfill the criteria were defined as having secondary polycythemia (n = 84).

RESULTS

The neutrophil lymphocyte ratio, platelet lymphocyte ratio and systemic immune-inflammation index were significantly higher in the polycythemia vera group (p < 0.001 for all). Erythropoietin had the highest area under the curve in the analysis to distinguish groups, followed by the systemic immune-inflammation index. The platelet lymphocyte ratio (≥135) had the highest specificity to detect polycythemia vera, followed closely by the systemic immune-inflammation index. The sensitivity for polycythemia vera detection was highest with the erythropoietin and systemic immune-inflammation index combination, followed by erythropoietin and the neutrophil lymphocyte ratio. All the single and combinatory variables exhibited significant performance in predicting polycythemia vera after adjusting for age and sex. However, the erythropoietin and systemic immune-inflammation index combination had the highest odds ratio, followed by erythropoietin alone.

CONCLUSION

These are promising findings supporting the usability of these biomarkers, especially the systemic immune-inflammation index, as minor criteria in the diagnosis of polycythemia vera. It is especially crucial to note that using erythropoietin in combination with these markers may improve diagnostic accuracy.

Systemic immune-inflammatory indicators and bone mineral density in chronic kidney disease patients: A cross-sectional research from NHANES 2011 to 2018

BACKGROUND

The purpose of this study was to look at the relationship between the Systemic Immune Inflammatory Index (SII) and bone mineral density (BMD) in the pelvis, left upper and lower limbs, lumbar spine, thoracic spine, and trunk in a chronic kidney disease (CKD) population in the United States.

METHODS

The National Health and Nutrition Examination Survey (2011-2016) yielded 2302 people with CKD aged >18 years. CKD was defined as eGFR less than 90 ml/min/1.73 m2 or eGFR greater than 90 ml/min/1.73 m2 with urine ACR greater than 30 mg/L.SII was calculated as PC * (NC / LC) from platelet count (PC), neutrophil count (NC), and lymphocyte count (LC). Multiple logistic regression was used to examine the relationship between BMD and SII at different sites in CKD patients, smoothed curve-fitting and generalized weighting models were used to investigate non-linear relationships, and a two-tailed linear regression model was used to find potential inflection points in the model.

RESULTS

We discovered a negative correlation between SII and pelvic BMD among 2302 participants after controlling for gender, age, and race [β = -0.008; 95% confidence value -0.008; 95% confidence interval (CI) -0.014, -0.002]. Lower PEBMD was related to increasing SII (trend p = 0.01125). After additional correction, only pelvic BMD remained adversely linked with SII [value -0.006; 95% CI -0.012, -0.000, p = 0.03368]. Smoothed curve fitting revealed a consistent inverse relationship between SII and pelvic BMD. Further stratified analyses revealed a substantial positive negative connection between SII and pelvic BMD in individuals who did not have hypertension, diabetes, a BMI of more than 30 kg/m2, or stage 2 CKD. The connection between SII and PEBMD in people without diabetes revealed a strong inverted U-shaped curve.

CONCLUSION

In individuals with CKD in the United States, there was a negative connection between the systemic immunoinflammatory index (SII) and pelvic BMD. The SII might be a low-cost and simple test for CKD-related BMD loss.

Association of two novel systemic inflammatory biomarkers and frailty based on NHANES 2007-2018

Background

Frailty is a significant concern in the field of public health. However, currently, there is a lack of widely recognized and reliable biological markers for frailty. This study aims to investigate the association between systemic inflammatory biomarkers and frailty in the older adult population in the United States.

Methods

This study employed data from the National Health and Nutrition Examination Survey (NHANES) spanning 2007 to 2018 and conducted a rigorous cross-sectional analysis. We constructed weighted logistic regression models to explore the correlation between the Systemic Immune-Inflammation Index (SII), Systemic Inflammatory Response Index (SIRI), and frailty in the population aged 40 to 80 years. Using restricted cubic spline (RCS), we successfully visualized the relationship between SII, SIRI, and frailty. Finally, we presented stratified analyses and interaction tests of covariates in a forest plot.

Results

This study involved 11,234 participants, 45.95% male and 54.05% female, with an average age of 64.75 ± 0.13 years. After adjusting for relevant covariates, the weighted logistic regression model indicated an odds ratio (OR) and 95% confidence interval(CI) for the correlation between frailty and the natural logarithm (ln) transformed lnSII and lnSIRI as 1.38 (1.24-1.54) and 1.69 (1.53-1.88), respectively. Subsequently, we assessed different levels of lnSII and lnSIRI, finding consistent results. In the lnSII group model, the likelihood of frailty significantly increased in the fourth quartile (OR = 1.82, 95% CI: 1.55-2.12) compared to the second quartile. In the lnSIRI group model, the likelihood of frailty significantly increased in the third quartile (OR = 1.30, 95% CI: 1.10-1.53) and fourth quartile (OR = 2.29, 95% CI: 1.95-2.70) compared to the second quartile. The interaction results indicate that age and income-to-poverty ratio influence the association between lnSIRI and frailty. RCS demonstrated a nonlinear relationship between lnSII, lnSIRI, and frailty.

Conclusion

The results of this cross-sectional study indicate a positive correlation between systemic inflammatory biomarkers (SII, SIRI) and frailty.

Nanoparticles targeting mutant p53 overcome chemoresistance and tumor recurrence in non-small cell lung cancer

Non-small cell lung cancer (NSCLC) shows high drug resistance and leads to low survival due to the high level of mutated Tumor Protein p53 (TP53). Cisplatin is a first-line treatment option for NSCLC, and the p53 mutation is a major factor in chemoresistance. We demonstrate that cisplatin chemotherapy increases the risk of TP53 mutations, further contributing to cisplatin resistance. Encouragingly, we find that the combination of cisplatin and fluvastatin can alleviate this problem. Therefore, we synthesize Fluplatin, a prodrug consisting of cisplatin and fluvastatin. Then, Fluplatin self-assembles and is further encapsulated with poly-(ethylene glycol)-phosphoethanolamine (PEG-PE), we obtain Fluplatin@PEG-PE nanoparticles (FP NPs). FP NPs can degrade mutant p53 (mutp53) and efficiently trigger endoplasmic reticulum stress (ERS). In this study, we show that FP NPs relieve the inhibition of cisplatin chemotherapy caused by mutp53, exhibiting highly effective tumor suppression and improving the poor NSCLC prognosis.

Development and validation of a prognostic nomogram model in locally advanced NSCLC based on metabolic features of PET/CT and hematological inflammatory indicators

BACKGROUND

We combined the metabolic features of 18F-FDG-PET/CT and hematological inflammatory indicators to establish a predictive model of the outcomes of patients with locally advanced non-small cell lung cancer (LA-NSCLC) receiving concurrent chemoradiotherapy.

RESULTS

A predictive nomogram was developed based on sex, CEA, systemic immune-inflammation index (SII), mean SUV (SUVmean), and total lesion glycolysis (TLG). The nomogram presents nice discrimination that yielded an AUC of 0.76 (95% confidence interval: 0.66-0.86) to predict 1-year PFS, with a sensitivity of 63.6%, a specificity of 83.3%, a positive predictive value of 83.7%, and a negative predictive value of 62.9% in the training set. The calibration curves and DCA suggested that the nomogram had good calibration and fit, as well as promising clinical effectiveness in the training set. In addition, survival analysis indicated that patients in the low-risk group had a significantly longer mPFS than those in the high-risk group (16.8 months versus 8.4 months, P < 0.001). Those results were supported by the results in the internal and external test sets.

CONCLUSIONS

The newly constructed predictive nomogram model presented promising discrimination, calibration, and clinical applicability and can be used as an individualized prognostic tool to facilitate precision treatment in clinical practice.

Association between systemic immune-inflammation index and insulin resistance and mortality

The role of inflammation in disease promotion is significant, yet the precise association between a newly identified inflammatory biomarker and insulin resistance (IR) and mortality remains uncertain. We aim to explore the potential correlation between systemic immune-inflammation index (SII) and these factors. We used data from 2011 to 2016 of National Health and Nutrition Examination Survey, and multivariate logistic regression and restricted cubic spline were employed. Subgroup and interaction analysis were conducted to recognize the consistency of the results. The association between SII and mortality was described by survival analysis. 6734 participants were enrolled, of whom 49.3% (3318) exhibited IR and 7.02% experienced mortality. Multivariate logistic regression revealed that individuals in the highest quartile (Q4) of SII had a significantly increased risk of IR compared to those in the lowest quartile (Q1). We then identified a linear association between SII and IR with an inflection point of 407, but may be influenced by gender. Similarly, compared to Q1, people whose SII at Q4 showed a higher all-cause and cardiovascular mortality. It showed a significant association between SII and both all-cause and cardiovascular mortality, but the results need to be interpreted with caution.

Association of systemic immunity-inflammation index with metabolic syndrome in U.S. adult: a cross-sectional study

BACKGROUND

Metabolic syndrome (MetS) is a pathological condition characterized by the abnormal clustering of several metabolic components and has become a major public health concern. We aim to investigate the potential link of Systemic immunity-inflammation index (SII) on MetS and its components.

METHODS AND RESULT

Weighted multivariable logistic regression was conducted to assess the relationship between SII and MetS and its components. Restricted cubic spline (RCS) model and threshold effect analysis were also performed. A total of 6,999 U.S. adults were enrolled. Multivariate model found that SII were positively associated with MetS (OR = 1.18;95CI%:1.07-1.30) and hypertension (OR = 1.22; 95CI%:1.12-1.34) in a dose-dependent manner. When SII was converted into a categorical variable, the risk of MetS increased by 36% and the risk of hypertension increased by 53% in the highest quantile of SIIs. The RCS model confirmed linear associations between SII and MetS, as well as a non-linear association between SII and certain components of MetS, including hypertension, hyperglycemia, low HDL, and hyperlipidemia. Meanwhile, the relationship between SII and hypertension presents a J-shaped curve with a threshold of 8.27, above which the risk of hypertension increases. Furthermore, in MetS and hypertension, age, sex, body mass index (BMI), and race were not significantly associated with this positive association based on subgroup analyses and interaction tests(p for interaction > 0.05).

CONCLUSIONS

The present study indicated that there was a higher SII association with an increased risk of MetS and hypertension in adults. However, further prospective cohort studies are required to establish a causal relationship between SII and MetS, as well as its components.

The association of systemic inflammatory biomarkers with non-alcoholic fatty liver disease: a large population-based cross-sectional study

Purpose

The aim of this study was to explore the relationship between non-alcoholic fatty liver disease (NAFLD) and the two blood inflammatory markers including the systemic immune-inflammation (SII) index, and the system inflammation response index (SIRI).

Methods

The National Health and Nutrition Examination Survey data between the year of 2017-2018 was used for this cross-sectional study. In order to analyze the association of SII index, and SIRI and risk of NAFLD, we used multivariable logistic regression models, restricted cubic spline (RCS) plot, and subgroup analysis to analyze the data.

Results

In total, there were 1,199 individuals who participated in the survey. As shown by the RCS plot, SII index, and SIRI were linked with NAFLD risk in a U-shaped pattern. With regard to known confounding variables, when comparing the lowest quartile, the odds ratio with 95 % confidence interval for prevalence of NAFLD across the quartiles of SII index and SIRI were (0.89 (0.57, 1.41), 0.56 (0.35, 0.89) and 1.01 (0.64, 1.59)), and (0.77 (0.48, 1.23), 0.79 (0.50, 1.24) and 0.94 (0.60, 1.47)), respectively. Additionally, SII index, and SIRI and NAFLD risk also were U-curve correlated among the participants in age ≥60 years, female, without hypertension, and BMI of ≥30 kg/m2.

Conclusions

There was a U-shaped association of SII index and SIRI with prevalence of NAFLD, indicating that SII index and SIRI should be monitored dynamically.

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 biomarkers dynamics reflect treatment response and predict prognosis in non-small cell lung cancer patients with neoadjuvant immunotherapy

Neoadjuvant immunotherapy has significantly changed the therapeutic approach for treating patients with surgically resectable non-small cell lung cancer (NSCLC). Here, peripheral blood inflammation-based biomarkers as well as previously less focused eosinophil fraction, modified Glasgow prognostic score (mGPS), and prognostic nutritional index (PNI) were systematically included to comprehensively analyze their potential in predicting neoadjuvant immunotherapy efficacy and prognosis. We enrolled 189 patients (94 in training and 95 in validation cohorts) with stage I-III B surgically resectable NSCLC treated with neoadjuvant immunotherapy from the National Cancer Center of China. Baseline and post-treatment eosinophils fraction, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), monocyte-to-lymphocyte ratio (MLR), PNI, mGPS, and their changes were calculated and analyzed for correlation with neoadjuvant immunotherapy efficacy and prognosis. In patients in the major pathological response (MPR) group, the post-treatment eosinophil fraction was significantly high, and NLR, PLR, SII, and MLR were significantly lower compared to the non-MPR group in both the training and validation cohorts. The receiver operating characteristic curve showed that post-treatment, eosinophil fraction and SII and their changing were two of the most important factors. Univariate and multivariate logistic regression analyses showed that post-treatment eosinophil fraction, SII, mGPS, and ΔSII could independently predict MPR in patients treated with neoadjuvant immunotherapy. Survival analysis showed a significant correlation between high post-treatment NLR, PLR, SII, mGPS, and their changes in ΔNLR and ΔSII elevation with poor overall survival and event-free survival of patients. Our results suggest that inflammatory biomarkers could predict the patient's response to neoadjuvant immunotherapy and prognosis.

Quantitative CT parameters combined with preoperative systemic inflammatory markers for differentiating risk subgroups of thymic epithelial tumors

BACKGROUND

Thymic epithelial tumors (TETs) are the most common primary neoplasms of the anterior mediastinum. Different risk subgroups of TETs have different prognosis and therapeutic strategies, therefore, preoperative identification of different risk subgroups is of high clinical significance. This study aims to explore the diagnostic efficiency of quantitative computed tomography (CT) parameters combined with preoperative systemic inflammatory markers in differentiating low-risk thymic epithelial tumors (LTETs) from high-risk thymic epithelial tumors (HTETs).

METHODS

74 Asian patients with TETs confirmed by biopsy or postoperative pathology between January 2013 and October 2022 were collected retrospectively and divided into two risk subgroups: LTET group (type A, AB and B1 thymomas) and HTET group (type B2, B3 thymomas and thymic carcinoma). Statistical analysis were performed between the two groups in terms of quantitative CT parameters and preoperative systemic inflammatory markers. Multivariate logistic regression analysis was used to determine the independent predictors of risk subgroups of TETs. The area under curve (AUC) and optimal cut-off values were calculated by receiver operating characteristic (ROC) curves.

RESULTS

47 TETs were in LTET group, while 27 TETs were in HTET group. In addition to tumor size and CT value of the tumor on plain scan, there were statistical significance comparing in CT value of the tumor on arterial phase (CTv-AP) and venous phase (CTv-VP), and maximum enhanced CT value (CEmax) of the tumor between the two groups (for all, P < 0.05). For systemic inflammatory markers, HTET group was significantly higher than LTET group (for all, P < 0.05), including platelet-to-lymphocyte ratio (PLR), neutrophil-to-lymphocyte ratio (NLR) and systemic immune-inflammation index (SII). Multivariate logistic regression analysis showed that NLR (odds ratio [OR] = 2.511, 95% confidence interval [CI]: 1.322-4.772, P = 0.005), CTv-AP (OR = 0.939, 95%CI: 0.888-0.994, P = 0.031) and CTv-VP (OR = 0.923, 95%CI: 0.871-0.979, P = 0.008) were the independent predictors of risk subgroups of TETs. The AUC value of 0.887 for the combined model was significantly higher than NLR (0.698), CTv-AP (0.800) or CTv-VP (0.811) alone. The optimal cut-off values for NLR, CTv-AP and CTv-VP were 2.523, 63.44 Hounsfeld Unit (HU) and 88.29HU, respectively.

CONCLUSIONS

Quantitative CT parameters and preoperative systemic inflammatory markers can differentiate LTETs from HTETs, and the combined model has the potential to improve diagnostic efficiency and to help the patient management.

Impact of systemic inflammatory markers in patients with ALK-positive non-small cell lung cancer treated with crizotinib

OBJECTIVES

To evaluate the prognostic utility of inflammation-based prognostic scores in patients with ALK-positive metastatic or non-resectable non-small-cell lung cancer (NSCLC) treated with crizotinib.

PATIENTS AND METHODS

A total of 82 patients with ALK-positive metastatic or non-resectable NSCLC who received ALK TKI crizotinib were included. Pre-treatment modified Glasgow prognostic score (mGPS), prognostic nutritional index (PNI), and systemic immune-inflammation index (SII) were calculated. Multivariable logistic regression and Cox proportional hazards models were used to assess the impact of pretreatment mGPS, PNI, and SII on overall survival (OS), progression-free survival (PFS), and objective response rate (ORR).

RESULTS

The ORR was 77.2%, while 1-year OS and PFS rates were 95.0% and 93.5%, respectively. The univariate analysis revealed significantly higher 1-year PFS (89.4 vs. 64.4%, p=0.043) and OS (92.0 vs. 83.3%, p=0.01) rates in patients with low (<934.7) vs. high (≥934.7) SII scores. Multivariate analysis revealed that PNI ≥0.09 was a significant determinant of poorer 1-year OS rates (hazard ratio [HR]: 2.46, 95% confidence interval [CI] 0.88-4.85, p=0.035). No significant difference was observed in survival rates according to gender, age, smoking status, prior lines of therapy, or mGPS scores, while higher mGPS scores (odds ratio [OR]: 0.1, 95%CI 0.16-1.04; p=0.009) and higher PNI scores (OR: 0.16, 95% CI 0.02-0.55; p=0.035) were associated with poorer ORR.

CONCLUSION

Our findings indicate the prognostic significance of PNI and SII in terms of survival outcome and the impact of mGPS and PNI on treatment response in patients with ALK-positive NSCLC treated with crizotinib.

Prognostic value of the systemic immune-inflammation index in patients with upper tract urothelial carcinoma after radical nephroureterectomy

BACKGROUND

To investigate the prognostic significance of the systemic immune-inflammation index (SII) for patients with upper tract urothelial carcinoma (UTUC) after radical nephroureterectomy (RNU) and develop nomogram models for predicting overall survival (OS), intravesical recurrence (IVR), and extra-urothelial recurrence (EUR).

METHODS

We retrospectively studied the clinical and pathological features of 195 patients who underwent RNU for UTUC. All patients were randomly divided into a training cohort (99 cases) and a validation cohort (96 cases). The training cohort was used to develop nomogram models, and the models were validated by the validation cohort. The least absolute shrinkage and selection operator (LASSO) regression and Cox regression were performed to identify independent predictors. The concordance index (C-index), receiver operator characteristics (ROC) analysis, and calibration plot were used to evaluate the reliability of the models. The clinical utility compared with the pathological T stage was assessed using the net reclassification index (NRI), integrated discrimination improvement (IDI), and decision curve analysis (DCA).

RESULTS

SII was an independent risk factor in predicting OS and EUR. The C-index values of the nomogram predicting OS, IVR, and EUR were 0.675, 0.702, and 0.756 in the training cohort and 0.715, 0.756, and 0.713 in the validation cohort. A high level of SII was correlated with the invasion of the mucosa, muscle layer of the ureter, nerves, vessels, and fat tissues.

CONCLUSION

We developed nomogram models to predict the OS, IVR, and EUR of UTUC patients. The efficacy of these models was substantiated through internal validation, demonstrating favorable discrimination, calibration, and clinical utility. A high level of SII was associated with both worse OS and shorter EUR-free survival.

Association between systemic immune-inflammation index and metabolic syndrome and its components: results from the National Health and Nutrition Examination Survey 2011-2016

BACKGROUND

Metabolic syndrome (MetS), a worldwide public health problem, affects human health and quality of life in a dramatic manner. A growing evidence base suggests that MetS is strongly associated with levels of systemic immune inflammation. The present study aimed to investigate the possible relationship between the systemic immune-inflammation index (SII), a novel inflammatory marker, and MetS to provide data support for effective MetS prevention by reducing the systemic inflammatory response.

METHODS

We included adult participants with complete SII and MetS information from the 2011-2016 National Health and Nutrition Examination Survey (NHANES). MetS was defined as using the criteria developed by the Adult Treatment Program III of the National Cholesterol Education Program. The formula for SII was as follows: SII = platelet counts × neutrophil counts/ lymphocyte counts. Weighted linear regression was used to assess differences in variables across SII quartile groups after the SII score was divided into 4 quartiles. The independent interaction between SII and MetS was investigated using weighted multivariate logistic regression analysis and subgroup analysis, and the relationship between SII levels and 5 particular MetS items was further explored in depth.

RESULTS

A total of 12,402 participants, 3,489 of whom were diagnosed with MetS, were included in this study. After correcting for covariates, the results of a logistic regression of multistage weighted complex sampling data revealed that participants with higher SII scores had a higher chance of developing MetS (odds ratio (OR) = 1.33, 95% confidence interval (CI): 1.14-1.55) and that SII levels could be used as an independent risk factor to predict that likelihood of MetS onset. In the Q1-Q4 SII quartile group, the risk of developing MetS was 1.33 times higher in the Q4 group, which had the highest level of systemic immune inflammation than in the Q1 group. After adjusting for all confounding factors, SII scores were found to have a negative correlation with high-density lipoprotein cholesterol (OR = 1.29; 95% CI, 0.99-1.67, P = 0.056) and a significant positive correlation with waist circumference (OR = 2.17; 95% CI, 1.65-2.87, P < 0.001) and blood pressure (BP) (OR = 1.65; 95% CI, 1.20-2.27, P = 0.003). Gender, age, and smoking status were shown to alter the positive association between SII and MetS in subgroup analyses and interaction tests (p for interaction < 0.05). Additionally, we demonstrated a nonlinear correlation between SII and MetS. The findings of the restricted cubic spline indicated that there was an inverted U-shaped association between SII and MetS.

CONCLUSIONS

Our findings imply that increased SII levels are related to MetS, and SII may be a simple and cost-effective method to identify individuals with MetS. Therefore, protective measures such as early investigation and anti-inflammatory interventions are necessary to reduce the overall incidence of MetS.

Immune Activation Effects at Different Irradiated Sites and Optimal Timing of Radioimmunotherapy in Patients with Extensive-Stage Small Cell Lung Cancer: a Real-World Analysis

BACKGROUND

In view of the limited data on radiotherapy (RT) combined with immunotherapy in patients with extensive-stage small cell lung cancer (ES-SCLC), this study aimed to identify the immune activation effect on different sites and the survival outcomes of radioimmunotherapy at different treatment stages.

METHODS

Forty-five patients diagnosed with ES-SCLC were included in this retrospective analysis. We collected the overall survival (OS) of the patients,, recorded the blood cell counts before, during, and after RT, and derived blood index ratios such as the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and systemic immune-inflammation index (SII). The datasets were analyzed using the Spearman rank correlation test, Kruskal-Wallis rank sum test and logistic regression.

RESULTS

Among the selected blood indices, the delta-NLR/PLR/Sll correlated with different irradiated organs, and the mean ranks of these three indices were the lowest in the brain-irradiated group during immunotherapy. Additionally, adjunct first-line immunotherapy with RT demonstrated a significant improvement compared to second- or third-line therapy and subsequent therapies.

CONCLUSION

Our findings suggest that compared to other organs, the strongest immune activation effect occurs with brain RT, and ES-SCLC patients who received radioimmunotherapy (RIT) earlier achieved higher OS rates.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

Association of Systemic Immune-Inflammation Index with Non-Alcoholic Fatty Liver Disease: A Population-Based Cross-Sectional Study

Background

The aim of this study was to explore the relationship between systemic immune-inflammation (SII) index with non-alcoholic fatty liver disease (NAFLD) in the general population of the United States (U.S.).

Methods

We conducted a cross-sectional study of subjects in the National Health and Nutrition Examination Survey 2017-2018. For the analysis of the association between SII index and risk of NAFLD, the restricted cubic spline (RCS) plot, we performed multivariable logistic regression models and subgroup analysis. In addition, generalized additive models with smooth functions were conducted for the relationship between the SII index and the ZJU index, the BARD score, and the NAFLD fibrosis score.

Results

There were a total of 1197 individuals in our study. Taking into account known confounding variables, compared with the lowest quartiles, the odds ratios with 95% confidence intervals for NAFLD across the quartiles were 0.923 (0.585, 1.455), 0.563 (0.351, 0.901), and 1.061 (0.669, 1.682), respectively. As shown by the RCS plot, the SII index was linked with NAFLD risk in a U-shaped pattern. Based on the results of subgroup analysis, SII index and NAFLD risk were U-curve correlated among participants in all age groups, male or female, with or without hypertension, with diabetes mellitus, and with a BMI of <30 or >30 kg/m2. The SII index was linearly positive with the ZJU index but negative with the NAFLD fibrosis score. However, the SII index and BARD score showed a trend of first decreasing, then increasing, and then decreasing.

Conclusion

The U-shaped relationships exist between SII index and risk of NAFLD, which highlighted that we should focus on the dynamic change of SII index.

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.

Evaluation of Predictive and Prognostic Importance of Lung Immune Prognostic Index in Locally Advanced Rectal Cancer Patients Treated With Neoadjuvant Chemoradiotherapy

OBJECTIVE

The systemic inflammatory response (SIR) is known as an important factor associated with tumorigenesis and tumor progression, and can be reflected by inflammatory markers. One of the markers that reflect this is the lung immune prognostic index (LIPI). It is based on a derived neutrophil-to-lymphocyte ratio (dNLR) and lactate dehydrogenase (LDH) level. We aimed to investigate the significance of LIPI in locally advanced rectal cancer (LARC) patients treated with neoadjuvant chemoradiotherapy (NACRT).

METHODS

In this retrospective study, we stratified the patients according to LIPI score as good LIPI and intermediate (int)/poor LIPI. According to pathological response to NACRT, we divided the patients into two groups as those with complete response (CR) or near-CR, and those with partial response (PR) or poor/no response. We classified CR and near-CR as good response. We evaluated the predictive and prognostic significance of LIPI for NACRT response, disease-free survival (DFS), and overall survival (OS) by univariate and multivariate analyses.

RESULTS

We included 137 patients in the results, with 72 (52.6%) having good LIPI and 65 (47.4%) having int/poor LIPI. The median follow-up period was 44.7 months (range: 10-105 months). Thirteen patients (18.0%) in the good LIPI group and 22 patients (34.0%) in the int/poor LIPI group achieved good response. In multivariate analysis, we found only the LIPI score as an independent risk factor (hazard ratio (HR): 2.4, p = 0.04) for NACRT response. Median DFS was 89.2 months (95% CI: 11.4-167.0) in the int/poor LIPI group; however, the DFS of all study populations and patients in the good LIPI group did not reach the median value. In multivariate analysis for DFS, we identified abdominoperineal resection (APR) (HR: 2.21, p = 0.02), presence of tumor deposit (HR: 2.96, p = 0.003), and int/poor LIPI score (HR: 2.07, p = 0.02) as separate risk variables. OS of all study populations and the patients in the LIPI groups did not reach the median value. In multivariate analysis for OS, we identified APR (HR: 2.74, p = 0.02), surgical margin positivity (HR: 12.94, p < 0.001), and adjuvant CT (HR: 0.20, p = 0.002) as separate risk variables for OS.

CONCLUSION

This is the first study investigating the predictive and prognostic significance of LIPI in LARC patients treated with NACRT. The results revealed that int/poor LIPI was associated with a higher rate of good response but shorter DFS compared to good LIPI. The baseline LIPI score serves as an easily accessible and useful prognostic index, and it has significant potential for making appropriate treatment decisions in LARC.

Systematic analysis between inflammation-related index and sex hormones in American adults: cross-sectional research based NHANES 2013-2016

Background

A series of novel inflammation-related indexes has been confirmed to be efficient indicators of human immune and inflammatory status, with great potential as predictors for a variety of diseases. However, the association between inflammation-related indexes and sex hormones in the general population remained uncertain.

Methods

We incorporated data from the NHANES 2013-2016 survey of American adults. On the basis of distribution and comparison analysis, we chose to undertake separate analyses of men and women (including premenopausal and postmenopausal groups). Multivariable weighted linear regression models, eXtreme Gradient Boosting (XGBoost) models, generalized linear analysis, stratified models, logistic regression models and sensitivity analysis were utilized to assess the relationships between inflammation-related indexes and sex hormones.

Results

Total 9372 participants out of 20146 were fitted into our research. We conducted separate gender analysis due to different distribution. Multivariable weighted linear regression indicated every component of the inflammation-related index was negatively correlated with at least one component of the male hormone indexes. However, SII, NLR, PPN, and NC were associated positively with female estradiol. XGBoost identify SII, PLR and NLR were the critical indexes on sex hormones. Inflammation-related indexes was associated with Testosterone deficiency in male and postmenstrual group and associated with Excessive Estradiol in premenstrual group. Finally, the subgroup analysis revealed that the association between sex hormones and inflammatory indicators was prominent in American adults over the age of 60 or those with BMI (>28 kg/m²).

Conclusion

In all, inflammation-related indexes act as independent risks associated with sex hormone alterations and metabolic disorder in both genders. Using multiple models, we revealed the relative importance of inflammation-related indexes. Subgroup analysis also identified the high-risk population. More prospective and experimental research should be conducted to validate the results.

Effect of Lymphopenia on Tumor Response and Clinical Outcomes Following Chemoradiotherapy in Stage III Non-Small Cell Lung Cancer

Background

Prior studies suggest lymphopenia, systemic immune-inflammatory index, and tumor response all impact clinical outcomes in Stage III NSCLC. We hypothesized that tumor response after CRT would be associated with hematologic metrics and might predict clinical outcomes.

Materials and Methods

Patients with stage III NSCLC treated at a single institution between 2011 and 2018 were retrospectively reviewed. Pre-treatment gross tumor volume (GTV) was recorded then reassessed at 1-4 months post-CRT. Complete blood counts before, during and after treatment were recorded. Systemic immune-inflammation index (SII) was defined as neutrophil × platelet/lymphocyte. Overall survival (OS) and progression free survival (PFS) were calculated using Kaplan-Meier estimates, and compared with Wilcoxon tests. A multivariate analysis of hematologic factors impacting restricted mean survival was then performed using pseudovalue regression, accounting for other baseline factors.

Results

106 patients were included. After median follow-up of 24 months, median PFS and OS were 16 and 40 months, respectively. Within the multivariate model, baseline SII was associated with OS (p = 0.046) but not PFS (p = 0.09), and baseline ALC correlated with both PFS and OS (p = 0.03 and p = 0.02, respectively). Nadir ALC, nadir SII, and recovery SII were not associated with PFS or OS.

Conclusion

In this cohort of patients with stage III NSCLC, baseline hematologic factors were associated with clinical outcomes including baseline ALC, baseline SII and recovery ALC. Disease response was not well correlated with hematologic factors or clinical outcomes.

Evaluation of C-reactive protein and fibrinogen in comparison to CEA and CA72-4 as diagnostic biomarkers for colorectal cancer

Carcinoembryonic antigen (CEA) and carbohydrate antigen 72-4 (CA72-4) are commonly used markers for colorectal cancer (CRC) in clinical applications. However, low positivity rate and sensitivity limits their clinical effectiveness. In this study, we explored the potential of C-reactive protein (CRP) and fibrinogen to improve the diagnostic efficiency of traditional biomarkers of CRC. The concentrations of CRP and fibrinogen in plasma were significantly higher in CRC patients compared with benign or healthy controls. The area under the ROC curves (AUCs) showed that the diagnostic efficacy of CRP and fibrinogen was 0.745 (95% CI: 0.712-0.779) and 0.699 (95% CI: 0.663-0.734), respectively. AUC increased to 0.750 (95% CI: 0.716-0.784) when CRP and fibrinogen were combined. It also further improved to 0.889 (95% CI: 0.866-0.913) when CRP and fibrinogen were integrated with CEA and CA72-4. Moreover, this combination increased the maximum area under AUC to 0.857 (95% CI: 0.830-0.883), which effective differentiated CRC from benign disease. Overall, this study found that CRP and fibrinogen were highly expressed in the plasma of CRC patients, suggesting their potential to improve the diagnostic efficiency of traditional biomarkers of CRC.

Combined systemic immune-inflammatory index and prognostic nutritional index predict outcomes in advanced non-small cell lung cancer patients receiving platinum-doublet chemotherapy

Background

Systemic immune-inflammatory index (SII) and prognostic nutritional index (PNI) could evaluate the therapeutic efficacy and prognosis in different tumors. However, no studies investigated the SII-PNI score to predict outcomes in non-small cell lung cancer (NSCLC) patients treated with platinum-doublet chemotherapy. The aim of this study was to investigate the SII-PNI score in predicting outcomes in non-small cell lung cancer (NSCLC) patients treated with platinum-doublet chemotherapy.

Materials and methods

Our study retrospectively analyzed clinical data from 124 patients with advanced NSCLC receiving platinum-doublet chemotherapy. The SII and PNI were calculated based on peripheral blood cell counts and serum albumin, and the optimal cut-off values were determined using receiver operating characteristic (ROC). All patients were divided into three groups according to the SII-PNI score. The association between the SII-PNI score and the clinicopathological characteristics of the patients was examined. The Kaplan-Meier and Cox regression models were used to assess progression-free survival (PFS)and overall survival (OS).

Results

There was no significant correlation between SII, PNI at baseline and chemotherapy response in patients with advanced NSCLC (p&gt;0.05). However, after receiving 4 cycles of platinum-doublet chemotherapy, the SII of the SD group (p=0.0369) and PD group (p=0.0286) was significantly higher than that of the PR group. At the same time, the PNI of the SD group (p=0.0112) and the PD group (p=0.0007) was significantly lower than that of the PR group. The PFS of patients with SII-PNI scores of 0, 1, and 2 were 12.0, 7.0, and 5.0 months, and the OS of patients with SII-PNI scores of 0, 1, and 2 were 34.0, 17.0, and 10.5 months, respectively. There was statistical significance among the three groups (all p &lt;0.001). Multivariate analyses showed that the chemotherapy response of progressive disease (PD) (HR, 3.508; 95% CI, 1.546-7.960; p=0.003) and SII-PNI score of 2 (HR, 4.732; 95% CI, 2.561-8.743; p &lt; 0.001) were independently associated with a shorter OS. The uses of targeted drugs (HR, 0.543; 95% CI, 0.329-0.898; p=0.017) and immune checkpoint inhibitors (HR, 0.218; 95% CI, 0.081-0.584; p=0.002) were protective factors for OS in patients with NSCLC.

Conclusion

Compared with baseline parameters, the correlation between SII, PNI after 4 cycles of chemotherapy and the chemotherapy effect was more significant. The SII-PNI score after 4 cycles of chemotherapy is an effective prognostic biomarker for advanced NSCLC patients treated with platinum-doublet chemotherapy. Patients with a higher SII-PNI score had a worse prognosis.

Prediction of Distant Metastases After Stereotactic Body Radiation Therapy for Early Stage NSCLC: Development and External Validation of a Multi-Institutional Model

INTRODUCTION

Distant metastases (DMs) are the primary driver of mortality for patients with early stage NSCLC receiving stereotactic body radiation therapy (SBRT), yet patient-level risk is difficult to predict. We developed and validated a model to predict individualized risk of DM in this population.

METHODS

We used a multi-institutional database of 1280 patients with cT1-3N0M0 NSCLC treated with SBRT from 2006 to 2015 for model development and internal validation. A Fine and Gray (FG) regression model was built to predict 1-year DM risk and compared with a random survival forests model. The higher performing model was evaluated on an external data set of 130 patients from a separate institution. Discriminatory performance was evaluated using the time-dependent area under the curve (AUC). Calibration was assessed graphically and with Brier scores.

RESULTS

The FG model yielded an AUC of 0.71 (95% confidence interval [CI]: 0.57-0.86) compared with the AUC of random survival forest at 0.69 (95% CI: 0.63-0.85) in the internal test set and was selected for further testing. On external validation, the FG model yielded an AUC of 0.70 (95% CI: 0.57-0.83) with good calibration (Brier score: 0.08). The model identified a high-risk patient subgroup with greater 1-year DM rates in the internal test (20.0% [3 of 15] versus 2.9% [7 of 241], p = 0.001) and external validation (21.4% [3 of 15] versus 7.8% [9 of 116], p = 0.095). A model nomogram and online application was made available.

CONCLUSIONS

We developed and externally validated a practical model that predicts DM risk in patients with NSCLC receiving SBRT which may help select patients for systemic therapy.

Systemic Immune-Inflammation Index May Predict Mortality in Neuroblastoma

INTRODUCTION

Neuroblastomas (NB) are among the most frequent childhood solid tumors. The link between inflammation and cancer is well understood. Many research studies have been conducted to determine the prognostic importance of inflammatory markers in cancer patients. C-reactive protein (CRP), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and systemic immune-inflammation index (SII) are all potential inflammation indicators. The purpose of this study is to assess the efficacy of NLR and SII as inflammatory indicators in predicting NB patient survival.

MATERIALS AND METHODS

Patients with NB diagnosed between January 1, 2012 and December 31, 2021 were studied retrospectively, and death was documented. By dividing the number of neutrophils by the number of lymphocytes, the NLR was obtained. The SII was calculated by multiplying the NLR by the platelet count.

RESULTS

 46 patients with NB were included in the study with a mean age of 57.58 months (4.14-170.05). When the patients were analyzed based on mortality the NLR and SII values were statistically significantly increased in the dead group (2.71 (1.22-4.1 ) vs. 1.7 (0.16-5.1); p=0.02; and 677.8 (215-1322) vs. 294.6 (69.49-799.1), respectively; p=0.012). Analysis of the receiver operating curve found that 328.49 is the ideal cutoff value for SII to predict mortality with a sensitivity of 83% and a specificity of 68% (area under the receiver operating characteristic curve = 0.814 (95% confidence interval: 0.671-0.956), p=0.005 ). Analyzing the influence of risk factors on survival using Cox regression analysis, SII was discovered as a significant predictor of survival in the study (HR =1.001, 95% CI =1-1.20; p=0.049).

CONCLUSION

 SII may be used to predict the overall survival of NB patients.

Association between Systemic Immunity-Inflammation Index and Hyperlipidemia: A Population-Based Study from the NHANES (2015-2020)

The systemic immunity-inflammation index (SII) is a novel inflammatory marker, and aberrant blood lipid levels are linked to inflammation. This study aimed to look at the probable link between SII and hyperlipidemia. The current cross-sectional investigation was carried out among people with complete SII and hyperlipidemia data from the 2015-2020 National Health and Nutrition Examination Survey (NHANES). SII was computed by dividing the platelet count × the neutrophil count/the lymphocyte count. The National Cholesterol Education Program standards were used to define hyperlipidemia. The nonlinear association between SII and hyperlipidemia was described using fitted smoothing curves and threshold effect analyses. A total of 6117 US adults were included in our study. A substantial positive correlation between SII and hyperlipidemia was found [1.03 (1.01, 1.05)] in a multivariate linear regression analysis. Age, sex, body mass index, smoking status, hypertension, and diabetes were not significantly correlated with this positive connection, according to subgroup analysis and interaction testing (p for interaction > 0.05). Additionally, we discovered a non-linear association between SII and hyperlipidemia with an inflection point of 479.15 using a two-segment linear regression model. Our findings suggest a significant association between SII levels and hyperlipidemia. More large-scale prospective studies are needed to investigate the role of SII in hyperlipidemia.

The association between sedentary behavior, exercise, and sleep disturbance: A mediation analysis of inflammatory biomarkers

Background

Two related lifestyle behaviors associated with sleep disturbance are sedentary behavior and physical exercise participation. We aimed to use a population-based study to disentangle the relationships between sedentary behavior, exercise, and sleep disturbance based on blood-cell-based inflammatory biomarkers.

Methods

A total of 22,599 participants from the National Health and Nutrition Examination Survey (NHANES) were included in the analyses. Sleep disturbance was assessed according to the NHANES questionnaire. Exercise participation ansd sedentary behavior were evaluated by the global physical activity questionnaire. The inflammatory biomarkers in the examination were white blood cell (WBC) count, neutrophil count (NEU), neutrophil-to-lymphocyte ratio (NLR), and systemic immune inflammation index (SII). A complex multistage sampling design and weighted multivariable logistic regression were applied for further analysis. Mediation models were constructed to figure out the mediating role of inflammatory biomarkers.

Results

The weighted prevalence of sleep disturbance was 24.17%. Sedentary behavior and exercise were associated with sleep disturbance after full adjustment [for sedentary behavior, OR (95% CI): 1.261 (1.154, 1.377); for exercise, OR (95% CI): 0.849 (0.757, 0.953)]. In severe sedentary behavior groups, the mitigation effect of exercise on sleep disturbance was observed [OR (95% CI): 0.687 (0.551, 0.857)]. For the mechanism, strong associations were detected between inflammatory biomarkers and sleep disturbance. Mediation analysis showed that WBC, NEU, NLR, and SII mediated the statistical association between sedentary behavior and sleep disturbance with proportions (%) of 2.09, 2.27, 1.76, and 0.82, respectively.

Conclusions

Our data suggested that sedentary behavior was a risk factor for sleep disturbance. Blood-cell-based inflammatory biomarkers were an easily accessible and cost-effective strategy for identifying sleep disturbance and also significantly mediated the association between sedentary behavior and sleep disturbance. Exercise was proved to be effective in severe sedentary behavior groups to improve sleep disturbance symptoms, while the internal mechanism needed further exploration.

Systemic immune inflammation index and peripheral blood carbon dioxide concentration at admission predict poor prognosis in patients with severe traumatic brain injury

Background

Recent studies have shown that systemic inflammation responses and hyperventilation are associated with poor outcomes in patients with severe traumatic brain injury (TBI). The aim of this retrospective study was to investigate the relationships between the systemic immune inflammation index (SII = platelet × neutrophil/lymphocyte) and peripheral blood CO₂ concentration at admission with the Glasgow Outcome Score (GOS) at 6 months after discharge in patients with severe TBI.

Methods

We retrospectively analyzed the clinical data for 1266 patients with severe TBI at three large medical centers from January 2016 to December 2021, and recorded the GOS 6 months after discharge. The receiver operating characteristic (ROC) curve was used to determine the best cutoff values for SII, CO₂, neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), and lymphocyte to monocyte ratio (LMR), and chi-square tests were used to evaluate the relationships among SII, CO₂ and the basic clinical characteristics of patients with TBI. Multivariate logistic regression analysis was used to determine the independent prognostic factors for GOS in patients with severe TBI. Finally, ROC curve, nomogram, calibration curve and decision curve analyses were used to evaluate the value of SII and coSII-CO2 in predicting the prognosis of patients with severe TBI. And we used the multifactor regression analysis method to build the CRASH model and the IMPACT model. The CRASH model included age, GCS score (GCS, Glasgow Coma Scale) and Pupillary reflex to light: one, both, none. The IMPACT model includes age, motor score and Pupillary reflex to light: one, both, none.

Results

The ROC curves indicated that the best cutoff values of SII, CO₂, PLR, NLR and LMR were 2651.43×10⁹, 22.15mmol/L, 190.98×10⁹, 9.66×10⁹ and 1.5×10⁹, respectively. The GOS at 6 months after discharge of patients with high SII and low CO₂ were significantly poorer than those with low SII and high CO₂. Multivariate logistic regression analysis revealed that age, systolic blood pressure (SBP), pupil size, subarachnoid hemorrhage (SAH), SII, PLR, serum potassium concentration [K⁺], serum calcium concentration [Ca²⁺], international normalized ratio (INR), C-reactive protein (CRP) and co-systemic immune inflammation index combined with carbon dioxide (coSII-CO₂) (P < 0.001) were independent prognostic factors for GOS in patients with severe TBI. In the training group, the C-index was 0.837 with SII and 0.860 with coSII-CO₂. In the external validation group, the C-index was 0.907 with SII and 0.916 with coSII-CO₂. Decision curve analysis confirmed a superior net clinical benefit with coSII-CO₂ rather than SII in most cases. Furthermore, the calibration curve for the probability of GOS 6 months after discharge showed better agreement with the observed results when based on the coSII-CO₂ rather than the SII nomogram. According to machine learning, coSII-CO₂ ranked first in importance and was followed by pupil size, then SII.

Conclusions

SII and CO₂ have better predictive performance than NLR, PLR and LMR. SII and CO₂ can be used as new, accurate and objective clinical predictors, and coSII-CO₂, based on combining SII with CO₂, can be used to improve the accuracy of GOS prediction in patients with TBI 6 months after discharge.

Pre-radiotherapy systemic immune inflammation index associated with overall survival in patients with advanced EGFR mutant non-small cell lung cancer receiving thoracic radiotherapy

PURPOSE

This study aimed to investigate the prognostic potential of the pre-radiotherapy systemic immune-inflammation index (SII) for the survival of advanced lung adenocarcinoma patients with epidermal growth factor receptor (EGFR) mutations, which might provide a basis for optimizing the comprehensive treatment scheme.

METHODS

A total of 111 lung adenocarcinoma patients with EGFR mutations, who received thoracic radiotherapy, were included in this retrospective study. The primary endpoint of the study was based on the overall survival (OS) of patients. The receiver operating characteristic (ROC) curve analysis was performed to determine the optimal cut-off value of each immune inflammation index. Kaplan-Meier analysis was performed for the comparison of OS. The Cox proportional-hazard model was used for the multivariate and univariate regression analyses to determine the correlations of prognostic factors with the disease.

RESULTS

SII was divided into the high SII group (≥ 620.2; 45.95%) and the low SII group (SII < 620.2; 54.05%) based on the optimal cutoff values. The median OS rates were 53.3 and 33.3 months in the low and high SII groups, respectively, showing statistically significant differences ( hazard ratio (HR) = 0.459; 95% CI 0.286-0.736; P < 0.001). The multivariate analysis showed that, after adjusting for the significant covariates, the SII values were independently associated with the improved OS of the patients (adjusted HR = 0.444; 95% CI 0.279-0.709; P = 0.001). The low NLR values were associated with the better OS of patients (HR = 0.509; 95% CI 0.326-0.792; P = 0.005) and vice versa (HR = 0.422; 95% CI 0.213-0.836; P < 0.001). The patients in the low LMR group before radiotherapy exhibited longer OS as compared to those in the high LMR group (HR = 0.497; 95% CI 0.308-0.802; P = 0.001).

CONCLUSIONS

This study showed that these inflammatory indices might have an important prognostic potential for advanced lung adenocarcinoma patients with EGFR mutations, receiving thoracic radiotherapy and might provide a basis for the individualized treatment of these patients.

Clinical value of the systemic immune-inflammation index in moyamoya disease

Background

Moyamoya disease (MMD) is a rare cerebrovascular disorder with unknown etiology. The underlying pathophysiological mechanism of moyamoya disease remains to be elucidated, but recent studies have increasingly highlighted that abnormal immune response may be a potential trigger for MMD. Neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and systemic immune-inflammation index (SII) are inflammatory markers that can reflect the immune-inflammation state of the disease.

Objective

The purpose of this study was to investigate SII, NLR, and PLR in patients with moyamoya disease.

Methods

A total of 154 patients with moyamoya disease (MMD group) and 321 age- and sex-matched healthy subjects (control group) were included in this retrospective case-control study. Complete blood count parameters were assayed to calculate the SII, NLR, and PLR values.

Results

The SII, NLR, and PLR values in the moyamoya disease group were significantly higher than those in the control group [754 ± 499 vs. 411 ± 205 (P < 0.001), 2.83 ± 1.98 vs. 1.81 ± 0.72 (P < 0.001), and 152 ± 64 vs. 120 ± 42 (P < 0.001), respectively]. The SII in the medium-moyamoya vessels of moyamoya disease was higher than that in the high-moyamoya vessels and low-moyamoya vessels (P = 0.005). Using the receiver operating characteristic (ROC) curve analysis to predict MMD, the highest area under the curve (AUC) was determined for SII (0.76 for SII, 0.69 for NLR, and 0.66 for PLR).

Conclusion

Based on the results of this study, patients with moyamoya disease admitted for inpatient care due to acute or chronic stroke have significantly higher SII, NLR, and PLR when compared to blood samples drawn from completely healthy controls in a non-emergent outpatient setting. While the findings may suggest that inflammation plays a role in moyamoya disease, further studies are warranted to corroborate such an association. In the middle stage of moyamoya disease, there may be a more intense imbalance of immune inflammation. Further studies are needed to determine whether the SII index contributes to the diagnosis or serves as a potential marker of an inflammatory response in patients with moyamoya disease.

Preoperative Immunocite-Derived Ratios Predict Surgical Complications Better when Artificial Neural Networks Are Used for Analysis-A Pilot Comparative Study

We aimed to comparatively assess the prognostic preoperative value of the main peripheral blood components and their ratios-the systemic immune-inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), and platelet-to-lymphocyte ratio (PLR)-to the use of artificial-neural-network analysis in determining undesired postoperative outcomes in colorectal cancer patients. Our retrospective study included 281 patients undergoing elective radical surgery for colorectal cancer in the last seven years. The preoperative values of SII, NLR, LMR, and PLR were analyzed in relation to postoperative complications, with a special emphasis on their ability to accurately predict the occurrence of anastomotic leak. A feed-forward fully connected multilayer perceptron network (MLP) was trained and tested alongside conventional statistical tools to assess the predictive value of the abovementioned blood markers in terms of sensitivity and specificity. Statistically significant differences and moderate correlation levels were observed for SII and NLR in predicting the anastomotic leak rate and degree of postoperative complications. No correlations were found between the LMR and PLR or the abovementioned outcomes. The MLP network analysis showed superior prediction value in terms of both sensitivity (0.78 ± 0.07; 0.74 ± 0.04; 0.71 ± 0.13) and specificity (0.81 ± 0.11; 0.69 ± 0.03; 0.9 ± 0.04) for all the given tasks. Preoperative SII and NLR appear to be modest prognostic factors for anastomotic leakage and overall morbidity. Using an artificial neural network offers superior prognostic results in the preoperative risk assessment for overall morbidity and anastomotic leak rate.

Is the neutrophil-to-lymphocyte ratio a prognostic factor in non-small cell lung cancer patients who receive adjuvant chemotherapy?

Inflammation plays a key role in malignant tumor progression. Neutrophil-to-lymphocyte ratio (NLR) is a marker of systemic inflammation and, as such, high isolated pretreatment NLR has been shown in some studies to be associated with worse long-term outcomes. We summarize the data regarding the utility of NLR as a prognosis factor and present results of a single institution study assessing the usefulness of high preoperative NLR as a prognosis factor for patients with successfully resected NSCLC who receive adjuvant cisplatin-based chemotherapy. While largely supportive of the value of NLR as a prognostic factor, the literature is not consistent and suggest a more nuanced association. Our single institution study adds to the exiting literature. We conclude preoperative NLR can be used as a reliable, cost-effective biomarker to estimate prognosis in NSCLC patients who have undergone lung lobectomy with curative intent followed by cisplatin-based adjuvant chemotherapy.

Role of systemic immune-inflammatory index in early diagnosis of sepsis in newborns with CHD

OBJECTIVE

Congenital heart diseases (CHD) are the most common causes of birth defects that have increased the risk of infections. Neonatal sepsis is a life-threatening condition and early diagnosis can be life-saving. We aimed to evaluate the potential role of the systemic immune-inflammatory index in the early diagnosis of neonatal sepsis.

METHODS

A retrospective cohort study was conducted on 166 newborns with a diagnosis of neonatal sepsis who were admitted to our hospital with CHD between January 2017 and June 2021. Haematological indices including neutrophil/lymphocyte ratio, platelet/lymphocyte ratio, and systemic immune-inflammatory index were calculated for all patients at the time of diagnosis of neonatal sepsis (sepsis). The sepsis values of these indices were compared with the admission values (pre-sepsis) of the patients.

RESULTS

The mean gestational age and birth weight of the patients were 38.36 ± 1.42 weeks and 3057.75 ± 484.68 g. It was found that absolute neutrophil count, systemic immune-inflammatory index, neutrophil/lymphocyte ratio, but not platelet/lymphocyte ratio were significantly increased at the time of sepsis. The receiver operating characteristic curve showed that systemic immune-inflammatory index, neutrophil/lymphocyte ratio, and absolute neutrophil count have predictive ability to define neonatal sepsis among newborns with CHD. The systemic immune-inflammatory index produced an area under the curve receiver operating characteristic curve of 0.76 (70% sensitivity, 70.5% specificity). To discriminate neonatal sepsis, the cut-off values of systemic immune-inflammatory index, neutrophil/lymphocyte ratio, and absolute neutrophil count were 517.19, 2.62, and 9210/mm³, respectively.

CONCLUSION

As an easily accessible and reliable indicator, systemic immune-inflammatory index may be used in combination with the other parameters in the early diagnosis of neonatal sepsis.

Information Value of Calculated Hematological Indices in the Assessment of Cardiac Risk in Oncological Surgery

The objective: to study information value of the neutrophil to lymphocyte ratio (NLR) and platelet to lymphocyte ratio (PLR) in the cardiac risk assessment in abdominal oncological surgery.

Subjects and Methods. 94 patients of 68 [62‒73] years old who underwent elective surgery were examined.

Results. Cardiovascular comortbidity was diagnosed in 69 (73.4%) patients. 11 (11.7%) perioperative cardiovascular complications were registered. Cardiac mortality was 4.3%. Hematological indices were not associated with cardiovascular diseases (NLR: OR = 0.59‒1.42; 95% CI 0.14‒2.60; p = 0.29‒0.74, PLR: OR = 0.99‒1.00; 95% CI 0.97‒1.01; p = 0.31‒0.99). NLR and PLR were not predictors of cardiovascular complications (OR = 0.67; 95% CI 0.19‒2.37; p = 0.46 and OR = 1.00; 95% CI 0.99‒1.01; p = 0.68) and cardiac death (OR = 0.21; 95% CI 0.01‒8.05; p = 0.23 and OR = 0.99; 95% CI 0.98‒1.01; p = 0.79).

Conclusion. NLR and PLR cannot be recommended for the cardiac risk assessment in abdominal oncological surgery.

The relationship between systemic immune inflammation index and survival in patients with metastatic renal cell carcinomatreated withtyrosine kinase inhibitors

This study aims to investigate the prognostic value of the systemic immune-inflammation index (SII)and its impact on survival in patients with metastatic renal cell carcinoma (mRCC). A total of 706patients with mRCC treated with tyrosine kinase inhibitors (TKIs)between January 2007 and June 2020 (i.e., sunitinib, pazopanib) were included in this study. SII was calculated in 621 patients with the following formula:[neutrophil (cellsx10⁹/L) x platelet (cellsx10⁹/L)] / lymphocyte (cellsx10⁹/L).All patients were classified into SII-high and SII-low groups based on the cut-off value of SII at 756, which was the median SII level of our study group. The minimal follow-up duration was 10 months in all cohorts. The median age of patients was 60 (interquartile range (IQR):53–67) years. Three out of four patients were male. The majority of patients (85.7%) had clear cell histology, and sarcomatoid differentiation was observed in 16.9% of all patients. There were 311 and 310 patients in the SII-low and SII-high groups, respectively. In general, baseline characteristics were similar in each group. However, the rate of patients treated with sunitinib (63.3% vs. 49.0%, p < 0.001) and those who underwent nephrectomy (83.6% vs. 64.2%, p < 0.001) was higher in the SII-low group than in the SII-high group. On the other hand, patients with the IMDC poorrisk (31.6% vs. 8.0%, p < 0.001), those with bone (51.8% vs. 32.2%, p < 0.001) or central nervous system (12.9% vs. 5.8%, p = 0.026) metastasis, and those with Eastern Cooperative Oncology Group(ECOG) 2–4 performance score (28.1% vs.17.7%, p = 0.002) were more common in the SII-high group than in the SII-low group. The median overall survival (OS) was longer in the SII-low group than in the SII-high group (34.6 months vs. 14.5 months, p < 0.001). Similarly, the median progression-free survival (PFS) was longer in the SII-low group than in the SII-high group (18.0 months vs. 7.7 months, p < 0.001).In multivariableanalysis, SII was an independent prognostic factor for OS (hazard ratio (HR):1.39, 95% confidence interval (CI):1.05–1.85, p = 0.01) and PFS (HR:1.60, 95% CI:1.24–2.05, p < 0.001).Pre-treatment level of high SII might be considered a predictor of poor prognosisin patients with mRCC treated with TKIs.

Prognostic role of the systemic immune-inflammation index in biliary tract cancers: a meta-analysis of 3,515 patients

Background

The systemic immune-inflammation index (SII) is an inflammatory parameter calculated as platelet count × neutrophil count/lymphocyte count in the peripheral blood. In recent years, the prognostic role of the SII in patients with biliary tract cancer (BTC) has been gradually investigated. However, the results were controversial. This meta-analysis aimed to illustrate the prognostic value of the SII in BTC.

Methods

The electronic databases of PubMed, the Web of Science, Embase, and the Cochrane Library were thoroughly retrieved up to April 15, 2022. Pooled hazard ratios (HRs) with 95% confidence intervals (CIs) were used to evaluate the prognostic value of the SII for clinical outcomes. The association between the SII and overall survival (OS) and recurrence-free survival (RFS)/progression-free survival (PFS) was evaluated.

Results

Thirteen studies involving 3515 patients were included in this meta-analysis. The pooled results indicated that an elevated SII was significantly associated with poor OS (HR, 1.77; 95% CI, 1.47–2.14; p<0.001) and RFS/PFS (HR, 1.66; 95% CI, 1.38–1.99; p<0.001) in patients with BTC. Subgroup analysis stratified by country, sample size, and cutoff value showed similar results. The sensitivity analysis and publication bias test confirmed the reliability of our results.

Conclusions

An elevated pretreatment SII was significantly associated with worse OS and RFS/PFS in patients with BTC. Our results suggest that the SII is a valuable and cost-effective prognostic parameter for the treatment of patients with BTC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12957-022-02783-z.

The impairment of induction chemotherapy for stage II nasopharyngeal carcinoma treated with intensity-modulated radiotherapy with or without concurrent chemotherapy: A propensity score-matched analysis

OBJECTIVES

To explore the efficacy of induction chemotherapy (IC) plus concurrent chemoradiotherapy (CCRT) in stage II nasopharyngeal carcinoma (NPC) treated with intensity-modulated radiotherapy (IMRT).

METHODS

Totally, 450 eligible patients with staged II NPC on the basis of the 8th edition of the AJCC/UICC TNM staging system were eventually included from January 2010 to September 2020. The one-to-one propensity score-matched (1:1 PSM) analysis was employed to balance variables. We conducted univariate and multivariate analysis of survival to identify prognostic factors and demonstrated the findings in the matching cohort.

RESULTS

In total, 141 pairs were selected by 1:1 PSM. IC + CCRT group in the matched data decreased 5-year progression-free survival (PFS, 75.5% vs. 88.0%, p = 0.032) and distant metastasis-free survival (DMFS, 86.0% vs. 96.5%, p = 0.009). There was no significant difference in 5-year overall survival (OS, 93.8% vs. 95.6%, p = 0.192) and locoregional relapse-free survival (LRRFS, 87.1% vs. 94.3%, p = 0.169) compared with RT/CCRT. Multivariate analysis indicated that IC + CCRT was associated with significantly poor PFS (p = 0.024) and DMFS (p = 0.010). High neutrophil-to-lymphocyte ratio (>4.1) was negatively associated with OS (p = 0.034), PFS (p = 0.017) and DMFS (p = 0.001).

CONCLUSION

Adding IC to CCRT or IMRT alone has decreased PFS and DMFS, therefore, IC should not be recommended in stage II NPC patients. No significant differences in OS and LRRFS were observed in stage II disease.

Neutrophil-to-Lymphocyte, Monocyte-to-Lymphocyte, Platelet-to-Lymphocyte Ratio and Systemic Immune-Inflammatory Index in Different States of Bipolar Disorder

The neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR) and systemic immune-inflammatory (SII) index, which provide a simple, rapid, inexpensive method to measure the level of inflammation, have been examined as potential inflammatory biomarkers of bipolar disorder (BD) in several studies. We conducted a case-control study recruiting 180 BD patients and 407 healthy controls. BD patients who met the inclusion criteria and were hospitalized due to BD at the psychiatry clinic of the University General Hospital of Larisa, Greece, until September 2021 were included in the study. Among them, 111 patients experienced a manic episode and 69 patients experienced a depressive episode. Data including a complete blood count were retrieved from their first admission to the hospital. Bipolar patients had a higher NLR, MLR and SII index compared to healthy controls when they were experiencing a manic episode (p < 0.001) and a depressive episode (p < 0.001). MLR was increased with large effect size only in patients expressing manic episodes. Neutrophils and NLR had the highest area under the curve with a cutoff of 4.38 and 2.15 in the ROC curve, respectively. Gender-related differences were mainly observed in the SII index, with males who were expressing manic episodes and females expressing depressive episodes having an increased index compared to healthy controls. The NLR, MLR and SII index were significantly higher in patients with BD than in healthy controls, which implies a higher grade of inflammation in BD patients.

Clinical Significance of Serum Biomarkers in Stage IV Non-Small-Cell Lung Cancer Treated with PD-1 Inhibitors: LIPI Score, NLR, dNLR, LMR, and PAB

Background

To assess the prognostic value of pretreatment serum biomarkers in stage IV non-small-cell lung cancer (NSCLC) patients treated with PD-1 (programmed cell death protein 1) inhibitors and their value as a predictor of benefit.

Methods

We performed a retrospective study including patients with stage IV NSCLC who were treated with anti-PD-1 drugs in first or advanced lines of therapy in the Affiliated Tumor Hospital of Nantong University. Serum biomarkers such as NLR, dNLR, LMR, PAB, ALB, and LIPI scores were calculated and analyzed in detail.

Results

A total of 85 patients with stage IV NSCLC treated with PD-1 inhibitors in the first or advanced lines of therapy were included in this subject. According to the tumor response of PD-1-based treatment, ORR was 42.4% (36/85) and DCR was 68.2% (58/85). The median OS and PFS were 20.0 months and 7.0 months, respectively. The ROC curves showed that the serum biomarkers of NLR, dNLR, LDH, LMR, PAB, and ALB were significantly associated with overall survival and helped to determine the cut-off value. The multivariate Cox proportional hazard analyses for stage IV NSCLC patients treated with PD-1 inhibitors indicated that dNLR (P < 0.001) and ALB (P = 0.033) were independent prognostic indicators of PFS, while liver metastasis (P = 0.01), NLR (P = 0.01), dNLR (P = 0.001), and LMR (P = 0.006) were independent prognostic indicators of OS. Moreover, patients of the good LIPI group showed prolonged PFS and OS than those with intermediate/poor LIPI score (P < 0.001 and P = 0.006, respectively).

Conclusions

Pretreatment dNLR is an independent prognostic indicator of both PFS and OS in stage IV NSCLC patients treated with PD-1 inhibitors. Pretreatment LIPI, combining dNLR > 3 and LDH>ULN, was correlated with worse outcome for stage IV NSCLC patients treated with ICI. High NLR, high dNLR, low LMR, and low ALB at baseline might be useful as an early predictive biomarker of benefit.

Predictive value of the systemic immune-inflammation index for cancer-specific survival of osteosarcoma in children

Background

Osteosarcoma (OS) is the primary malignant bone tumor that most commonly affects children and adolescents. Recent years effective chemotherapy have improved the 5-year survival in osteosarcoma patients to up to 60%-70%. Still, there is a lack of novel therapeutic strategies to enhance further survival. Our study aimed to evaluate the clinical significance of pretreatment inflammatory-based parameters, including PLT, NLR, and SII, as prognostic indicators of survival in pediatric osteosarcoma patients.

Methods

A total of 86 pediatric osteosarcoma patients between 2012 and 2021 in the Department of Orthopedics or tumor Surgery of Children's Hospital affiliated to Chongqing Medical University were retrospectively analyzed. The clinicopathological variables and systematic inflammatory biomarkers, including NLR, PLR and SII, was performed by the A Receiver operating characteristic (ROC) curve and Cox proportional risk regression model. According to the results of multivariate analysis, a prognostic nomogram was generated, and the concordance index (C-index) was calculated to predict the performance of the established nomogram. The survival curve was plotted by the Kaplan-Meier method.

Results

Univariate analysis showed that TNM stage, tumor size, NLR value, PLR value, SII value, neutrophil count and platelet count were related to CSS (p < 0.05). According to multivariate analysis, only TNM stage (p = 0.006) and SII values (p = 0.015) were associated with poor prognosis.To further predict survival in pediatric osteosarcoma patients, multivariate Cox regression analysis was used to predict cancer-specific survival at 1, 3 and 5 years. And constructed a nomogram model to predict children's CSS. The C-index of the nomogram is 0.776 (95%CI, 0.776–0.910), indicating that the model has good accuracy.

Conclusion

Preoperative SII and TNM staging are independent prognostic markers for pediatric osteosarcoma patients. SII may be used in conjunction with TNM staging for individualized treatment of pediatric osteosarcoma patients in future clinical work.

Risk Prediction Model for Synchronous Oligometastatic Non-Small Cell Lung Cancer: Thoracic Radiotherapy May Not Prolong Survival in High-Risk patients

Background and Purpose

On the basis of the promising clinical study results, thoracic radiotherapy (TRT)¹ has become an integral part of treatment of synchronous oligometastatic non–small cell lung cancer (SOM-NSCLC). However, some of them experienced rapid disease progression after TRT and showed no significant survival benefit. How to screen out such patients is a more concerned problem at present. In this study, we developed a risk-prediction model by screening hematological and clinical data of patients with SOM-NSCLC and identified patients who would not benefit from TRT.

Materials and Methods

We investigated patients with SOM-NSCLC between 2011 and 2019. A formula named Risk-Total was constructed using factors screened by LASSO-Cox regression analysis. Stabilized inverse probability treatment weight analysis was used to match the clinical characteristics between TRT and non-TRT groups. The primary endpoint was overall survival (OS).

Results

We finally included 283 patients divided into two groups: 188 cases for the training cohort and 95 for the validation cohort. Ten prognostic factors included in the Risk-Total formula were age, N stage, T stage, adrenal metastasis, liver metastasis, sensitive mutation status, local treatment status to metastatic sites, systemic inflammatory index, CEA, and Cyfra211. Patients were divided into low- and high-risk groups based on risk scores, and TRT was found to have improved the OS of low-risk patients (46.4 vs. 31.7 months, P = 0.083; 34.1 vs. 25.9 months, P = 0.078) but not that of high-risk patients (14.9 vs. 11.7 months, P = 0.663; 19.4 vs. 18.6 months, P = 0.811) in the training and validation sets, respectively.

Conclusion

We developed a prediction model to help identify patients with SOM-NSCLC who would not benefit from TRT, and TRT could not improve the survival of high-risk patients.

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

Background

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

Objective

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

Methods

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

Results

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

Conclusions

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

A Novel Score Combining Magnetic Resonance Spectroscopy Parameters and Systemic Immune-Inflammation Index Improves Prognosis Prediction in Non-Small Cell Lung Cancer Patients With Brain Metastases After Stereotactic Radiotherapy

Objective

The aim of this study was to evaluate the prognostic significance of the combination of the magnetic resonance spectroscopy (MRS) parameters and systemic immune-inflammation index (SII) in patients with brain metastases (BMs) from non-small cell lung cancer (NSCLC) treated with stereotactic radiotherapy.

Methods

A total of 118 NSCLC patients with BM who were treated with stereotactic radiotherapy were retrospectively enrolled in this study. All patients underwent MRS and blood samples test for SII analysis before the initiation of stereotactic radiotherapy. The correlation between the parameters of MRS and SII level was assessed using Spearman's correlation coefficient. The cutoff values for the parameters of MRS, SII, and clinical laboratory variables were defined by the receiver operating characteristic (ROC) curve analysis to quantify these predictive values. The prognostic factors of overall survival (OS) and progression-free survival (PFS) curves were assessed using the Kaplan-Meier and Cox proportional hazards models.

Results

The median follow-up time was 25 months (range, 12-49 months). The optimal cutoff point for the choline/creatine (Cho/Cr) ratio and SII were 1.50 and 480, respectively. The Cho/Cr ratio was negatively correlated with SII (rs = 0.164, p = 0.075), but there was a trend. The C-SII score was established by combining the Cho/Cr ratio and SII. Patients with both an elevated Cho/Cr ratio (>1.50) and an elevated SII (>480) were given a C-SII score of 2, and patients with one or neither were given a C-SII score of 1 or 0, respectively. The Kaplan-Meier analysis showed that a C-SII score of 2 was significantly linked with poor OS and PFS (p < 0.001 and p < 0.001, respectively). In the Cox proportional hazards model, the C-SII score independently predicted OS [hazard ratio (HR), 1.749; 95% CI, 1.176-2.601; p = 0.006] and PFS (HR, 2.472; 95% CI, 1.624-3.763; p < 0.001).

Conclusion

The C-SII score was more accurate for predicting the clinical outcomes of NSCLC patients with BM who underwent stereotactic radiotherapy. The C-SII score, which was superior to either score alone, could be used to identify BM in NSCLC patients with poor outcomes.

Significance of hemogram‐derived ratios for predicting in‐hospital mortality in COVID‐19: A multicenter study

Background

To address the problem of resource limitation, biomarkers having a potential for mortality prediction are urgently required. This study was designed to evaluate whether hemogram‐derived ratios could predict in‐hospital deaths in COVID‐19 patients.

Materials and Methods

This multicenter retrospective study included hospitalized COVID‐19 patients from four COVID‐19 dedicated hospitals in Sylhet, Bangladesh. Data on clinical characteristics, laboratory parameters, and survival outcomes were analyzed. Logistic regression models were fitted to identify the predictors of in‐hospital death.

Results

Out of 442 patients, 55 (12.44%) suffered in‐hospital death. The proportion of male was higher in nonsurvivor group (61.8%). The mean age was higher in nonsurvivors (69 ± 13 vs. 59 ± 14 years, p < 0.001). Compared to survivors, nonsurvivors exhibited higher frequency of comorbidities, such as chronic kidney disease (34.5% vs. 15.2%, p ≤ 0.001), chronic obstructive pulmonary disease (23.6% vs. 10.6%, p = 0.011), ischemic heart disease (41.8% vs. 19.4%, p < 0.001), and diabetes mellitus (76.4% vs. 61.8%, p = 0.05). Leukocytosis and lymphocytopenia were more prevalent in nonsurvivors (p < 0.05). Neutrophil‐to‐lymphocyte ratio (NLR), derived NLR (d‐NLR), and neutrophil‐to‐platelet ratio (NPR) were significantly higher in nonsurvivors (p < 0.05). After adjusting for potential covariates, NLR (odds ratio [OR] 1.05; 95% confidence interval [CI] 1.009‐1.08), d‐NLR (OR 1.08; 95% CI 1.006‐1.14), and NPR (OR 1.20; 95% CI 1.09‐1.32) have been found to be significant predictors of mortality in hospitalized COVID‐19 patients. The optimal cut‐off points for NLR, d‐NLR, and NPR for prediction of in‐hospital mortality for COVID‐19 patients were 7.57, 5.52 and 3.87, respectively.

Conclusion

Initial assessment of NLR, d‐NLR, and NPR values at hospital admission is of good prognostic value for predicting mortality of patients with COVID‐19.

Early and Long-Term Outcomes after Propofol-and Sevoflurane-Based Anesthesia in Colorectal Cancer Surgery: A Retrospective Study

Background: Propofol is considered to protect against immunosuppression and has lower inflammatory responses in the perioperative period than volatile agents. We evaluated whether the anesthetic agent is associated with cancer outcomes. Methods: We retrospectively reviewed 2616 patients who underwent colorectal cancer surgery under general anesthesia between 2016 and 2018 (follow-up closure: July 2021) at a single institution. Patients received propofol-based total intravenous anesthesia or sevoflurane-based inhalational anesthesia. After propensity score matching, the postoperative neutrophil-lymphocyte ratio (NLR) was compared as primary outcome, and clinical outcomes were evaluated. Results: After 1:2 propensity matching, 717 patients were given propofol anesthesia and 1410 patients were given sevoflurane anesthesia. In the matched cohort, preoperative NLR was not significantly different between propofol and sevoflurane anesthesia (mean (95% CI)2.3 (1.8 to 2.8) and 2.2 (1.9 to 3.2); p = 0.72). NLR was significantly lower in propofol anesthesia at postoperative day two and five (mean difference (95% CI) 0.71 (0.43 to 0.98); p = 0.000 and 0.52 (0.30 to 0.74); p = 0.000). Urinary retention showed a higher incidence after propofol anesthesia (4.9% vs. 2.6%; p = 0.008). Other postoperative complications and overall/recurrence-free survival were not different in the two groups. Discussion: Although propofol anesthesia showed lower postoperative NLR than sevoflurane anesthesia, there was no association with clinical outcomes.