The Influence of Systemic Inflammation Response Index on Survival Outcomes of Limited-Stage Small-Cell Lung Cancer Patients Treated with Concurrent Chemoradiotherapy

Nomogram for predicting overall survival after curative gastrectomy using inflammatory, nutritional and pathological factors

PURPOSE

To establish a nomogram for predicting the overall survival (OS) in patients with gastric cancer (GC) based on inflammatory, nutritional and pathological factors.

METHODS

GC patients underwent curative gastrectomy from January 2012 to June 2017 in our hospital were included, and were classified into training set and validation set with a ratio of 7:3. Then variables associated with OS were analyzed using univariate and multivariate Cox regression analysis. Nomograms predicting OS were built using variables from multivariable Cox models. Finally, Kaplan-Meier curve and Log-rank test were also conducted to analyze the 1-yr, 3-yr and 5-yr OS to validate the efficiency of risk stratification of the nomogram.

RESULTS

A total of 366 GC patients were included. After univariate and multivariate Cox regression analysis, age (HR = 1.52, 95% CI = 1.01-2.30, P = 0.044), CA50 (HR = 1.90, 95% CI = 1.12-3.21, P = 0.017), PNI (HR = 1.65, 95% CI = 1.13-2.39, P = 0.009), SII (HR = 1.46, 95% CI = 1.03-2.08, P = 0.036), T stage (HR = 2.26, 95% CI = 1.01-5.05, P = 0.048; HR = 7.24, 95% CI = 3.64-14.40, P < 0.001) were independent influencing factors on the survival time of GC patients. Five factors including CEA, prognostic nutritional index (PNI), systemic immune-inflammation index (SII), ln (tumor size), T stage, and N stage were identified and entered the nomogram, which showed good discrimination and calibration in both sets. On internal validation, 1-yr, 3-yr and 5-yr nomogram demonstrated a good discrimination with an area under the ROC curve (AUC) of 0.77, 0.84 and 0.86, respectively. The AUC for 1-yr, 3-yr and 5-yr nomogram in validation set was 0.77, 0.79 and 0.81, respectively. The OS in low risk group of training cohort and validation cohort was significantly higher than that of intermediate risk group and high risk group, respectively.

CONCLUSIONS

We established a nomogram based on PNI, SII and pathological factors for predicting OS in GC patients. In addition, its efficiency was validated by validation set and stratified analysis.

Preoperative inflammation and nutrition-based comprehensive biomarker for predicting prognosis in resectable colorectal cancer

BACKGROUND

Colorectal cancer (CRC) remains a major global health concern, with significant morbidity and mortality rates. In this study, we aimed to develop a comprehensive blood indicator based on systemic inflammation and nutritional condition to predict the prognosis of resectable CRC patients.

METHODS

A retrospective cohort of 210 CRC patients who underwent radical resection at the First Affiliated Hospital of Chongqing Medical University, China, between January 2015 and December 2017, was included in the analysis. Baseline characteristics, preoperative blood markers, including neutrophil count, monocyte count, lymphocyte count, platelets, albumin, and CEA were retrospectively reviewed. Various blood indicators, such as NLR, PLR, MLR, SIRI and OPNI were calculated. The least absolute shrinkage and selection operator (LASSO) method was employed to select indicators to establish a novel comprehensive biomarker (named PSI). Kaplan-Meier survival curves and log-rank tests were used to evaluate the prognostic impact of preoperative OPNI, SIRI, and PSI. Univariate and multivariate Cox regression model were conducted to identify independent prognostic factors for CRC. The receiver operating characteristic (ROC) method assessed the predictive ability of PSI, stage, OPNI, and SIRI.

RESULTS

Patients with higher preoperative OPNI and lower SIRI values had significantly better overall survival (OS). PSI was identified as an independent prognostic factor for OS in both univariate and multivariate analysis. Patients with medium (28.3-43.4) and high (>43.4) PSI scores exhibited superior OS compared to those with low (≤ 28.3) PSI scores. PSI showed higher predictive ability (AUC: 0.734) than individual indicators alone (OPNI: 0.721, SIRI: 0.645, stage: 0.635).

CONCLUSION

The novel indicator, PSI, based on preoperative SIRI and OPNI, demonstrated significant prognostic value for resectable CRC patients. PSI outperformed individual indicators and could serve as a reliable tool for prognostic evaluation in CRC patients.

The association and prognostic value of systemic inflammatory response index with short and long-term mortality in patients with sepsis

This study evaluated the association and prognostic significance of the systemic inflammation response index (SIRI) with mortality in sepsis. In this cohort study, the sepsis patients were retrieved from the Medical Information Mart for Intensive Care III (MIMIC-III) and MIMIC-IV intensive care unit (ICU) databases. SIRI was calculated by using the neutrophil, monocyte, and lymphocyte counts. The outcomes were 28-day mortality, 1-year mortality, and 28 days to 1-year mortality. The Cox proportional hazards model with a hazard ratio (HR) and a 95% confidence interval (CI) was used to investigate the association and prognostic value of SIRI with mortality in sepsis. Subgroup analyses of the associations of SIRI with 28-day and 1-year mortality in sepsis were based on age, gender, Simplified Acute Physiology Score II (SAPSII), Sequential Organ Failure Assessment (SOFA), and presence or absence of septic shock. The receiver operating characteristic (ROC) curve was used to compare the predictive performances of SIRI, SOFA and SAPS II for mortality in sepsis. Of the 4239 patients included, 1339 patients suffered from 28-day mortality, 2085 patients suffering from 1-year mortality, and 746 (25.72%) suffered from 28 days to 1-year mortality. High SIRI levels exhibited higher risks of 28-day mortality (HR: 1.15, 95% CI: 1.03-1.29, P = .010), 1-year mortality (HR: 1.14, 95% CI: 1.04-1.24, P = .003), and 28 days to 1-year mortality (HR: 1.16, 95% CI: 1.01-1.35, P = .047) in sepsis. A higher SIRI was reported related to 28-day mortality and 1-year mortality in sepsis patients with female gender, with SOFA < 8, with SAPS II < 44, and in sepsis patients without sepsis shock. The AUC of SIRS, SOFA, and SAPS II in predicting 28-day mortality in sepsis were 0.726, 0.591, and 0.644, respectively. The AUC of SIRI in predicting 1-year mortality in sepsis was 0.761, higher than the AUC values of SOFA and SAPS II. A higher AUC value of SIRI compared with SOFA, and SAPS II in predicting 28 days to 1-year mortality was observed. Elevated SIRI was associated with an increased risk of mortality in sepsis. SIRI is an independent prognostic biomarker of mortality in sepsis.

The response prediction and prognostic values of systemic inflammation response index in patients with advanced lung adenocarcinoma

PURPOSE

This study aimed to assess the response prediction and prognostic values of different peripheral blood cell biomarkers for advanced lung adenocarcinoma (LUAD) patients receiving first-line therapy.

METHODS

Patients diagnosed with advanced LUAD as well as healthy controls and patients with benign pulmonary diseases were collected in this retrospective study. Propensity score matching (PSM) was performed in a 1:1 ratio. Survival state was estimated by the Kaplan-Meier method and the Cox proportional hazard model was used to assess the prognostic factors.

RESULTS

Compared with the control groups, the level of peripheral blood leucocyte, neutrophil, monocyte, platelet, and neutrophil to lymphocyte ratio, monocyte to lymphocyte ratio, platelet to lymphocyte ratio, and systemic inflammation response index (SIRI) were higher in LUAD patients (all p < 0.001). Some inflammatory markers decreased at the time of optimal response and then increased again as the disease progressed. Multivariate analysis revealed that SIRI and lactate dehydrogenase (LDH) were independent prognostic factors no matter before or after PSM analysis. Area under the curve (AUC) of SIRI and LDH were 0.625 (p < 0.001) and 0.596 (p = 0.008), respectively. When SIRI and LDH were combined, the AUC reached 0.649 (p < 0.001).

CONCLUSIONS

Pretreatment SIRI was an independent prognostic factor of progression free survival (PFS) in advanced LUAD patients. Dynamic monitoring of inflammatory index changes could help to predict therapeutic efficacy. The combination of SIRI and LDH is expected to be a promising clinically accessible biomarker in the future.

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

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

Construction of Brain Metastasis Prediction Model and Optimization of Prophylactic Cranial Irradiation Selection for Limited-Stage Small-Cell Lung Cancer

Prophylactic cranial irradiation (PCI), as an essential part of the treatment of limited-stage small-cell lung cancer (LS-SCLC), inevitably leads to neurotoxicity. This study aimed to construct a brain metastasis prediction model and identify low-risk patients to avoid PCI; 236 patients with LS-SCLC were retrospectively analyzed and divided into PCI (63 cases) and non-PCI groups (173 cases). The nomogram was developed based on variables determined by univariate and multivariate analyses in the non-PCI group. According to the cutoff nomogram score, all patients were divided into high- and low-risk cohorts. A log-rank test was used to compare the incidence of brain metastasis between patients with and without PCI in the low-risk and high-risk groups, respectively. The nomogram included five variables: chemotherapy cycles (ChT cycles), time to radiotherapy (RT), lactate dehydrogenase (LDH), pro-gastrin-releasing peptide precursor (ProGRP), and lymphocytes−monocytes ratio (LMR). The area under the receiver operating characteristics (AUC) of the nomogram was 0.763 and 0.782 at 1 year, and 0.759 and 0.732 at 2 years in the training and validation cohorts, respectively. Based on the nomogram, patients were divided into high- and low-risk groups with a cutoff value of 165. In the high-risk cohort, the incidence of brain metastasis in the non-PCI group was significantly higher than in the PCI group (p < 0.001), but there was no difference in the low-risk cohort (p = 0.160). Propensity score-matching (PSM) analysis showed similar results; the proposed nomogram showed reliable performance in assessing the individualized brain metastasis risk and has the potential to become a clinical tool to individualize PCI treatment for LS-SCLC.

Systemic Inflammation Response Index as a Prognostic Marker in Cancer Patients: A Systematic Review and Meta-Analysis of 38 Cohorts

Background

The systemic inflammation response index (SIRI), a novel and cost-effective serum biomarker, is associated with prognosis in patients with cancer. However, the prognostic value of the SIRI in cancer remains unclear. This study aimed to evaluate the potential role of the SIRI as a prognostic indicator in cancer.

Methods

Reports in which the prognostic value of the SIRI in cancer was evaluated were retrieved from electronic databases. The pooled hazard ratio (HR) and 95% confidence interval (CI) were calculated to evaluate the prognostic significance of the SIRI. The odds ratio (OR) was also calculated to explore the association between the SIRI and clinicopathological features.

Results

This study included 30 retrospective studies with 38 cohorts and 10 754 cases. The meta-analysis indicated that a high SIRI was associated with short overall survival (OS) (HR = 2.04, 95% CI = 1.82-2.29, P < .001) and disease-free survival (DFS)/recurrence-free survival (RFS)/progression-free survival (PFS) (HR = 2.08, 95% CI = 1.84-2.34, P < .001). Subgroup analysis showed that the prognostic value of the SIRI was significant in all kinds of cancer included. Moreover, the SIRI was significantly correlated with sex, tumor size, T stage, N stage, TNM stage, and lymphovascular invasion.

Conclusion

The pretreatment SIRI could be a promising universal prognostic indicator in cancer.