Dataset Information

Inflammatory markers for predicting overall survival in gastric cancer patients: A systematic review and meta-analysis.

ABSTRACT: Systemic inflammatory biomarkers have begun to be used in clinical practice to predict prognosis and survival of cancer patients, but the approach remains controversial. We conducted a meta-analysis to determine the predictive value of the c-reactive protein (CRP), neutrophil-to-lymphocyte ratio (NLR), and Glasgow prognostic score (GPS)/modified Glasgow prognostic score (mGPS) in the clinical outcome of gastric cancer (GC) patients. We searched literature databases to identify relevant studies. All articles identified in the search were independently reviewed based on predetermined selection criteria. Meta-analysis was conducted to calculate the hazard ratio (HR) and 95% confidence intervals (CI) of overall survival of the included studies. A total of 41 eligible cohort studies, involving a total of 18,348 patients meeting the inclusion criteria, were considered for meta-analysis. Increases in CRP (HR = 1.654, 95% CI: 1.272-2.151), NLR (HR = 1.605, 95% CI: 1.449-1.779), and GPS/mGPS (HR = 1.648, 95% CI: 1.351-2.011) were significantly associated with poorer survival in patients with GC. Substantial heterogeneities were noted in all three markers (I2 = 86.479%, 50.799%, 69.774%, in CRP, NLR, and GPS/mGPS, respectively). Subgroup analysis revealed a significant positive correlation between each marker and poor survival, regardless of country, study quality, cancer stage, study design, or the inclusion of patients undergoing chemotherapy. This meta-analysis demonstrates that CRP, NLR, and GPS/mGPS are associated with poor survival in patients with GC. Further prospective studies using standardized measurements are warranted to conclude the prognostic value of various inflammatory markers.

SUBMITTER: Kim MR

PROVIDER: S-EPMC7384660 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Inflammatory markers for predicting overall survival in gastric cancer patients: A systematic review and meta-analysis.

Kim Mi-Rae MR Kim A-Sol AS Choi Hye-In HI Jung Jae-Hun JH Park Ji Yeon JY Ko Hae-Jin HJ

PloS one 20200727 7

Systemic inflammatory biomarkers have begun to be used in clinical practice to predict prognosis and survival of cancer patients, but the approach remains controversial. We conducted a meta-analysis to determine the predictive value of the c-reactive protein (CRP), neutrophil-to-lymphocyte ratio (NLR), and Glasgow prognostic score (GPS)/modified Glasgow prognostic score (mGPS) in the clinical outcome of gastric cancer (GC) patients. We searched literature databases to identify relevant studies. ...[more]

PMID: 32716955

Similar Datasets

Project description:BackgroundInflammatory markers are associated with tumor genesis and progression, but their prognostic significance in osteosarcoma remains unclear. Therefore, we discussed the prognostic value of related inflammatory markers in osteosarcoma through a meta-analysis and systematic review. These inflammatory markers include C-reactive protein (CRP), neutrophil to lymphocyte ratio (NLR), lymphocyte to monocyte ratio (LMR), platelet to lymphocyte ratio (PLR), and Glasgow prognostic score (GPS).MethodsThe Chinese National Knowledge Infrastructure (CNKI), Wanfang, Chinese Scientific Journals (VIP), PubMed, Embase, and Cochrane libraries were searched. The design of meta-analysis was made based on the PICOS (population, intervention/exposure, control, outcomes, and study design) principles, and STATA 15.1 was used to analyze the data. The Newcastle-Ottawa scale (NOS) was used to assess the quality of included studies. Hazard ratios (HRs) for overall survival (OS) and disease-specific survival (DPS) were extracted for the investigation of the prognostic value of inflammatory markers.ResultsTwelve researches with 2162 osteosarcoma patients were included in total. The pooled results showed that elevated NLR, CRP, and GPS are all greatly related to shortening of OS among patients with osteosarcoma (HR = 1.68, P = 0.007, 95% CI: 1.15-2.45; HR = 1.96, P = 0.002, 95% CI: 1.28-3.00; HR = 2.54, P < 0.0001, 95% CI: 1.95-3.31, respectively), and CRP level is significantly associated with shortening of DPS among patients with osteosarcoma (HR = 2.76, 95% CI:2.01-3.80, P < 0.0001), additionally. However, the correlation between LMR or PLR and the prognosis of osteosarcoma is not statistically significant (HR = 0.60, 95% CI: 0.30-1.18, P = 0.138; HR = 1.13, 95% CI: 0.85-1.49, P = 0.405, respectively). The outcomes of subgroup analysis to NLR and CRP suggested that histology, ethnicity, metastasis, and sample size all have an impact on its prognosis of patients with osteosarcoma.ConclusionWorsened prognosis may be related to high levels of NLR, CRP, and GPS before treatment rather than LMR or PLR, which can provide the basis for clinicians to judge the outcomes of prognosis. Trial Registration. PROSPERO (CRD42021249954), https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=249954.

Project description:BackgroundThe survival rates of advanced cancer patients remain low despite clinical therapy advancements. However, physical activity showed promising effects in improving cancer outcomes. This review aimed to systematically evaluate and synthesize the effects on overall mortality of post-diagnosis physical activity in advanced cancer patients.MethodsA systematic search of six English databases (PubMed, EMBASE, CINAHL, PsycINFO, The Cochrane Central Register of Controlled Trials, and SPORTDiscus) was conducted from their inception up to 3 February 2021. The association of physical activity with survival was evaluated by combining study-specific hazard ratios with random-effects meta-analysis models.ResultsEleven studies were identified. Compared with the reference group, higher-level physical activity was not significantly associated with a lower risk of earlier mortality in advanced cancer patients (InHR = - 0.18, 95% CI, - 0.36 to 0.01). When separated by study type, a higher level of physical activity in non-randomised trials was significantly associated with reduced mortality risk (InHR = - 0.25, 95% CI: - 0.44, - 0.06). However, in randomised trials, engaging in exercise was not significantly associated with a lower mortality risk compared with the control group (InHR = 0.08, 95%CI: - 0.17, 0.32).ConclusionsDiscrepancies were uncovered in the effect of physical activity on overall survival in randomised and non-randomised trials. In non-randomised trials, a higher level of physical activity was significantly associated with a lower risk of mortality, whereas no significant effect on survival was observed during exercise interventions compared to the control in randomised trials. Considering the wider benefits of physical activity, exercise can still be recommended to improve outcomes for advanced cancer patients. Nevertheless, it might be too late for advanced cancer patients to start exercising for survival improvements, based on findings from randomised controlled trials.

Project description:ObjectivesWe aimed to identify nutritional, inflammatory and clinical indicators associated with stage II/III gastric cancer in patients, and construct a nomogram model for accurate prediction of prognosis of patients.MethodsWe retrospectively recruited stage II/III gastric cancer (GC) patients who underwent radical gastrectomy at Fudan University Shanghai Cancer Center, from 2012 to 2019. The patients were randomly divided into training and internal validation sets, and then the Maximum log-rank statistic method was used to determine the optimal cut-off value. Next, we performed univariate and multivariate Cox regression analyses to identify independent risk factors associated with overall survival (OS). These were subsequently used to develop a nomogram model. We validated this model in patients with stage II/III gastric cancer (from 2010 to 2019) at Guangxi Medical University Affiliated Tumor Hospital.ResultsA total of 2,443 patients met our inclusion criteria and were therefore included in our study. Patients from Fudan University Shanghai Cancer Center were randomly divided into training (n=1725) and internal validation (n=430) sets, while those from Guangxi Medical University Affiliated Tumor Hospital were used as the external validation set (n=288). Results from univariate and multivariate Cox regression analyses revealed that age (adjusted HR, 1.23; 95% CI, 1.05-1.44; P=0.012), TNM stage (adjusted HR, 3.62; 95% CI, 2.79-4.68; P<0.001), CEA (adjusted HR, 1.40; 95% CI, 1.14-1.71; P<0.001), CA199 (adjusted HR, 1.47; 95% CI, 1.21-1.79; P<0.001), and Prognostic Nutritional Index (PNI, adjusted HR, 0.81; 95% CI, 0.67-0.98; P=0.026) were independent prognostic factors for OS in the training set. The established nomogram model, with a C-index of 0.67, had 3- and 5-year Area under Curve (AUC) values of 0.719 and 0.714, respectively. Notably, the model effectively distinguished patients' OS in both the internal (P<0.001) and external (P<0.001) datasets.ConclusionsPNI is an independent prognostic factor for stage II/III GC patients after radical resection. The established novel nomogram model, based on nutritional, inflammatory and clinical indicators, can accurately and efficiently predict prognosis of stage II/III GC patients.

Project description:Background: Systemic inflammatory indicators are clinically significant in guiding diffuse large B-cell lymphoma (DLBCL) prognosis. However, which inflammatory markers are the best predictors of DLBCL prognosis is still unclear. In this study, we aimed to create a nomogram based on the best inflammatory markers and clinical indicators to predict the overall survival of patients with DLBCL. Patients and methods: We analyzed data from 423 DLBCL patients from two institutions and divided them into a training set, an internal validation set, and an external validation set (n = 228, 97, and 98, respectively). The least absolute shrinkage and selection operator and Cox regression analysis were used to develop nomograms. We assessed model fit using the Akaike information criterion and Bayesian information criterion. The concordance index (C-index), calibration curve, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA) were used to assess the nomogram's predictive performance and clinical net benefit and compared with the International Prognostic Index (IPI) and National Comprehensive Cancer Network (NCCN)-IPI. Results: The inclusion variables for the nomogram model were age, Eastern Cooperative Oncology Group performance status, lactate dehydrogenase level, the systemic immune-inflammation index (SII), the prognostic nutritional index (PNI), and β-2 microglobulin (β-2 MG) level. In the training cohort, the nomogram showed better goodness of fit than the IPI and NCCN-IPI. The C-index of the nomogram (0.804, 95% CI: 0.751-0.857) outperformed the IPI (0.690, 95% CI: 0.629-0.751) and NCCN-IPI (0.691, 95% CI: 0.632-0.750). The calibration curve, ROC curve, and DCA curve analysis showed that the nomogram has satisfactory predictive power and clinical utility. Similar results were found in the validation cohort. Conclusion: The nomogram integrated with the clinical characteristics and inflammatory markers is beneficial to predict the prognosis of patients with DLBCL.

Dataset Information

Inflammatory markers for predicting overall survival in gastric cancer patients: A systematic review and meta-analysis.

Publications

Inflammatory markers for predicting overall survival in gastric cancer patients: A systematic review and meta-analysis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets