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BACKGROUND: During the COVID-19 pandemic, identifying reliable biomarkers for predicting disease severity and patient outcomes in unvaccinated individuals is essential. This study evaluates the efficacy of key hematological markers, including leukocyte and neutrophil counts, Neutrophil-to-Lymphocyte Ratio (NLR), and cytokine profiles (IL-6, INF-γ, TNF-α, IL-17A, CCL2, and CXCL10) for predicting the necessity for mechanical ventilation and assessing survival probabilities. METHODS: We conducted an in-depth analysis on a cohort of COVID-19 patients, emphasizing the relationship between NLR, cytokine profiles, and clinical outcomes, utilizing routine leukocyte counting and cytokine quantification by flow cytometry. RESULTS: Elevated leukocyte and neutrophil counts, increased NLR, and significant cytokine elevations such as IL-6 and IL-10 were strongly associated with the need for mechanical ventilation, reflecting a pronounced systemic inflammatory response indicative of severe disease outcomes. CONCLUSION: Integrating hematological markers, particularly NLR and cytokine profiles, is crucial in predicting mechanical ventilation needs and survival in non-vaccinated COVID-19 patients. Our findings provide critical insights into the pathophysiology of COVID-19, supporting the development of more targeted clinical interventions and potentially informing future strategies for managing infectious disease outbreaks.
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OBJECTIVE: Various systemic inflammation response indexes (SIRI) have repeatedly been described as prognostic factors in ovarian cancer. They have not been validated in prospective trials and published results are sometimes contradictory. We aimed to explore their role in a cohort of patients diagnosed with stage III and IV ovarian cancer treated at our institution. METHODS: We retrospectively examined the prognostic influence of the neutrophil-to-lymphocyte ratio (NLR), the platelet-to-lymphocyte ratio (PLR), the monocyte-to-lymphocyte ratio (MLR), the red cell distribution width (RDW), and the mean platelet volume (MPV). RESULTS: A total of 77 patients were analyzed. NLR > 2.243 at diagnosis, NLR before primary surgery, MLR at diagnosis, PLR > 289.1 at diagnosis, and PLR at diagnosis were significant in univariate Cox regression for progression-free survival, but none of them retained their significance in the multivariate Cox regression analysis. For overall survival, NLR > = 2.53 at diagnosis, MLR > = 0.245 at diagnosis, and PLR > = 198.3 at diagnosis resulted significant in univariate COX regression; only PLR > = 198.3 at diagnosis retained its significance in the multivariate analysis. CONCLUSION: In our cohort, PLR > = 198.3 was an independent prognostic factor for worse OS. The definitive role of SIRI in ovarian cancer has not yet been established. If their value as prognostic factors could finally be established, they would become a simple and economical method to predict prognosis in patients with advanced ovarian cancer. Therefore, it is time to conduct prospective, multicenter studies with larger samples to definitively establish its role in ovarian cancer, if any.
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Background: Gastric cancer (GC) remains an important global health concern with limited treatment options for advanced cases. Immunotherapy has shown promising results, but identifying predictive biomarkers for treatment efficacy is challenging. Novel inflammatory markers, such as the platelet-to-lymphocyte ratio (PLR) and neutrophil-to-lymphocyte ratio (NLR), derived from complete blood count measurements, have gained attention as potential prognostic indicators. This systematic review and meta-analysis investigates the roles of the PLR and NLR as predictors of overall survival (OS) and progression-free survival (PFS) in advanced GC and gastroesophageal junction cancer (GEJC) patients treated with immunotherapy. Methods: A comprehensive search of the literature was conducted through PubMed, Embase, and Cochrane Library to identify relevant studies. A total of 16 studies involving NLR and 8 studies involving PLR were included. Pooled hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated to assess the association between high biomarker values and poor OS and PFS. Subgroup analyses were performed to explore potential sources of heterogeneity. Poor OS, PFS were defined by each study as statistically significant shorter survival. Results: A high NLR was significantly associated with worse OS (HR: 2.11; 95% CI: 1.70-2.62) and PFS (HR: 1.76; 95% CI: 1.43-2.17). High PLR was also significantly associated with poorer OS (HR: 1.77; 95% CI: 1.44-2.17) and PFS (HR: 1.61; 95% CI: 1.33-1.96). Subgroup analyses and sensitivity analyses supported the robustness of these findings. Publication bias was noted in NLR analysis for OS but not for PFS. PLR analysis showed low publication bias. Conclusions: Elevated NLR and PLR are associated with unfavorable OS and PFS outcomes in advanced GC/GEJC patients on immunotherapy. These findings imply the utility of these easily accessible biomarkers in prognostic assessment. However, standardized cutoff values and further research on interactions with the tumor microenvironment and comorbidities are needed. Additional prospective studies are warranted to validate these findings for both biomarkers.