scholarly journals Prognostic Significance of Serum Free Amino Acids in Head and Neck Cancers

Cells ◽  
2019 ◽  
Vol 8 (5) ◽  
pp. 428 ◽  
Author(s):  
Vit Vsiansky ◽  
Marketa Svobodova ◽  
Jaromir Gumulec ◽  
Natalia Cernei ◽  
Dagmar Sterbova ◽  
...  
Keyword(s):  
Amino Acids ◽  
Amino Acid ◽  
Regression Model ◽  
Head And Neck ◽  
Cell Lines ◽  
Proportional Hazards ◽  
Cox Proportional Hazards ◽  
Transformed Cells ◽  
Cox Proportional Hazards Regression ◽  
Proportional Hazards Regression

Despite distinctive advances in the field of head and neck squamous cell cancer (HNSCC) biomarker discovery, the spectrum of clinically useful prognostic serum biomarkers is limited. As metabolic activities in highly proliferative transformed cells are fundamentally different from those in non-transformed cells, specific shifts in concentration of different metabolites may serve as diagnostic or prognostic markers. Blood amino acids have been identified as promising biomarkers in different cancers before, but little is known about this field in HNSCC. Blood amino acid profiles of 140 HNSCC patients were examined using high-performance liquid chromatography. Cox proportional hazards regression model was used to assess the prognostic value of amino acid concentrations in serum. Colony forming assay was used to identify the effect of amino acids that were significant in Cox proportional hazards regression models on colony forming ability of FaDu and Detroit 562 cell lines. In the multivariable Cox regression model for overall survival (OS), palliative treatment was associated with an unfavourable prognosis while high serum levels of methionine have had a positive prognostic impact. In the relapse-free survival (RFS) multivariable model, methionine was similarly identified as a positive prognostic factor, along with tumor localization in the oropharynx. Oral cavity localization and primary radio(chemo)therapy treatment strategy have been linked to poorer RFS. 1mM serine was shown to support the forming of colonies in both tested HNSCC cell lines. Effect of methionine was exactly the opposite.

MODELLING THE DETERMINANTS OF UNDER-FIVE CHILD MORTALITY RATES USING COX PROPORTIONAL HAZARDS REGRESSION MODEL

2021 ◽  
Vol 4 (4) ◽  
pp. 401-408
Author(s):  
M. C. Musa ◽  
O. E. Asiribo ◽  
H. G. Dikko ◽  
M. Usman ◽  
S. S. Sani
Keyword(s):  
Regression Model ◽  
Child Mortality ◽  
Proportional Hazards ◽  
Mortality Rates ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Predictor Variables ◽  
Under Five ◽  
Cox Proportional Hazards Regression ◽  
Proportional Hazards Regression

An under-five childhood mortality rates in Nigeria is still high, despite efforts of government at all levels to combat the menace. This study examined some factors that significantly affect under-five child mortality. A sample of mothers with children under the age of five from Nigeria Demographic and Health Survey data (NDHS, 2013 & 2018) was used to assess the effect of some selected predictor variables (or covariates) on childhood survival. Cox proportional hazards model is essentially a regression model popularly used for investigating the association between the survival time and one or more predictor variables. The results from final fitted Cox proportional hazards regression model that the covariates, contraceptive used by the mother, state of residence, birth weight of child and type of toilet facility used by the h-ousehold were found to be significantly associated with under-five survival in the North Central Region of Nigeria. All the calculations are performed using the R software for statistical analysis.

scholarly journals High PD-L1 Expression Associates with Low T-Cadherin Expression and Poor Prognosis in HPV-Negative Head and Neck Squamous Cell Carcinoma

2021 ◽  
Author(s):  
Qiuju Wang ◽  
Yanzhen Zhao ◽  
Yan Chen ◽  
Yibo Chen ◽  
Xiaoyu Song ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Regression Analysis ◽  
Protein Expression ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Squamous Cell ◽  
Proportional Hazards ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Regression ◽  
Proportional Hazards Regression

Abstract PurposeT-cadherin is an immunoglobulin-like adhesion molecule which acts as a tumor suppressor gene, programmed cell death ligand 1 (PD-L1) is a cell surface protein that involves in the suppression of the immune system. This study aimed at exploring the correlation between T-cadherin and PD-L1, as well as their prognostic value in patients with HPV-negative head and neck squamous cell carcinoma (HNSCC). MethodsIn this study, immunohistochemical staining was used to determine the protein expression of T-cadherin and PD-L1 in 104 tissue specimens of HPV-negative HNSCC. Spearman linear correlation analysis was used to determine the association between protein expression of T-cadherin and PD-L1. Kaplan-Meier analysis was used to plot overall survival (OS) and disease-free survival (DFS) curves. Cox proportional hazards regression analysis was used to conduct univariate and multivariate analysis. ResultsThe results showed a large negative association between protein expression of T-cadherin and PD-L1 (r=-0.775, P<0.01), expression of T-cadherin and PD-L1 were associated with OS (P=0.021 and 0.034, respectively) and DFS (P=0.012 and 0.016, respectively) in patients with HPV-negative HNSCC. Cox proportional hazards regression analysis revealed that expression of T-cadherin and PD-L1 were independent prognostic predictors for OS and DFS in patients with HPV-negative HNSCC. The worst prognosis was observed in patients with T-cadherin negative/PD-L1 positive.ConclusionIn conclusion, expression of T-cadherin and PD-L1 were inversely correlated and were independent prognostic factors for patients with HPV-negative HNSCC.

scholarly journals An Assessment of the Cox Proportional Hazards Regression Model for Epidemiologic Studies

Risk Analysis ◽  
2017 ◽  
Vol 38 (4) ◽  
pp. 777-794 ◽  
Author(s):  
Suresh H. Moolgavkar ◽  
Ellen T. Chang ◽  
Heather N. Watson ◽  
Edmund C. Lau
Keyword(s):  
Regression Model ◽  
Proportional Hazards ◽  
Epidemiologic Studies ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Regression ◽  
Proportional Hazards Regression
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