scholarly journals A Proportional Hazards Regression Model for the Subdistribution with Covariates-adjusted Censoring Weight for Competing Risks Data

2015 ◽  
Vol 43 (1) ◽  
pp. 103-122 ◽  
Author(s):  
Peng He ◽  
Frank Eriksson ◽  
Thomas H. Scheike ◽  
Mei-Jie Zhang
Keyword(s):  
Regression Model ◽  
Competing Risks ◽  
Proportional Hazards ◽  
Proportional Hazards Regression ◽  
Competing Risks Data

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 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.

Adjusted variable plots for Cox's proportional hazards regression model

1996 ◽  
Vol 2 (1) ◽  
pp. 73-90 ◽  
Author(s):  
Charles B. Hall ◽  
Scott L. Zeger ◽  
Karen J. Bandeen-Roche
Keyword(s):  
Regression Model ◽  
Proportional Hazards ◽  
Proportional Hazards Regression
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