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Statements

Subject Item
n2:RIV%2F61989100%3A27740%2F14%3A86089069%21RIV15-MSM-27740___
rdf:type
n15:Vysledek skos:Concept
rdfs:seeAlso
http://www.sciencedirect.com/science/journal/09518320/125
dcterms:description
Medical survival right-censored data of about 850 patients are evaluated to analyze their uncertainty on one hand and compare two basic surgery techniques in the context with risk of mortality on the other hand. Colorectal data comes from patients who underwent colectomy in the University Hospital of Ostrava. Two basic surgery operating techniques are used for the colectomy: either classical (open) or minimally invasive (laparoscopic). Basic question which arises at the colectomy operation is which type of operation to choose to guarantee longer overall survival time. Two non-parametric approaches have been used to quantify risk of mortality with uncertainties. In fact, supplement of the risk to one, i.e. survival function with corresponding confidence levels is calculated and evaluated. First approach considers standard nonparametric estimators resulting from both the Kaplan-Meier estimator of survival function in connection with Greenwood’s formula and the Nelson-Aalen estimator of cumulative hazard function including confidence interval for survival function as well. The second innovative approach, represented by Nonparametric Predictive Inference (NPI), uses lower and upper probabilities for quantifying uncertainty and provides a model of predictive survival function instead of the population survival function. The traditional log-rank test on one hand and the nonparametric predictive comparison of two groups of lifetime data on the other hand have been confronted to evaluate risk of mortality in context with mentioned surgery techniques. The size of the difference between two groups of lifetime data has been considered and analyzed as well. Medical survival right-censored data of about 850 patients are evaluated to analyze their uncertainty on one hand and compare two basic surgery techniques in the context with risk of mortality on the other hand. Colorectal data comes from patients who underwent colectomy in the University Hospital of Ostrava. Two basic surgery operating techniques are used for the colectomy: either classical (open) or minimally invasive (laparoscopic). Basic question which arises at the colectomy operation is which type of operation to choose to guarantee longer overall survival time. Two non-parametric approaches have been used to quantify risk of mortality with uncertainties. In fact, supplement of the risk to one, i.e. survival function with corresponding confidence levels is calculated and evaluated. First approach considers standard nonparametric estimators resulting from both the Kaplan-Meier estimator of survival function in connection with Greenwood’s formula and the Nelson-Aalen estimator of cumulative hazard function including confidence interval for survival function as well. The second innovative approach, represented by Nonparametric Predictive Inference (NPI), uses lower and upper probabilities for quantifying uncertainty and provides a model of predictive survival function instead of the population survival function. The traditional log-rank test on one hand and the nonparametric predictive comparison of two groups of lifetime data on the other hand have been confronted to evaluate risk of mortality in context with mentioned surgery techniques. The size of the difference between two groups of lifetime data has been considered and analyzed as well.
dcterms:title
A Nonparametric Approach to Medical Survival Data: Uncertainty in the Context of Risk in Mortality Analysis A Nonparametric Approach to Medical Survival Data: Uncertainty in the Context of Risk in Mortality Analysis
skos:prefLabel
A Nonparametric Approach to Medical Survival Data: Uncertainty in the Context of Risk in Mortality Analysis A Nonparametric Approach to Medical Survival Data: Uncertainty in the Context of Risk in Mortality Analysis
skos:notation
RIV/61989100:27740/14:86089069!RIV15-MSM-27740___
n3:aktivita
n18:P
n3:aktivity
P(ED1.1.00/02.0070)
n3:cisloPeriodika
2014
n3:dodaniDat
n12:2015
n3:domaciTvurceVysledku
n9:6396038 n9:8075077
n3:druhVysledku
n17:J
n3:duvernostUdaju
n5:S
n3:entitaPredkladatele
n13:predkladatel
n3:idSjednocenehoVysledku
966
n3:idVysledku
RIV/61989100:27740/14:86089069
n3:jazykVysledku
n16:eng
n3:klicovaSlova
Survival Analysis, Uncertainty, Medical Data, Kaplan-Meier Estimator, Nelson-Aalen Estimator, Nonparametric Predictive Inference
n3:klicoveSlovo
n4:Nonparametric%20Predictive%20Inference n4:Uncertainty n4:Survival%20Analysis n4:Kaplan-Meier%20Estimator n4:Medical%20Data n4:Nelson-Aalen%20Estimator
n3:kodStatuVydavatele
GB - Spojené království Velké Británie a Severního Irska
n3:kontrolniKodProRIV
[D395E61DAD0D]
n3:nazevZdroje
Reliability engineering and system safety
n3:obor
n14:BB
n3:pocetDomacichTvurcuVysledku
2
n3:pocetTvurcuVysledku
2
n3:projekt
n19:ED1.1.00%2F02.0070
n3:rokUplatneniVysledku
n12:2014
n3:svazekPeriodika
125
n3:tvurceVysledku
Briš, Radim Janurová, Kateřina
n3:wos
000333790600014
s:issn
0951-8320
s:numberOfPages
8
n11:doi
10.1016/j.ress.2013.03.014
n6:organizacniJednotka
27740