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Analysis of heart transplant survival data using generalized additive models. 2013

Masaaki Tsujitani, and Yusuke Tanaka
Department of Engineering Informatics, Osaka Electro-Communication University, Osaka 572-8530, Japan. ekaaf900@ricv.zaq.ne.jp

The Stanford Heart Transplant data were collected to model survival in patients using penalized smoothing splines for covariates whose values change over the course of the study. The basic idea of the present study is to use a logistic regression model and a generalized additive model with B-splines to estimate the survival function. We model survival time as a function of patient covariates and transplant status and compare the results obtained using smoothing spline, partial logistic, Cox's proportional hazards, and piecewise exponential models.

UI MeSH Term Description Entries
D008875 Middle Aged An adult aged 45 - 64 years. Middle Age
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D000328 Adult A person having attained full growth or maturity. Adults are of 19 through 44 years of age. For a person between 19 and 24 years of age, YOUNG ADULT is available. Adults
D000465 Algorithms A procedure consisting of a sequence of algebraic formulas and/or logical steps to calculate or determine a given task. Algorithm
D015233 Models, Statistical Statistical formulations or analyses which, when applied to data and found to fit the data, are then used to verify the assumptions and parameters used in the analysis. Examples of statistical models are the linear model, binomial model, polynomial model, two-parameter model, etc. Probabilistic Models,Statistical Models,Two-Parameter Models,Model, Statistical,Models, Binomial,Models, Polynomial,Statistical Model,Binomial Model,Binomial Models,Model, Binomial,Model, Polynomial,Model, Probabilistic,Model, Two-Parameter,Models, Probabilistic,Models, Two-Parameter,Polynomial Model,Polynomial Models,Probabilistic Model,Two Parameter Models,Two-Parameter Model
D016014 Linear Models Statistical models in which the value of a parameter for a given value of a factor is assumed to be equal to a + bx, where a and b are constants. The models predict a linear regression. Linear Regression,Log-Linear Models,Models, Linear,Linear Model,Linear Regressions,Log Linear Models,Log-Linear Model,Model, Linear,Model, Log-Linear,Models, Log-Linear,Regression, Linear,Regressions, Linear
D016015 Logistic Models Statistical models which describe the relationship between a qualitative dependent variable (that is, one which can take only certain discrete values, such as the presence or absence of a disease) and an independent variable. A common application is in epidemiology for estimating an individual's risk (probability of a disease) as a function of a given risk factor. Logistic Regression,Logit Models,Models, Logistic,Logistic Model,Logistic Regressions,Logit Model,Model, Logistic,Model, Logit,Models, Logit,Regression, Logistic,Regressions, Logistic
D016016 Proportional Hazards Models Statistical models used in survival analysis that assert that the effect of the study factors on the hazard rate in the study population is multiplicative and does not change over time. Cox Model,Cox Proportional Hazards Model,Hazard Model,Hazards Model,Hazards Models,Models, Proportional Hazards,Proportional Hazard Model,Proportional Hazards Model,Cox Models,Cox Proportional Hazards Models,Hazard Models,Proportional Hazard Models,Hazard Model, Proportional,Hazard Models, Proportional,Hazards Model, Proportional,Hazards Models, Proportional,Model, Cox,Model, Hazard,Model, Hazards,Model, Proportional Hazard,Model, Proportional Hazards,Models, Cox,Models, Hazard,Models, Hazards,Models, Proportional Hazard
D016019 Survival Analysis A class of statistical procedures for estimating the survival function (function of time, starting with a population 100% well at a given time and providing the percentage of the population still well at later times). The survival analysis is then used for making inferences about the effects of treatments, prognostic factors, exposures, and other covariates on the function. Analysis, Survival,Analyses, Survival,Survival Analyses
D016027 Heart Transplantation The transference of a heart from one human or animal to another. Cardiac Transplantation,Grafting, Heart,Transplantation, Cardiac,Transplantation, Heart,Cardiac Transplantations,Graftings, Heart,Heart Grafting,Heart Graftings,Heart Transplantations,Transplantations, Cardiac,Transplantations, Heart

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