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2014•Unpublished venueRequires access

Accelerated Failure Time Models: An Application in the Survival of Acute Liver Failure Patients in India

Shankar Prasad Khanal, V. Sreenivas, Subrat Kumar Acharya

Open publisher page 39 citations

Abstract

Accelerated Failure Time (AFT) models can be used for the analysis of time to event data to estimate the effects of covariates on acceleration/deceleration of the survival time. The effect of the covariate is measured through a log-linear model taking logarithm of the survival time as the outcome or dependent variable. Hence, the effect of covariate is multiplicative on time scale, and the results of AFT models may be easier to interpret as the covariate effects are directly expressed in terms of time ratio (TR). Some AFT models are applied to the data on time to death of hospitalized Acute Liver Failure (ALF) patients in All India Institute of Medical Sciences, New Delhi, India to identify the prognostic factors. This type of study is being carried out for the first time in Indian population using retrospective data of ALF patients using AFT models.

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What this paper is about

Accelerated Failure Time (AFT) models can be used for the analysis of time to event data to estimate the effects of covariates on acceleration/deceleration of the survival time. The effect of the covariate is measured through a log-linear model taking logarithm of the survival time as the outcome or dependent variable. Hence, the effect of covariate is multiplicative on time scale, and the results of AFT models may be easier to interpret as the covariate effects are directly expressed in terms of time ratio (TR). Some AFT models are applied to the data on time to death of hospitalized Acute Liver Failure (ALF) patients in All India Institute of Medical Sciences, New Delhi, India to identify the prognostic factors. This type of study is being carried out for the first time in Indian population using retrospective data of ALF patients using AFT models.

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Available abstract

Accelerated Failure Time (AFT) models can be used for the analysis of time to event data to estimate the effects of covariates on acceleration/deceleration of the survival time. The effect of the covariate is measured through a log-linear model taking logarithm of the survival time as the outcome or dependent variable. Hence, the effect of covariate is multiplicative on time scale, and the results of AFT models may be easier to interpret as the covariate effects are directly expressed in terms of time ratio (TR). Some AFT models are applied to the data on time to death of hospitalized Acute Liver Failure (ALF) patients in All India Institute of Medical Sciences, New Delhi, India to identify the prognostic factors. This type of study is being carried out for the first time in Indian population using retrospective data of ALF patients using AFT models.

Key concepts: Covariate, Accelerated failure time model, Survival analysis, Statistics, Medicine, Multiplicative function, Event data, Proportional hazards model

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Accelerated Failure Time Models: An Application in the Survival of Acute Liver Failure Patients in India — Research Paper | ScholarLens