Survival analysis: Kaplan-Meier and life table estimates for time to event clinical trial tuberculosis data.

Kripasankar, A.S.; Ravanan, R.; Ponnuraja, C.

Concepts in Pure and Applied Science; 2013; 1; 17-21.

Abstract: In clinical trials, the effect of an intervention is assessed by measuring the number of subjects survived or recovered from disease during and in fact after the intervention over a period of time. All the conventional approaches are failing in managing the data with censored observations. The Kaplan-Meier estimate is the simplest way of computing the survival over time in spite of all these difficulties associated with subjects. The purpose is to estimate a population survival curve from a sample. If every patient is followed until event, the curve may be estimated simply by computing the fraction surviving at each time. In this article, it emphasizes the usage of Kaplan-Meier and life table methods for randomized controlled clinical trial tuberculosis data for their time to smear conversion from diseased period to normal. All patients are having positive results at their entry into the trial. 257 tuberculosis patients are administered with four types of treatments. The event of interest is time to sputum conversion. 225 cases experience the event during the treatment period and only 32 cases do not experience the event. It means that all the 32 cases are censored observations. Types of treatment (regimen) and gender (sex) are the main covariates taken into analysis and resulted that there is no difference among treatments in time to smear conversion but there is a difference between genders.

Keywords: Survival Analysis; Kaplan-Meier; Life table

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