Methods for Estimating Survival Time of Treatments for Renal Dialysis

Authors

  • Sri Astuti Thamrin

DOI:

https://doi.org/10.20956/jmsk.v14i2.3551

Abstract

This papes discusses the theory and application of statistical methods for describing and analyzing survival times of the renal dialysis patients : a) from the first diagnosis until the time of death, and b) on each mode of given treatment. The paper also tries to predict the variables significantly effecting the survival time of renal dialysis patients. The paper makes use of and focuses on the data sets containing patient hospital records, patients’ identity and hospital code centre. To meet the desired aims, the paper uses two prominent methods of survival analysis including the Kaplan-Meier and Cox Proportional Hazard model. The result shows that survival time on the first treatment depends on mode of treatment and it quite low approximately 18 days for median time on hospital outpatient CAPD. Similarly, survival time on the second treatment is quite low about 24 days for the median time on hospital outpatient CAPD. It was also indicated that the survival time of renal dialysis patient depends on the number of treatments, the number of treatment changes, place of treatment, age and the first treatment

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References

CCEB, 2004, “Parametric and semiparametric methods for survival data”, Module 6 of Advanced Biostatistics, University of Newcastle, Australia.

. Cox, R.D., 1984, “Analysis of Survival Data”, Chapman and Hall, Melbourne, Australia.

. Efron, B., 1988, “Logistic regression, survival analysis and the Kaplan-Meier curve”, Journal of the American Statistical Association, Vol. 83, No. 402.

. Galbriath, S., 2004, “Statistics for Biomedical research”, Course Notes, University of New South Wales, Australia.

. Glant, S., 2001, “Primer of Biostatistics”, McGraw-Hill, USA.

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Published

2018-03-19

Issue

Section

Research Articles