Monte Carlo estimation of extrapolation of quality-adjusted survival for follow-up studies.
The expected quality-adjusted survival (QAS) for an index population with a specific disease can be estimated by summing the product of the survival function and the mean quality of life function of the population. In many follow-up studies with heavy censoring, the expected QAS may not be well estimated due to the lack of data beyond the close of follow-up. In this paper, we first created a reference population from the life tables of the general population according to the Monte Carlo method. Secondly, we fitted a simple linear regression line to the logit of the ratio of quality-adjusted survival functions for the index and reference populations up to the end of follow-up. Finally, combining information on the reference population with the fitted line, we predicted the expected quality-adjusted survival curve beyond the follow-up period for the index population. Simulation studies have shown that the simple Monte Carlo estimation procedure is a potential approach for estimating expected QAS and the survival function beyond the follow-up with a certain degree of accuracy.
Institute of Statistical Science, Academia Sinica, Taipei 115, Taiwan. jshwang@stat.sinica.edu.tw
J S
JS
Hwang
J D
JD
Wang
D003198:Computer Simulation; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D015993:Life Tables; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D009010:Monte Carlo Method; D016016:Proportional Hazards Models; D019057:Quality-Adjusted Life Years; D016019:Survival Analysis; D015996:Survival Rate; D013624:Taiwan / Q000453:epidemiology