| Literature DB >> 10407234 |
Abstract
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. Copyright 1999 John Wiley & Sons, Ltd.Mesh:
Year: 1999 PMID: 10407234 DOI: 10.1002/(sici)1097-0258(19990715)18:13<1627::aid-sim159>3.0.co;2-d
Source DB: PubMed Journal: Stat Med ISSN: 0277-6715 Impact factor: 2.373