Monte Carlo estimation of extrapolation of quality-adjusted survival for follow-up studies

✍ Scribed by Jing-Shiang Hwang; Jung-Der Wang

• Book ID: 101238628
• Publisher: John Wiley and Sons
• Year: 1999
• Tongue: English
• Weight: 149 KB
• Volume: 18
• Category: Article
• ISSN: 0277-6715
• DOI: 10.1002/(sici)1097-0258(19990715)18:13<1627::aid-sim159>3.0.co;2-d

✦ Synopsis

The expected quality-adjusted survival (QAS) for an index population with a speci"c 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 "rst created a reference population from the life tables of the general population according to the Monte Carlo method. Secondly, we "tted 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 "tted 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.