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

Stat Med. 1999 Jul 15;18(13):1627-40. doi: 10.1002/(sici)1097-0258(19990715)18:13<1627::aid-sim159>;2-d.


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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Computer Simulation
  • Female
  • Follow-Up Studies
  • Humans
  • Life Tables
  • Linear Models
  • Male
  • Middle Aged
  • Monte Carlo Method*
  • Proportional Hazards Models
  • Quality-Adjusted Life Years*
  • Survival Analysis*
  • Survival Rate
  • Taiwan / epidemiology