12. Quality-Adjusted Survival

  1. Peter M. Fayers1,2 and
  2. David Machin3,4

Published Online: 8 MAR 2002

DOI: 10.1002/0470846283.ch12

Quality of Life: Assessment, Analysis and Interpretation

Quality of Life: Assessment, Analysis and Interpretation

How to Cite

Fayers, P. M. and Machin, D. (2000) Quality-Adjusted Survival, in Quality of Life: Assessment, Analysis and Interpretation, John Wiley & Sons, Ltd, Chichester, UK. doi: 10.1002/0470846283.ch12

Author Information

  1. 1

    Medical Research Council Clinical Trials Unit, London, UK

  2. 2

    Unit of Applied Clinical Research, Norwegian University of Science and Technology, Trondheim, Norway

  3. 3

    NMRC Clinical Trials & Epidemiology Research Unit, Singapore

  4. 4

    School of Health and Related Research, University of Sheffield, UK

Publication History

  1. Published Online: 8 MAR 2002
  2. Published Print: 18 APR 2000

ISBN Information

Print ISBN: 9780471968610

Online ISBN: 9780470846285



  • visual analogue rating scales (VAS);
  • time trade-off (TTO);
  • multi-attribute utility measures;
  • utility-based instruments;
  • quality-adjusted life years (QALYs);
  • Q-TWiST;
  • sensitivity analysis


The overall survival time following diagnosis in a patient with a life-threatening disease may be considered as partitioned into distinct periods during which the QoL levels of the patient may expect to differ. Once the time in each of these states is determined, they can be used to calculate the time without symptoms and toxicity (TWiST); the time actually experiencing symptoms and/or toxicity (TOX): and the time in relapse following progression of the disease (PROG).

Utility coefficients (once defined) corresponding to each of these states can be used as multipliers of TOX, TWiST and PROG to obtain a weighted quality-adjusted time without symptoms and toxicity (Q-TWiST). These are then averaged over all patients receiving a particular treatment and so can be used to compare treatments.

Threshold analysis enables the investigations of how sensitive the difference in treatments so quantified is on the values of the utility coefficients of each state. The way in which Q-TWiST may be compared between different prognostic groups, and changes over successive time intervals from diagnosis, are described.