Do clinical marker states improve responsiveness and construct validity of the standard gamble and feeling thermometer: a randomized multi-center trial in patients with chronic respiratory disease

Qual Life Res. 2006 Feb;15(1):1-14. doi: 10.1007/s11136-005-0126-x.

Abstract

Background: Optimizing the validity and responsiveness of utility measures will enhance their usefulness in randomized trials. We evaluated the impact of clinical marker state (CMS) rating prior to patients' rating their own health on two utility instruments (feeling thermometer (FT) and standard gamble (SG)) in patients with chronic respiratory disease (CRD).

Methods: We randomized 182 patients with CRD to complete the FT (self-administered) and SG with CMS (FT+/SG+, n=91) or without marker states (FT-/SG-, n=91) before and after undergoing respiratory rehabilitation in a multi-center trial.

Results: Use of CMS did not influence baseline utility scores. Improvement after therapy on the scale from 0 (dead) to 1.0 (full health) was 0.04 both in FT+ (p=0.03) and FT- (p=0.02; the difference between FT+ and FT- was 0.00, p=0.83). Improvement on the SG was 0.05 in both SG+ (p=0.08) and SG- (p=0.04; difference between SG+ and SG- 0.00, p=0.95). Correlations with other health related quality of life scores were highest for FT+.

Conclusion: Administration of CMS did not improve responsiveness of the FT but may have improved construct validity. The SG showed limited construct validity and responsiveness that was not influenced by CMS use.

Publication types

  • Multicenter Study
  • Randomized Controlled Trial
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Aged, 80 and over
  • Attitude to Health*
  • Biomarkers
  • Chronic Disease
  • Female
  • Humans
  • Male
  • Middle Aged
  • Pain Measurement
  • Patient Satisfaction*
  • Quality of Life / psychology*
  • Reproducibility of Results
  • Respiration Disorders / mortality
  • Respiration Disorders / psychology*
  • Respiration Disorders / rehabilitation
  • Respiratory Function Tests
  • Sickness Impact Profile
  • Surveys and Questionnaires
  • Treatment Outcome
  • Value of Life

Substances

  • Biomarkers