Literature DB >> 26039695

Use of forecasted assessment of quality of life to validate time-trade-off utilities and a prostate cancer screening decision-analytic model.

Scott B Cantor1, Ashish A Deshmukh1, Murray D Krahn2, Robert J Volk3.   

Abstract

PURPOSE: To determine whether the forecasted assessment of how someone would feel in a future health state can be predictive of utilities (e.g. as elicited by the time-trade-off method) and also predictive of optimal decisions as determined by a decision-analytic model.
METHODS: We elicited time-trade-off utilities for prostate cancer treatment outcomes from 168 men. We also elicited forecasted assessments, that is, an informal, non-quantitative, descriptive evaluation, of impotence and incontinence from these men. We used multivariate regression analysis to explore the relationship between forecasted assessment and reluctance to trade length for improved quality of life, that is, the unwillingness to trade length of life for improved quality of life in the time-trade-off utility assessment and the relationship between the forecasted assessments and the optimal decision of whether to undergo screening for prostate cancer as determined from a previously published decision-analytic model.
RESULTS: Importance of sexual function was strongly related to impotence utilities (P < 0.05). Based on the multivariate analysis, significant predictors for the utility of severe incontinence were family income, family history of prostate cancer, work status and attitude towards needing to wear an incontinence pad. However, no variables were statistically significant predictors for the utility of complete impotence. The importance of sexual functioning was a significant predictor of the optimal decision.
CONCLUSION: Anticipated difficulty adjusting to adverse health effects were highly related to preferences and could be used as a proxy measure of utility. Similarly, the importance of sexual functioning, a future preference, was highly related to the optimal decision, which validates our previously published decision-analytic model.
© 2013 John Wiley & Sons Ltd.

Entities:  

Keywords:  decision making; decision support techniques; mass screening; prostate neoplasm; quality of life

Mesh:

Year:  2013        PMID: 26039695      PMCID: PMC5060828          DOI: 10.1111/hex.12150

Source DB:  PubMed          Journal:  Health Expect        ISSN: 1369-6513            Impact factor:   3.377


  19 in total

1.  Concordance of couples' prostate cancer screening recommendations from a decision analysis.

Authors:  Scott B Cantor; Robert J Volk; Murray D Krahn; Alvah R Cass; Jawaria Gilani; Susan C Weller; Stephen J Spann
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2.  Predictors and prevalence of erectile dysfunction in a racially diverse population.

Authors:  Christopher S Saigal; Hunter Wessells; Jennifer Pace; Matt Schonlau; Timothy J Wilt
Journal:  Arch Intern Med       Date:  2006-01-23

3.  Screening for prostate cancer: U.S. Preventive Services Task Force recommendation statement.

Authors:  Virginia A Moyer
Journal:  Ann Intern Med       Date:  2012-07-17       Impact factor: 25.391

4.  A brief male sexual function inventory for urology.

Authors:  M P O'Leary; F J Fowler; W R Lenderking; B Barber; P P Sagnier; H A Guess; M J Barry
Journal:  Urology       Date:  1995-11       Impact factor: 2.649

5.  The "utility" of the Time Trade-Off method in cancer patients: feasibility and proportional Trade-Off.

Authors:  A M Stiggelbout; G M Kiebert; J Kievit; J W Leer; J D Habbema; J C De Haes
Journal:  J Clin Epidemiol       Date:  1995-10       Impact factor: 6.437

6.  Predictors of utilities for health states in early stage prostate cancer.

Authors:  C S Saigal; J Gornbein; R Nease; M S Litwin
Journal:  J Urol       Date:  2001-09       Impact factor: 7.450

7.  Health values of hospitalized patients 80 years or older. HELP Investigators. Hospitalized Elderly Longitudinal Project.

Authors:  J Tsevat; N V Dawson; A W Wu; J Lynn; J R Soukup; E F Cook; H Vidaillet; R S Phillips
Journal:  JAMA       Date:  1998-02-04       Impact factor: 56.272

8.  Relation of family history of prostate cancer to perceived vulnerability and screening behavior.

Authors:  Paul B Jacobsen; Laurie A Lamonde; Melissa Honour; Kathryn Kash; Perry B Hudson; Julio Pow-Sang
Journal:  Psychooncology       Date:  2004-02       Impact factor: 3.894

9.  Stability of time trade-off utilities for health states associated with the treatment of prostate cancer.

Authors:  Christopher S Saigal; Jeffrey Gornbein; Kristen Reid; Mark S Litwin
Journal:  Qual Life Res       Date:  2002-08       Impact factor: 4.147

10.  Preferences of husbands and wives for outcomes of prostate cancer screening and treatment.

Authors:  Robert J Volk; Scott B Cantor; Alvah R Cass; Stephen J Spann; Susan C Weller; Murray D Krahn
Journal:  J Gen Intern Med       Date:  2004-04       Impact factor: 5.128

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  1 in total

Review 1.  A Systematic Review and Meta-Analysis of Prostate Cancer Utility Values of Patients and Partners Between 2007 and 2016.

Authors:  Anne Magnus; Wanrudee Isaranuwatchai; Cathrine Mihalopoulos; Victoria Brown; Rob Carter
Journal:  MDM Policy Pract       Date:  2019-05-27
  1 in total

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