Literature DB >> 12231054

A review of measurement of patient preferences for treatment outcomes after prostate cancer.

Deborah P Lubeck1, Gary D Grossfeld, Peter R Carroll.   

Abstract

The diagnosis of early-stage prostate cancer cases creates dilemmas for many men diagnosed with the disease each year. Treatment interventions are all associated with significant treatment morbidity, including impotence and incontinence. The basic concept behind patient preferences, or utilities, is to ask patients to make judgments about the value of particular health outcomes. Several preference-based instruments are available, including the visual analog rating scale, the time trade-off utility assessment, and the standard gamble. These assessments result in scores or weights assigned to different health states. From the perspective of the patient with prostate cancer, the treatment that produces optimal outcomes will depend on the relative importance of several domains, which may include pain, urinary functioning, sexual functioning, and general physical health. Patients with similar diagnoses and overlapping clinical characteristics may have markedly different preferences for treatment outcomes.

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Year:  2002        PMID: 12231054     DOI: 10.1016/s0090-4295(02)01577-7

Source DB:  PubMed          Journal:  Urology        ISSN: 0090-4295            Impact factor:   2.649


  4 in total

Review 1.  Patient preferences for the treatment of type 2 diabetes: a scoping review.

Authors:  Susan M Joy; Emily Little; Nisa M Maruthur; Tanjala S Purnell; John F P Bridges
Journal:  Pharmacoeconomics       Date:  2013-10       Impact factor: 4.981

2.  Survival gains needed to offset persistent adverse treatment effects in localised prostate cancer.

Authors:  M T King; R Viney; D P Smith; I Hossain; D Street; E Savage; S Fowler; M P Berry; M Stockler; P Cozzi; P Stricker; J Ward; B K Armstrong
Journal:  Br J Cancer       Date:  2012-01-24       Impact factor: 7.640

Review 3.  Factors that influence patient preferences for prostate cancer management options: A systematic review.

Authors:  Timothy N Showalter; Mark V Mishra; John Fp Bridges
Journal:  Patient Prefer Adherence       Date:  2015-07-02       Impact factor: 2.711

4.  Latent class cluster analysis to understand heterogeneity in prostate cancer treatment utilities.

Authors:  Salimah H Meghani; Christopher S Lee; Alexandra L Hanlon; Deborah W Bruner
Journal:  BMC Med Inform Decis Mak       Date:  2009-11-27       Impact factor: 2.796

  4 in total

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