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United States Utility Algorithm for the EORTC QLU-C10D, a Multiattribute Utility Instrument Based on a Cancer-Specific Quality-of-Life Instrument.
Revicki, Dennis A; King, Madeleine T; Viney, Rosalie; Pickard, A Simon; Mercieca-Bebber, Rebecca; Shaw, James W; Müller, Fabiola; Norman, Richard.
Afiliação
  • Revicki DA; Patient-Centered Outcomes Research, Evidera, Bethesda, MD, USA.
  • King MT; School of Psychology, Sydney, University of Sydney, New South Wales, Australia.
  • Viney R; Centre for Health Economics Research & Evaluation, UTS Business School, University of Technology Sydney, Sydney, New South Wales, Australia.
  • Pickard AS; Department of Pharmacy Systems, Outcomes and Policy, College of Pharmacy, University of Illinois at Chicago, Chicago, IL, USA.
  • Mercieca-Bebber R; School of Psychology, Sydney, University of Sydney, New South Wales, Australia.
  • Shaw JW; NHMRC Clinical Trials Centre, Faculty of Medicine, University of Sydney, Sydney, New South Wales, Australia.
  • Müller F; Patient-Reported Outcomes Assessment, Worldwide Health Economics and Outcomes Research, Bristol Myers Squibb, Lawrenceville, NJ, USA.
  • Norman R; School of Psychology, Sydney, University of Sydney, New South Wales, Australia.
Med Decis Making ; 41(4): 485-501, 2021 05.
Article em En | MEDLINE | ID: mdl-33813946
ABSTRACT

BACKGROUND:

The EORTC QLU-C10D is a multiattribute utility measure derived from the cancer-specific quality-of-life questionnaire, the EORTC QLQ-C30. The QLU-C10D contains 10 dimensions (physical, role, social and emotional functioning, pain, fatigue, sleep, appetite, nausea, bowel problems). The objective of this study was to develop a United States value set for the QLU-C10D.

METHODS:

A US online panel was quota recruited to achieve a representative sample for sex, age (≥18 y), race, and ethnicity. Respondents undertook a discrete choice experiment, each completing 16 choice-pairs, randomly assigned from a total of 960 choice-pairs. Each pair included 2 QLU-C10D health states and duration. Data were analyzed using conditional logistic regression, parameterized to fit the quality-adjusted life-year framework. Utility weights were calculated as the ratio of each dimension-level coefficient to the coefficient for life expectancy.

RESULTS:

A total of 2480 panel members opted in, 2333 (94%) completed at least 1 choice-pair, and 2273 (92%) completed all choice-pairs. Within dimensions, weights were generally monotonic. Physical functioning, role functioning, and pain were associated with the largest utility weights. Cancer-specific dimensions, such as nausea and bowel problems, were associated with moderate utility decrements, as were general issues such as problems with emotional functioning and social functioning. Sleep problems and fatigue were associated with smaller utility decrements. The value of the worst health state was 0.032, which was slightly greater than 0 (equivalent to being dead).

CONCLUSIONS:

This study provides the US-specific value set for the QLU-C10D. These estimated health state scores, based on responses to the EORTC QLQ-C30 questionnaire, can be used to evaluate the cost-utility of oncology treatments.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Qualidade de Vida / Neoplasias Tipo de estudo: Prognostic_studies Limite: Humans País/Região como assunto: America do norte Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Qualidade de Vida / Neoplasias Tipo de estudo: Prognostic_studies Limite: Humans País/Região como assunto: America do norte Idioma: En Ano de publicação: 2021 Tipo de documento: Article