United States Value Set for the Functional Assessment of Cancer Therapy-General Eight Dimensions (FACT-8D), a Cancer-Specific Preference-Based Quality of Life Instrument.

King, MT; Revicki, DA; Norman, R; Müller, F; Viney, RC; Pickard, AS; Cella, D; Shaw, JW; MAUCa Consortium,

United States Value Set for the Functional Assessment of Cancer Therapy-General Eight Dimensions (FACT-8D), a Cancer-Specific Preference-Based Quality of Life Instrument.

King, MT Revicki, DA Norman, R Müller, F Viney, RC Pickard, AS Cella, D Shaw, JW MAUCa Consortium,

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Publisher:: SPRINGER INT PUBL AG
Publication Type:: Journal Article
Citation:: Pharmacoecon Open, 2024, 8, (1), pp. 49-63
Issue Date:: 2024-01

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Field	Value	Language
dc.contributor.author	King, MT
dc.contributor.author	Revicki, DA
dc.contributor.author	Norman, R
dc.contributor.author	Müller, F
dc.contributor.author	Viney, RC
dc.contributor.author	Pickard, AS
dc.contributor.author	Cella, D
dc.contributor.author	Shaw, JW
dc.contributor.author	MAUCa Consortium,
dc.date.accessioned	2024-01-24T06:29:14Z
dc.date.available	2023-10-11
dc.date.available	2024-01-24T06:29:14Z
dc.date.issued	2024-01
dc.identifier.citation	Pharmacoecon Open, 2024, 8, (1), pp. 49-63
dc.identifier.issn	2509-4262
dc.identifier.issn	2509-4254
dc.identifier.uri	http://hdl.handle.net/10453/174907
dc.description.abstract	OBJECTIVES: To develop a value set reflecting the United States (US) general population's preferences for health states described by the Functional Assessment of Cancer Therapy (FACT) eight-dimensions preference-based multi-attribute utility instrument (FACT-8D), derived from the FACT-General cancer-specific health-related quality-of-life (HRQL) questionnaire. METHODS: A US online panel was quota-sampled to achieve a general population sample representative by sex, age (≥ 18 years), race and ethnicity. A discrete choice experiment (DCE) was used to value health states. The valuation task involved choosing between pairs of health states (choice-sets) described by varying levels of the FACT-8D HRQL dimensions and survival (life-years). The DCE included 100 choice-sets; each respondent was randomly allocated 16 choice-sets. Data were analysed using conditional logit regression parameterized to fit the quality-adjusted life-year framework, weighted for sociodemographic variables that were non-representative of the US general population. Preference weights were calculated as the ratio of HRQL-level coefficients to the survival coefficient. RESULTS: 2562 panel members opted in, 2462 (96%) completed at least one choice-set and 2357 (92%) completed 16 choice-sets. Pain and nausea were associated with the largest utility weights, work and sleep had more moderate utility weights, and sadness, worry and support had the smallest utility weights. Within dimensions, more severe HRQL levels were generally associated with larger weights. A preference-weighting algorithm to estimate US utilities from responses to the FACT-General questionnaire was generated. The worst health state's value was -0.33. CONCLUSIONS: This value set provides US population utilities for health states defined by the FACT-8D for use in evaluating oncology treatments.
dc.format	Print-Electronic
dc.language	eng
dc.publisher	SPRINGER INT PUBL AG
dc.relation	http://purl.org/au-research/grants/nhmrc/632662
dc.relation.ispartof	Pharmacoecon Open
dc.relation.isbasedon	10.1007/s41669-023-00448-5
dc.rights	info:eu-repo/semantics/openAccess
dc.title	United States Value Set for the Functional Assessment of Cancer Therapy-General Eight Dimensions (FACT-8D), a Cancer-Specific Preference-Based Quality of Life Instrument.
dc.type	Journal Article
utslib.citation.volume	8
utslib.location.activity	Switzerland
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Health
pubs.organisational-group	University of Technology Sydney/Strength - CHERE - Centre for Health Economics Research and Evaluation
pubs.organisational-group	University of Technology Sydney/Faculty of Health/Centre for Health Economics Research and Evaluation
utslib.copyright.status	open_access	*
dc.date.updated	2024-01-24T06:29:12Z
pubs.issue	1
pubs.publication-status	Published
pubs.volume	8
utslib.citation.issue	1

Abstract:

OBJECTIVES: To develop a value set reflecting the United States (US) general population's preferences for health states described by the Functional Assessment of Cancer Therapy (FACT) eight-dimensions preference-based multi-attribute utility instrument (FACT-8D), derived from the FACT-General cancer-specific health-related quality-of-life (HRQL) questionnaire. METHODS: A US online panel was quota-sampled to achieve a general population sample representative by sex, age (≥ 18 years), race and ethnicity. A discrete choice experiment (DCE) was used to value health states. The valuation task involved choosing between pairs of health states (choice-sets) described by varying levels of the FACT-8D HRQL dimensions and survival (life-years). The DCE included 100 choice-sets; each respondent was randomly allocated 16 choice-sets. Data were analysed using conditional logit regression parameterized to fit the quality-adjusted life-year framework, weighted for sociodemographic variables that were non-representative of the US general population. Preference weights were calculated as the ratio of HRQL-level coefficients to the survival coefficient. RESULTS: 2562 panel members opted in, 2462 (96%) completed at least one choice-set and 2357 (92%) completed 16 choice-sets. Pain and nausea were associated with the largest utility weights, work and sleep had more moderate utility weights, and sadness, worry and support had the smallest utility weights. Within dimensions, more severe HRQL levels were generally associated with larger weights. A preference-weighting algorithm to estimate US utilities from responses to the FACT-General questionnaire was generated. The worst health state's value was -0.33. CONCLUSIONS: This value set provides US population utilities for health states defined by the FACT-8D for use in evaluating oncology treatments.

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http://hdl.handle.net/10453/174907