TY - JOUR
T1 - The Functional Assessment of Cancer Therapy Eight Dimension (FACT-8D), a Multi-Attribute Utility Instrument Derived From the Cancer-Specific FACT-General (FACT-G) Quality of Life Questionnaire: Development and Australian Value Set
AU - Multi-Attribute Utility in Cancer Consortium
AU - King, M. T.
AU - Norman, Richard
AU - Mercieca-Bebber, Rebecca
AU - Costa, Daniel S.J.
AU - McTaggart-Cowan, Helen
AU - Peacock, Stuart
AU - Janda, Monika
AU - Müller, Fabiola
AU - Viney, R.
AU - Pickard, Alan Simon
AU - Cella, David
AU - Aaronson, N.
AU - Brazier, J.
AU - Cella, D.
AU - Costa, D. S.J.
AU - Fayers, P.
AU - Grimison, P.
AU - Janda, M.
AU - Kemmler, G.
AU - King, M. T.
AU - McTaggart-Cowan, H.
AU - Mercieca-Bebber, R.
AU - Norman, R.
AU - Peacock, S.
AU - Pickard, A. S.
AU - Rowen, D.
AU - Velikova, G.
AU - Viney, R.
AU - Street, D.
AU - Young, T.
N1 - Funding Information:
Funding/Support: This work was supported by Project Grant 632662 from the Australian National Health and Medical Research Council (NHMRC) Professor King was supported by the Australian Government through Cancer Australia and Professor Janda was supported by a NHMRC Translating Research into Practice Fellowship during the conduct of the study.
Funding Information:
Conflict of Interest Disclosures: Dr Norman is an editor for Value in Health and had no role in the peer review process of this article. Dr Viney is a member of the Scientific Executive of the EuroQol Foundation and reported receiving a grant from the EuroQoL Foundation outside the submitted work. Dr Cella reported receiving personal fees from FACIT.org outside the submitted work. No other disclosures were reported.
Publisher Copyright:
© 2021 ISPOR–The Professional Society for Health Economics and Outcomes Research
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2021/6
Y1 - 2021/6
N2 - Objectives: To develop a cancer-specific multi-attribute utility instrument derived from the Functional Assessment of Cancer Therapy - General (FACT-G) health-related quality of life (HRQL) questionnaire. Methods: We derived a descriptive system based on a subset of the 27-item FACT-G. Item selection was informed by psychometric analyses of existing FACT-G data (n = 6912) and by patient input (n = 82). We then conducted an online valuation survey, with participants recruited via an Australian general population online panel. A discrete choice experiment (DCE) was used, with attributes being the HRQL dimensions of the descriptive system and survival duration, and 16 choice-pairs per participant. Utility decrements were estimated with conditional logit and mixed logit modeling. Results: Eight HRQL dimensions were included in the descriptive system: pain, fatigue, nausea, sleep, work, social support, sadness, and future health worry; each with 5 levels. Of 1737 panel members who accessed the valuation survey, 1644 (95%) completed 1 or more DCE choice-pairs and were included in analyses. Utility decrements were generally monotonic; within each dimension, poorer HRQL levels generally had larger utility decrements. The largest utility decrements were for the highest levels of pain (-0.40) and nausea (-0.28). The worst health state had a utility of -0.54, considerably worse than dead. Conclusions: A descriptive system and preference-based scoring approach were developed for the FACT-8D, a new cancer-specific multi-attribute utility instrument derived from the FACT-G. The Australian value set is the first of a series of country-specific value sets planned that can facilitate cost-utility analyses based on items from the FACT-G and related FACIT questionnaires containing FACT-G items.
AB - Objectives: To develop a cancer-specific multi-attribute utility instrument derived from the Functional Assessment of Cancer Therapy - General (FACT-G) health-related quality of life (HRQL) questionnaire. Methods: We derived a descriptive system based on a subset of the 27-item FACT-G. Item selection was informed by psychometric analyses of existing FACT-G data (n = 6912) and by patient input (n = 82). We then conducted an online valuation survey, with participants recruited via an Australian general population online panel. A discrete choice experiment (DCE) was used, with attributes being the HRQL dimensions of the descriptive system and survival duration, and 16 choice-pairs per participant. Utility decrements were estimated with conditional logit and mixed logit modeling. Results: Eight HRQL dimensions were included in the descriptive system: pain, fatigue, nausea, sleep, work, social support, sadness, and future health worry; each with 5 levels. Of 1737 panel members who accessed the valuation survey, 1644 (95%) completed 1 or more DCE choice-pairs and were included in analyses. Utility decrements were generally monotonic; within each dimension, poorer HRQL levels generally had larger utility decrements. The largest utility decrements were for the highest levels of pain (-0.40) and nausea (-0.28). The worst health state had a utility of -0.54, considerably worse than dead. Conclusions: A descriptive system and preference-based scoring approach were developed for the FACT-8D, a new cancer-specific multi-attribute utility instrument derived from the FACT-G. The Australian value set is the first of a series of country-specific value sets planned that can facilitate cost-utility analyses based on items from the FACT-G and related FACIT questionnaires containing FACT-G items.
KW - condition-specific
KW - health-related quality of life
KW - multi-attribute utility
KW - preference-based
KW - QALY
KW - quality of life
KW - quality-adjusted life-year
KW - utility
KW - value set
UR - http://www.scopus.com/inward/record.url?scp=85106291128&partnerID=8YFLogxK
U2 - 10.1016/j.jval.2021.01.007
DO - 10.1016/j.jval.2021.01.007
M3 - Article
AN - SCOPUS:85106291128
SN - 1098-3015
VL - 24
SP - 862
EP - 873
JO - Value in Health
JF - Value in Health
IS - 6
ER -