Preliminary Validation of an Optimally Weighted Patient-Based Utility Index by Application to Randomized Trials in Breast Cancer

Grimison, Peter; Simes, R. John; Hudson, H. Malcolm; Stockler, Martin R.

doi:10.1111/j.1524-4733.2009.00536.x

Cited by 4 publications

(4 citation statements)

References 63 publications

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“… 24 – 26 Only one study, from Australia, reported use of the cancer-specific measure UBQ-C and the subscales were converted to a utility index. 15 …”

Section: Resultsmentioning

confidence: 99%

A structured review of health utility measures and elicitation in advanced/metastatic breast cancer

Hao

Wolfram²,

Cook³

2016

CEOR

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BackgroundHealth utilities are increasingly incorporated in health economic evaluations. Different elicitation methods, direct and indirect, have been established in the past. This study examined the evidence on health utility elicitation previously reported in advanced/metastatic breast cancer and aimed to link these results to requirements of reimbursement bodies.MethodsSearches were conducted using a detailed search strategy across several electronic databases (MEDLINE, EMBASE, Cochrane Library, and EconLit databases), online sources (Cost-effectiveness Analysis Registry and the Health Economics Research Center), and web sites of health technology assessment (HTA) bodies. Publications were selected based on the search strategy and the overall study objectives.ResultsA total of 768 publications were identified in the searches, and 26 publications, comprising 18 journal articles and eight submissions to HTA bodies, were included in the evidence review. Most journal articles derived utilities from the European Quality of Life Five-Dimensions questionnaire (EQ-5D). Other utility measures, such as the direct methods standard gamble (SG), time trade-off (TTO), and visual analog scale (VAS), were less frequently used. Several studies described mapping algorithms to generate utilities from disease-specific health-related quality of life (HRQOL) instruments such as European Organization for Research and Treatment of Cancer Quality of Life Questionnaire – Core 30 (EORTC QLQ-C30), European Organization for Research and Treatment of Cancer Quality of Life Questionnaire – Breast Cancer 23 (EORTC QLQ-BR23), Functional Assessment of Cancer Therapy – General questionnaire (FACT-G), and Utility-Based Questionnaire-Cancer (UBQ-C); most used EQ-5D as the reference. Sociodemographic factors that affect health utilities, such as age, sex, income, and education, as well as disease progression, choice of utility elicitation method, and country settings, were identified within the journal articles. Most submissions to HTA bodies obtained utility values from the literature rather than exploring the HRQOL data obtained during clinical development. This was critiqued by the National Institute for Health and Clinical Excellence (NICE). Furthermore, the impact of age on utilities was highlighted by NICE and it was suggested that an age match of the study population should be attempted.ConclusionHealth utilities are recorded across the globe to varying extents and using differing elicitation methods. Manufacturers seeking reimbursement need to be aware of the country-specific requirements for elicitation of health utilities.

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“… 24 – 26 Only one study, from Australia, reported use of the cancer-specific measure UBQ-C and the subscales were converted to a utility index. 15 …”

Section: Resultsmentioning

confidence: 99%

A structured review of health utility measures and elicitation in advanced/metastatic breast cancer

Hao

Wolfram²,

Cook³

2016

CEOR

View full text Add to dashboard Cite

show abstract

“…Ongoing work is needed to support the validity of the utility index. A companion article describes the application of the scoring algorithm to independent trial datasets in breast cancer, and provides further evidence to support its validity by comparison with clinical data [28]. We have also reported on a comparison of the value and sensitivity of utility scores generated by the index to those generated by the EQ‐5D in colorectal cancer [71].…”

Section: Discussionmentioning

confidence: 99%

“…The purpose of optimizing the algorithm is to reflect the differences in importance that patients with different types and stages of cancer, and treatments assign to various dimensions of HRQL [40,74]. The implications of optimizing the algorithm for different treatment contexts are addressed by application and discussion in a companion article [28].…”

Section: Discussionmentioning

confidence: 99%