A Patient-Based Utility Measure of Health for Clinical Trials of Cancer Therapy Based on the European Organization for the Research and Treatment of Cancer Quality of Life Questionnaire

Pickard, A. Simon; Shaw, James W.; Lin, Hsueh-Chun; Trask, Peter C.; Aaronson, Neil K.; Lee, Todd A.; Cella, David

doi:10.1111/j.1524-4733.2009.00545.x

Cited by 22 publications

(12 citation statements)

References 42 publications

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“…Four of these dimensions are identical (Emotional Functioning, Fatigue, Nausea, Bowel Problems), one contains the same items but different levels (Physical Functioning) and three contain different items (Role Functioning, Social Functioning, Pain). Pickard et al used similar psychometric item selection methods to derive multi-attribute models in their mapping study [19], obtaining results that had some ' T se differences in results are likely due to different patient populations, and the item selection process itself, which requires judgment to reach a decision across a range of criteria. Given these differences, we recommend the QLU-C10D be used, particularly as it based on such a broad spectrum of patients and has been endorsed by the EORTC QOL Group.…”

Section: Discussionmentioning

confidence: 99%

QLU-C10D: a health state classification system for a multi-attribute utility measure based on the EORTC QLQ-C30

et al. 2016

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Abstract:Purpose: To derive a health state classification system (HSCS) from the cancerspecific quality of life questionnaire, the EORTC QLQ-C30, as the basis for a multiattribute utility instrument.Methods: The conceptual model for the HSCS was based on the established domain structure of the QLQ-C30. Several criteria were considered to select a subset of dimensions and items for the HSCS. Expert opinion and patient input informed a priori Powered by Edit orial Manager® and ProduXion Manager® from Aries Syst em s Corporat ionselection of key dimensions. Psychometric criteria were assessed via secondary analysis of a pooled dataset comprising HRQOL and clinical data from 2616 patients from eight countries and a range of primary cancer sites, disease stages, and treatments. We used confirmatory factor analysis (CFA) to assess the conceptual model's robustness and generalisability. We assessed item floor effects (>75% observations at lowest score), disordered item response thresholds, coverage of the latent variable and differential item function (DIF) using Rasch analysis. We calculated effect sizes for known group comparisons based on disease stage and responsiveness to change. Seventy-nine cancer patients assessed the relative importance of items within dimensions.Results: CFA supported the conceptual model and its generalizability across primary cancer sites. After considering all criteria, 12 items were selected representing 10 dimensions: physical functioning (mobility), role functioning, social functioning, emotional functioning, pain, fatigue, sleep, appetite, nausea, bowel problems.

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Section: Discussionmentioning

confidence: 99%

QLU-C10D: a health state classification system for a multi-attribute utility measure based on the EORTC QLQ-C30

et al. 2016

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“…Mapping functions have been previously developed by using data from patients with general cancer [31,32], esophageal cancer [33], gastric cancer [15], and prostate cancer [20]. This study is the first attempt, to our knowledge, to develop a mapping function to estimate SF-6D preference-based values from condition-specific measures for patients with CRN.…”

Section: Discussionmentioning

confidence: 95%

Mapping the Functional Assessment of Cancer Therapy-General or -Colorectal to SF-6D in Chinese Patients with Colorectal Neoplasm

et al. 2012

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Models mapping FACT-G and FACT-C onto SF-6D reached an acceptable degree of precision. Mapping from the condition-specific measure (FACT-C) had better performance than did mapping from the general cancer measure (FACT-G). These mapping functions can be applied to FACT-G or FACT-C data sets to estimate SF-6D utility values for economic evaluation of medical interventions for patients with colorectal neoplasm. Further research assessing model performance in independent data sets and non-Chinese populations are encouraged.

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“…Following a more psychometric tradition, Pickard and Shaw [25] used an item reduction approach on all the QLQ-C30 items with a rating scale method before applying median regression on the remaining items on a sample of cancer patients drawn from five academic medical centres in the US. Their item-reduction process resulted in only eight items being retained.…”

Section: Discussionmentioning

confidence: 99%

Mapping the QLQ-C30 quality of life cancer questionnaire to EQ-5D patient preferences

Crott

Briggs

2010

Eur J Health Econ

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A Patient-Based Utility Measure of Health for Clinical Trials of Cancer Therapy Based on the European Organization for the Research and Treatment of Cancer Quality of Life Questionnaire

Cited by 22 publications

References 42 publications

QLU-C10D: a health state classification system for a multi-attribute utility measure based on the EORTC QLQ-C30

QLU-C10D: a health state classification system for a multi-attribute utility measure based on the EORTC QLQ-C30

Mapping the Functional Assessment of Cancer Therapy-General or -Colorectal to SF-6D in Chinese Patients with Colorectal Neoplasm

Mapping the QLQ-C30 quality of life cancer questionnaire to EQ-5D patient preferences

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