BACKGROUND: Multi attribute utility instruments (MAUIs) are preference-based measures that comprise a health state classification system (HSCS) and a scoring algorithm that assigns a utility value to each health state in the HSCS. When developing a MAUI from a health-related quality of life (HRQOL) questionnaire, first a HSCS must be derived. This typically involves selecting a subset of domains and items because HRQOL questionnaires typically have too many items to be amendable to the valuation task required to develop the scoring algorithm for a MAUI. Currently, exploratory factor analysis (EFA) followed by Rasch analysis is recommended for deriving a MAUI from a HRQOL measure. AIM: To determine whether confirmatory factor analysis ( @entity3795 ) is more appropriate and efficient than EFA to derive a HSCS from the European Organisation for the Research and Treatment of @entity5 's core HRQOL questionnaire, Quality of Life Questionnaire (QLQ-C30), given its well-established domain structure. METHODS: QLQ-C30 (Version 3) data were collected from 356 @entity1 receiving palliative radiotherapy for recurrent/ @entity5 (various primary sites). The dimensional structure of the QLQ-C30 was tested with EFA and @entity3795 , the latter informed by the established QLQ-C30 structure and views of both @entity1 and clinicians on which are the most relevant items. Dimensions determined by EFA or @entity3795 were then subjected to Rasch analysis. RESULTS: @entity3795 results generally supported the proposed QLQ-C30 structure (comparative fit index =0.99, Tucker-Lewis index =0.99, root mean square error of approximation =0.04). EFA revealed fewer factors and some items cross-loaded on multiple factors. Further assessment of dimensionality with Rasch analysis allowed better alignment of the EFA dimensions with those detected by @entity3795 . CONCLUSION: @entity3795 was more appropriate and efficient than EFA in producing clinically interpretable results for the HSCS for a proposed new @entity5 . Our findings suggest that @entity3795 should be recommended generally when deriving a preference-based measure from a HRQOL measure that has an established domain structure.

Deriving a preference-based utility measure for @entity5 @entity1 from the European Organisation for the Research and Treatment of XXXX 's Quality of Life Questionnaire C30: a confirmatory versus exploratory approach.

@entity5 :: ('MESH:D009369', 'Disease') :: ['metastatic cancer', 'cancer-specific MAUI', 'Cancer'] @entity1 :: ('9606', 'Species') :: ['patients'] @entity3795 :: ('31658', 'Species') :: ['CFA']
@entity5 :: (MESH:D009369,Disease) :: ['Cancer']
