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Purpose: To assess the feasibility of using a discrete choice experiment (DCE) to value health states within the QLU-C10D, a utility instrument derived from the QLQ-C30, and to assess clarity, difficulty, and respondent preference between two presentation formats., Methods: We ran a DCE valuation task in an online panel (N = 430). Respondents answered 16 choice pairs; in half of these, differences between dimensions were highlighted, and in the remainder, common dimensions were described in text and differing attributes were tabulated. To simplify the cognitive task, only four of the QLU-C10D's ten dimensions differed per choice set. We assessed difficulty and clarity of the valuation task with Likert-type scales, and respondents were asked which format they preferred. We analysed the DCE data by format with a conditional logit model and used Chi-squared tests to compare other responses by format. Semi-structured telephone interviews (N = 8) explored respondents' cognitive approaches to the valuation task., Results: Four hundred and forty-nine individuals were recruited, 430 completed at least one choice set, and 422/449 (94 %) completed all 16 choice sets. Interviews revealed that respondents found ten domains difficult but manageable, many adopting simplifying heuristics. Results for clarity and difficulty were identical between formats, but the "highlight" format was preferred by 68 % of respondents. Conditional logit parameter estimates were monotonic within domains, suggesting respondents were able to complete the DCE sensibly, yielding valid results., Conclusion: A DCE valuation task in which only four of the QLU-C10D's ten dimensions differed in any choice set is feasible for deriving utility weights for the QLU-C10D.

Purpose: Health-related quality of life (HRQoL) and unmet needs (needs) questionnaires offer alternative perspectives for assessing cancer patients' concerns. We examined whether the conceptual differences underlying these alternative approaches yield corresponding empirical differences., Methods: Eight-hundred and seventy-four women with ovarian cancer completed the Functional Assessment of Cancer Therapy scale (FACT-G; HRQoL) and the Supportive Care Needs Survey (SCNS-SF34; needs) every 3 months for 2 years. Correlational analysis, exploratory and confirmatory factor analysis (EFA/CFA), and Rasch analysis tested the relationship between patients' responses to similar domains and similar items across the two questionnaires., Results: Strong correlations were found between items with virtually identical wording (0.67-0.75), while moderate to strong correlations (0.55-0.65) were found for those with very similar wording. EFA identified two common domains across the two questionnaires: physical and psychological. For each common domain, CFA indicated models involving a single construct with systematic variation within each questionnaire fit best. Rasch analysis including very similar items within the physical and psychological domains (separately) demonstrated strong evidence of unidimensionality., Conclusions: The high degree of similarity between patient responses to items addressing the same or very similar concerns suggests either that HRQoL and needs approaches do not reflect different constructs or that patients may not be able to differentiate between the severity of a concern and the level of need associated with that concern, especially when these are assessed in quick succession.

Background: The aim was to carry out phase 4 international field‐testing of the European Organisation for Research and Treatment of Cancer (EORTC) breast reconstruction (BRECON) module. The primary objective was finalization of its scale structure. Secondary objectives were evaluation of its reliability, validity, responsiveness, acceptability and interpretability in patients with breast cancer undergoing mastectomy and reconstruction. Methods: The EORTC module development guidelines were followed. Patients were recruited from 28 centres in seven countries. A prospective cohort completed the QLQ‐BRECON15 before mastectomy and the QLQ‐BRECON24 at 4–8 months after reconstruction. The cross‐sectional cohort completed the QLQ‐BRECON24 at 1–5 years after reconstruction, and repeated this 2–8 weeks later (test–retest reliability). All participants completed debriefing questionnaires. Results: A total of 438 patients were recruited, 234 in the prospective cohort and 204 in the cross‐sectional cohort. A total of 414 reconstructions were immediate, with a comparable number of implants (176) and donor‐site flaps (166). Control groups comprised patients who underwent two‐stage implant procedures (72, 75 per cent) or delayed reconstruction (24, 25 per cent). Psychometric scale validity was supported by moderate to high item‐own scale and item‐total correlations (over 0·5). Questionnaire validity was confirmed by good scale‐to‐sample targeting, and computable scale scores exceeding 50 per cent, except nipple cosmesis (over 40 per cent). In known‐group comparisons, QLQ‐BRECON24 scales and items differentiated between patient groups defined by clinical criteria, such as type and timing of reconstruction, postmastectomy radiotherapy and surgical complications, with moderate effect sizes. Prospectively, sexuality and surgical side‐effects scales showed significant responsiveness over time (P < 0·001). Scale reliability was supported by high Cronbach's α coefficients (over 0·7) and test–retest (intraclass correlation more than 0·8). One item (finding a well fitting bra) was excluded based on high floor/ceiling effects, poor test–retest and weak correlations in factor analysis (below 0·3), thus generating the QLQ‐BRECON23 questionnaire. Conclusion: The QLQ‐BRECON23 is an internationally validated tool to be used alongside the EORTC QLQ‐C30 (cancer) and QLQ‐BR23 (breast cancer) questionnaires for evaluating quality of life and satisfaction after breast reconstruction. [ABSTRACT FROM AUTHOR]

Purpose: To derive a health state classification system (HSCS) from the cancer-specific quality of life questionnaire, the EORTC QLQ-C30, as the basis for a multi-attribute 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 selection 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 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 generalisability 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.Conclusions: The HSCS created from QLQ-C30 items is known as the EORTC Quality of Life Utility Measure-Core 10 dimensions (QLU-C10D). The next phase of the QLU-C10D's development involves valuation studies, currently planned or being conducted across the globe. [ABSTRACT FROM AUTHOR]

Background: This review aims to assist cancer clinical researchers in choosing between the two most widely used measures of cancer-specific health-related quality of life: the European Organisation for the Research and Treatment of Cancer Quality of Life Questionnaire Core 30 and Functional Assessment of Cancer Therapy—General (FACT-G).Materials and methods: Information on QLQ-C30 and FACT-G content, scale structure, accessibility and availability was collated from websites and manuals. A systematic review was undertaken to identify all articles reporting on psychometric properties and information to assist interpretability. Evidence for reliability, validity and responsiveness was rated using a standardised checklist. Instrument properties were compared and contrasted to inform recommendations.Results: Psychometric evidence does not recommend one questionnaire over the other in general. However, there are important differences between the scale structure, social domains and tone that inform choice for any particular study.Conclusions: Where research objectives are concerned with the impact of a specific tumour type, treatment or symptom, choice should be guided by the availability, content, scale structure and psychometric properties of relevant European Organisation for the Research and Treatment of Cancer versus Functional Assessment of Chronic Illness Therapy modules. Because the FACT-G combines symptoms and concerns within each scale, individual items should always be reviewed within the context of specific research objectives. Where these issues are indecisive, researchers are encouraged to use an algorithm at the end of the current article. [ABSTRACT FROM AUTHOR]