Evidence map›Paper›PMID 26342928›Full record

ArticleQuality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation2016

Using a discrete choice experiment to value the QLU-C10D: feasibility and sensitivity to presentation format.

R Norman, R Viney, N K Aaronson, J E Brazier, D Cella, D S J Costa, P M Fayers, G Kemmler, S Peacock, A S Pickard and 5 more

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In one paragraph

Article in Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 52 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
52citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

52 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Discrete choice experiments to generate utility values for multi-attribute utility instruments: a systematic review of methods.The European journal of health economics : HEPAC : health economics in prevention and care · 2020
    Pooled it
  3. Cancer-specific utility: clinical validation of the EORTC QLU-C10D in patients with glioblastoma.The European journal of health economics : HEPAC : health economics in prevention and care · 2025
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  10. United Kingdom value set for the functional assessment of cancer therapy eight dimension (FACT-8D) preference-based quality of life instrument.The European journal of health economics : HEPAC : health economics in prevention and care · 2026
    Article
  11. Cancer-specific or generic preference-based measures in oncology? A validity comparison across six commonly diagnosed cancers.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2026
    Article
  12. Valuing health and wellbeing using discrete choice experiment: exploring feasibility, design effect and international preference similarity.The European journal of health economics : HEPAC : health economics in prevention and care · 2026
    Article
  13. Article
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  16. Developing a utility value set for the Gambling Quality of Life Scale-Brief (GQoLS-Brief) using a discrete choice experiment.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2025
    Article
  17. Norwegian and Swedish value sets for the EORTC QLU-C10D utility instrument.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2025
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  18. Article
  19. Chinese utility weights for the EORTC cancer-specific utility instrument QLU-C10D.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2024
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  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

15 authors.

R NormanSchool of Public Health, Curtin University, Perth, Australia. Richard.norman@curtin.edu.au.
R VineyCentre for Health Economics Research and Evaluation (CHERE), University of Technology Sydney (UTS), Sydney, Australia.
N K AaronsonThe Netherlands Cancer Institute, Amsterdam, The Netherlands.
J E BrazierSchool of Health and Related Research, University of Sheffield, Sheffield, South Yorkshire, UK.
D CellaDepartment of Medical Social Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
D S J CostaPsycho-Oncology Cooperative Research Group (PoCoG), University of Sydney, Sydney, Australia.
P M FayersInstitute of Applied Health Sciences, University of Aberdeen, Aberdeen, UK.
G KemmlerInnsbruck Medical University, Innsbruck, Austria.
S PeacockFaculty of Health Sciences, Simon Fraser University, Vancouver, Canada.
A S PickardDepartment of Pharmacy Systems, Outcomes and Policy, College of Pharmacy, University of Illinois at Chicago, Chicago, IL, USA.
D RowenSchool of Health and Related Research, University of Sheffield, Sheffield, South Yorkshire, UK.
D J StreetSchool of Mathematical and Physical Sciences, University of Technology Sydney, Sydney, Australia.
G VelikovaLeeds Institute of Cancer and Pathology, University of Leeds, Leeds, UK.
T A YoungSchool of Health and Related Research, University of Sheffield, Sheffield, South Yorkshire, UK.
M T KingPsycho-Oncology Cooperative Research Group (PoCoG), University of Sydney, Sydney, Australia.

Funding

Medical Research Council MR/L01629X/1
6 · The paper itself

Abstract

purposeTo 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.

methodsWe 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.

resultsFour 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.

conclusionA 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.

Indexed as

Health StatusSurveys and QuestionnairesChoice BehaviorFemaleHumansLogistic ModelsMaleNeoplasmsPsychometricsQuality of LifeTelephoneCancerDiscrete choice experimentQLQ-C30Quality of lifeUtility

Identifiers

PMID26342928

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.