Evidence map›Paper›PMID 19255876›Full record

ArticleQuality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation2009

The precision of health state valuation by members of the general public using the standard gamble.

Ken Stein, Matthew Dyer, Ruairidh Milne, Alison Round, Julie Ratcliffe, John Brazier

Abstract readValidation Study
PubMed Publisher
In one paragraph

Article in Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
3.0field-weighted citation impact, top 7% of its field
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

2 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Comparison of the quality of life between patients with non-small-cell lung cancer and healthy controls.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2011
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 4 institutions in 1 country.

Ken SteinPeninsula Technology Assessment Group, Peninsula Medical School, University of Exeter, Exeter, UK. ken.stein@pms.ac.uk
Matthew Dyer
Ruairidh Milne
Alison Round
Julie Ratcliffe
John Brazier
Peninsula College of Medicine and Dentistry · GBUniversity of Sheffield · GBUniversity of Exeter · GBUniversity of Southampton · GB

Funding

Medical Research Council MC_U145080960
6 · The paper itself

Abstract

backgroundPrecision is a recognised requirement of patient-reported outcome measures but no previous studies of the precision of methods for obtaining health state values from the general public, based on specific health state descriptions or vignettes, have been carried out. The methodological requirements of policy makers internationally is driving growth in the use of methods to obtain utilities from the general public to inform cost per quality-adjusted life-year (QALY) analyses of health technologies being considered for adoption by health systems.

methodsThe precision of five comparisons of the outcomes of treatments, based on health state descriptions, was assessed against the results of clinical trials which showed a statistically and clinically significant improvement using an internet panel of members of the UK general public. Health states were developed to depict the baseline and post-treatment states from these exemplar clinical trials. Preferences for health states were obtained using bottom-up titrated standard gamble over the internet, and differences between summary health state values corresponding to the treatment and comparator groups within each exemplar study were compared. Results are considered in the context of various estimates for the minimally important difference in utility values.

resultsParticipation among members of the internet panel in the five exemplars ranged from 27 to 59. In four of the five exemplars, the utility-based estimates of treatment benefit showed significant differences between groups and were greater than an assumed minimally important difference of 0.1. Mean utility differences between groups were: 0.23 (computerised cognitive behavioural therapy for depression, P < 0.001), 0.11 (hip resurfacing for hip osteoarthritis, P < 0.001), 0.0005 (cognitive behavioural therapy for insomnia, P = 0.98), 0.15 (pulmonary rehabilitation for COPD, P < 0.001) and 0.11 (infliximab for Crohn's disease, P < 0.001). The confidence intervals around the estimates of utility-based treatment effect in three of the five examples did not exclude the possibility of a difference smaller than a minimally important difference of 0.1. Recent empirical evidence suggests a lower minimally important difference (0.03) may be more appropriate, in which case our results provide further reassurance of preservation of precision in health state description and valuation.

conclusionsThe precision of estimates of treatment effects based on preference data obtained from disease-specific measurements in clinically significant studies of health technologies was acceptable using an internet-based panel of members of the general public and the standard gamble. Definition of the minimally important difference in utility estimates is required to adequately assess precision and should be the subject of further research.

Indexed as

Clinical Trials as TopicReproducibility of ResultsSickness Impact ProfileSurveys and QuestionnairesTreatment OutcomeDisability EvaluationEvidence-Based MedicineHumansInternetSeverity of Illness Index

Identifiers

PMID19255876
OpenAlexW2039228113

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.