Evidence map›Paper›PMID 29843726›Full record

ArticleHealth and quality of life outcomes2018

Predicting health-related quality of life (EQ-5D-5 L) and capability wellbeing (ICECAP-A) in the context of opiate dependence using routine clinical outcome measures: CORE-OM, LDQ and TOP.

Jasmine Peak, Ilias Goranitis, Ed Day, Alex Copello, Nick Freemantle, Emma Frew

Abstract readValidation Study
In one paragraph

Article in Health and quality of life outcomes, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–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

10 citing papers in PubMed.

  1. Quality of life measures in treatment for active substance misuse: a scoping review.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2025
    Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Measurement properties of the ICECAP-A capability well-being instrument among dermatological patients.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2022
    Article
  7. Article
  8. Article
  9. Capability instruments in economic evaluations of health-related interventions: a comparative review of the literature.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2020
    Review
  10. Observational
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.

Jasmine PeakHealth Economics Unit, Institute of Applied Health Research, Public Health Building, University of Birmingham, B15 2TT, Birmingham, UK.
Ilias GoranitisMelbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia.
Ed DayResearch and Innovation Department, Birmingham & Solihull Mental Health NHS Foundation Trust, Birmingham, UK.
Alex CopelloResearch and Innovation Department, Birmingham & Solihull Mental Health NHS Foundation Trust, Birmingham, UK.
Nick FreemantleDepartment of Primary Care and Population Health, University College London, London, UK.
Emma FrewHealth Economics Unit, Institute of Applied Health Research, Public Health Building, University of Birmingham, B15 2TT, Birmingham, UK. E.Frew@bham.ac.uk.ORCID http://orcid.org/0000-0002-5462-1158

Funding

Department of Health PB-PG-0610-22392Research for Patient Benefit Programme Grant Reference Number PB-PG-0610-22392
6 · The paper itself

Abstract

backgroundEconomic evaluation normally requires information to be collected on outcome improvement using utility values. This is often not collected during the treatment of substance use disorders making cost-effectiveness evaluations of therapy difficult. One potential solution is the use of mapping to generate utility values from clinical measures. This study develops and evaluates mapping algorithms that could be used to predict the EuroQol-5D (EQ-5D-5 L) and the ICEpop CAPability measure for Adults (ICECAP-A) from the three commonly used clinical measures; the CORE-OM, the LDQ and the TOP measures.

methodsModels were estimated using pilot trial data of heroin users in opiate substitution treatment. In the trial the EQ-5D-5 L, ICECAP-A, CORE-OM, LDQ and TOP were administered at baseline, three and twelve month time intervals. Mapping was conducted using estimation and validation datasets. The normal estimation dataset, which comprised of baseline sample data, used ordinary least squares (OLS) and tobit regression methods. Data from the baseline and three month time periods were combined to create a pooled estimation dataset. Cluster and mixed regression methods were used to map from this dataset. Predictive accuracy of the models was assessed using the root mean square error (RMSE) and the mean absolute error (MAE). Algorithms were validated using sample data from the follow-up time periods.

resultsMapping algorithms can be used to predict the ICECAP-A and the EQ-5D-5 L in the context of opiate dependence. Although both measures can be predicted, the ICECAP-A was better predicted by the clinical measures. There were no advantages of pooling the data. There were 6 chosen mapping algorithms, which had MAE scores ranging from 0.100 to 0.138 and RMSE scores ranging from 0.134 to 0.178.

conclusionIt is possible to predict the scores of the ICECAP-A and the EQ-5D-5 L with the use of mapping. In the context of opiate dependence, these algorithms provide the possibility of generating utility values from clinical measures and thus enabling economic evaluation of alternative therapy options.

trial registrationISRCTN22608399 . Date of registration: 27/04/2012. Date of first randomisation: 14/08/2012.

Indexed as

AlgorithmsQuality of LifeAdultAgedCost-Benefit AnalysisFemaleHumansMaleOpioid-Related DisordersOutcome Assessment, Health CarePredictive Value of TestsSurveys and QuestionnairesAddictionCondition-specific measuresEconomic evaluationEQ-5DICECAPMappingMental healthPreference-based measures

Identifiers

PMID29843726
PMCPMC5975467

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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.