Evidence map›Paper›PMID 31938965›Full record

ArticleQuality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation2020

Assessing health-related quality of life in cancer survivors: factors impacting on EORTC QLU-C10D-derived utility values.

Thomas van Gelder, Brendan Mulhern, Dounya Schoormans, Olga Husson, Richard De Abreu Lourenço

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Article in Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
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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

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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

5 citing papers in PubMed.

  1. Article
  2. The EORTC QLU-C10D is a valid cancer-specific preference-based measure for cost-utility and health technology assessment in the Netherlands.The European journal of health economics : HEPAC : health economics in prevention and care · 2024
    Article
  3. Article
  4. Article
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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Thomas van GelderUtrecht University, Utrecht, The Netherlands.
Brendan MulhernCentre for Health Economics Research and Evaluation, University of Technology Sydney, Sydney, Australia.
Dounya SchoormansDepartment of Medical and Clinical Psychology, Center of Research on Psychology in Somatic Diseases (CoRPS), Tilburg University, Tilburg, The Netherlands.
Olga HussonDepartment of Psychosocial Research and Epidemiology, The Netherlands Cancer Institute, Amsterdam, The Netherlands.
Richard De Abreu LourençoCentre for Health Economics Research and Evaluation, University of Technology Sydney, Sydney, Australia. Richard.deabreulourenco@chere.uts.edu.au.ORCID http://orcid.org/0000-0002-5978-8774

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo investigate the factors influencing EORTC QLQ-C30-derived EORTC QLU-C10D utility values across five cancer types (non-Hodgkin lymphoma, multiple myeloma, colorectal, thyroid, and prostate cancer) and a general population sample.

methodsData from the Dutch population-based patient-reported outcomes following initial treatment and long-term evaluation of survivorship (PROFILES) registry collected between 2009 and 2012 were used. EORTC QLQ-C30 data were used to estimate utility values by applying the EORTC QLU-C10D instrument using Australian utility weights. Regression analyses were conducted, within and across cancer type, to examine the factors influencing utility values, including patient- and cancer-specific factors, as well as the EORTC QLQ-C30 scale/item scores.

resultsThe mean utility value for the total cancer sample was 0.791 (SD 0.201), significantly lower than that from the general population (0.865, SD 0.165). Multiple myeloma patients had the lowest utility value at 0.663 (SD 0.244). Physical functioning, pain and nausea and vomiting were the health-related quality of life (HRQoL) domains with the greatest impact on utility values; cognitive functioning and dyspnea had the lowest impact. Of the demographic and clinical factors, unemployment for reasons other than retirement, age older than 75 years, number of comorbidities, and experience of symptoms all had a statistically significant negative impact on utility values.

conclusionsThis study is one of the first to apply the EORTC QLU-C10D to a heterogeneous group of cancer patients. Results can be used to more efficiently target care towards factors influencing HRQoL. Furthermore, it enhances our understanding of how the EORTC QLU-C10D performs across cancer types, supporting its use in cost-utility analyses.

Indexed as

Patient Reported Outcome MeasuresAgedCancer SurvivorsHumansMaleMiddle AgedQuality of LifeSurveys and QuestionnairesCancerEORTC QLU-C10DHealth-related quality of lifePatient-reported outcomesUtility values

Identifiers

PMID31938965

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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.