Literature DB >> 27676291

Mapping EORTC-QLQ-C30 to EQ-5D-3L in patients with colorectal cancer.

Emily-Ruth Marriott1, Guy van Hazel2, Peter Gibbs3, Anthony J Hatswell1,4.   

Abstract

AIMS: The primary aim of this study was to perform a mapping of the EORTC-QLQ-C30 scores to EQ-5D-3L for the SIRFLOX study; a large dataset of patients with previously untreated liver-only or liver-dominant metastatic colorectal cancer (mCRC). A secondary aim was to compare the predictive validity of existing mappings from EORTC-QLQ-C30 to EQ-5D-3L conducted in other cancers. METHODS AND MATERIALS: Questionnaires (completed within 529 patients) were used in a linear mixed regression to model EQ-5D-3L utility values (scored using the UK tariff) as a function of the five function scores, nine symptom scores, and the global score from the EORTC-QLQ-C30 questionnaire. A Tobit regression was also performed. The mean EQ-5D-3L values for the SIRFLOX trial were calculated and compared with predicted EQ-5D-3L values derived using published mapping algorithms.
RESULTS: The linear mixed regression model provided a satisfactory mapping between the EORTC-QLQ-C30 and the EQ-5D-3L, whilst the Tobit model did not perform as well. When utilities from the SIRFLOX data were calculated with previously published mapping studies, three out of five studies performed well (< 10% mean difference). LIMITATIONS: The main limitation of the study was the lack of meaningful observations post-progression (67 paired observations). For this reason, this study was unable to test whether the mapping holds by disease stage. Additionally, although the study adds to the literature of mappings to the EQ-5D-3L, it is not known how results would differ using the EQ-5D-5L.
CONCLUSION: This study is the first of its kind in liver-only or liver-dominant mCRC, and mCRC in general. The mapping constructed showed a good fit to the data and provides practitioners with an additional mapping between EORTC-QLQ-C30 to EQ-5D-3L using a large dataset (529 patients, 707 paired observations). The study also confirmed the generalizability of mappings published by Proskorovsky, Kontodimopoulos, and Longworth to liver-only or liver-dominant mCRC.

Entities:  

Keywords:  Health-related quality-of-life; cost-utility; health state utility; patient-reported outcomes; quality-of-life

Mesh:

Year:  2016        PMID: 27676291     DOI: 10.1080/13696998.2016.1241788

Source DB:  PubMed          Journal:  J Med Econ        ISSN: 1369-6998            Impact factor:   2.448


  9 in total

1.  Testing alternative regression models to predict utilities: mapping the QLQ-C30 onto the EQ-5D-5L and the SF-6D.

Authors:  Admassu N Lamu; Jan Abel Olsen
Journal:  Qual Life Res       Date:  2018-09-01       Impact factor: 4.147

2.  Mapping EORTC-QLQ-C30 and QLQ-CR29 onto EQ-5D-5L in Colorectal Cancer Patients.

Authors:  Hosein Ameri; Mahmood Yousefi; Mehdi Yaseri; Azin Nahvijou; Mohammad Arab; Ali Akbari Sari
Journal:  J Gastrointest Cancer       Date:  2020-03

3.  Statistical tests for latent class in censored data due to detection limit.

Authors:  Hua He; Wan Tang; Tanika Kelly; Shengxu Li; Jiang He
Journal:  Stat Methods Med Res       Date:  2019-11-18       Impact factor: 3.021

4.  Effect of Collaborative Telerehabilitation on Functional Impairment and Pain Among Patients With Advanced-Stage Cancer: A Randomized Clinical Trial.

Authors:  Andrea L Cheville; Timothy Moynihan; Jeph Herrin; Charles Loprinzi; Kurt Kroenke
Journal:  JAMA Oncol       Date:  2019-05-01       Impact factor: 31.777

5.  Quality of Life in Palliative Care.

Authors:  Mellar P Davis; David Hui
Journal:  Expert Rev Qual Life Cancer Care       Date:  2017-11-08

Review 6.  Review and critical appraisal of studies mapping from quality of life or clinical measures to EQ-5D: an online database and application of the MAPS statement.

Authors:  Helen Dakin; Lucy Abel; Richéal Burns; Yaling Yang
Journal:  Health Qual Life Outcomes       Date:  2018-02-12       Impact factor: 3.186

7.  Evidence-based sizing of non-inferiority trials using decision models.

Authors:  Iris Lansdorp-Vogelaar; Reshma Jagsi; Jinani Jayasekera; Natasha K Stout; Sandra A Mitchell; Eric J Feuer
Journal:  BMC Med Res Methodol       Date:  2019-01-07       Impact factor: 4.615

8.  Cost-effectiveness of the Collaborative Care to Preserve Performance in Cancer (COPE) trial tele-rehabilitation interventions for patients with advanced cancers.

Authors:  Colleen F Longacre; John A Nyman; Sue L Visscher; Bijan J Borah; Andrea L Cheville
Journal:  Cancer Med       Date:  2020-02-23       Impact factor: 4.452

9.  Mapping analysis to predict EQ-5D-5 L utility values based on the Oxford Hip Score (OHS) and Oxford Knee Score (OKS) questionnaires in the Spanish population suffering from lower limb osteoarthritis.

Authors:  Jesús Martín-Fernández; Mariel Morey-Montalvo; Nuria Tomás-García; Elena Martín-Ramos; Juan Carlos Muñoz-García; Elena Polentinos-Castro; Gemma Rodríguez-Martínez; Juan Carlos Arenaza; Lidia García-Pérez; Laura Magdalena-Armas; Amaia Bilbao
Journal:  Health Qual Life Outcomes       Date:  2020-06-15       Impact factor: 3.186

  9 in total

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