title: Testing mapping algorithms of the cancer-specific EORTC QLQ-C30 onto EQ-5D in malignant mesothelioma.
abstract: BACKGROUND
  In order to estimate utilities for cancer studies where the EQ-5D was not used, the EORTC QLQ-C30 can be used to estimate EQ-5D using existing mapping algorithms. Several mapping algorithms exist for this transformation, however, algorithms tend to lose accuracy in patients in poor health states. The aim of this study was to test all existing mapping algorithms of QLQ-C30 onto EQ-5D, in a dataset of patients with malignant pleural mesothelioma, an invariably fatal malignancy where no previous mapping estimation has been published.
  
  
  METHODS
  Health related quality of life (HRQoL) data where both the EQ-5D and QLQ-C30 were used simultaneously was obtained from the UK-based prospective observational SWAMP (South West Area Mesothelioma and Pemetrexed) trial. In the original trial 73 patients with pleural mesothelioma were offered palliative chemotherapy and their HRQoL was assessed across five time points. This data was used to test the nine available mapping algorithms found in the literature, comparing predicted against observed EQ-5D values. The ability of algorithms to predict the mean, minimise error and detect clinically significant differences was assessed.
  
  
  RESULTS
  The dataset had a total of 250 observations across 5 timepoints. The linear regression mapping algorithms tested generally performed poorly, over-estimating the predicted compared to observed EQ-5D values, especially when observed EQ-5D was below 0.5. The best performing algorithm used a response mapping method and predicted the mean EQ-5D with accuracy with an average root mean squared error of 0.17 (Standard Deviation; 0.22). This algorithm reliably discriminated between clinically distinct subgroups seen in the primary dataset.
  
  
  CONCLUSIONS
  This study tested mapping algorithms in a population with poor health states, where they have been previously shown to perform poorly. Further research into EQ-5D estimation should be directed at response mapping methods given its superior performance in this study.
authors.affiliation: Academic Respiratory Unit, School of Clinical Sciences, University of Bristol, Bristol, UK. arnold.dta@gmail.com.
authors.forename: David T
authors.initials: DT
authors.lastname: Arnold
authors.affiliation: School of Health and Related Research (ScHARR), University of Sheffield, Sheffield, UK. d.rowen@sheffield.ac.uk.
authors.forename: Donna
authors.initials: D
authors.lastname: Rowen
authors.affiliation: Institute for Medical Technology Assessment, Erasmus University of Rotterdam, Rotterdam, Netherlands. versteegh@imta.eur.nl.
authors.forename: Matthijs M
authors.initials: MM
authors.lastname: Versteegh
authors.affiliation: Academic Respiratory Unit, School of Clinical Sciences, University of Bristol, Bristol, UK. anna.morley@nbt.nhs.uk.
authors.forename: Anna
authors.initials: A
authors.lastname: Morley
authors.affiliation: Academic Respiratory Unit, School of Clinical Sciences, University of Bristol, Bristol, UK. clare.hooper@worcsacute.nhs.uk.
authors.forename: Clare E
authors.initials: CE
authors.lastname: Hooper
authors.affiliation: Academic Respiratory Unit, School of Clinical Sciences, University of Bristol, Bristol, UK. Nick.maskell@bristol.ac.uk.
authors.forename: Nicholas A
authors.initials: NA
authors.lastname: Maskell
mesh_terms: D000368:Aged; D000465:Algorithms; D005260:Female; D006305:Health Status Indicators; D006801:Humans; D016014:Linear Models; D008175:Lung Neoplasms / Q000175:diagnosis / Q000523:psychology*; D008297:Male; D008654:Mesothelioma / Q000175:diagnosis / Q000523:psychology*; D000086002:Mesothelioma, Malignant; D008875:Middle Aged; D011446:Prospective Studies; D011788:Quality of Life / Q000523:psychology*; D012044:Regression Analysis; D015203:Reproducibility of Results; D011795:Surveys and Questionnaires / Q000592:standards*