Predicting SF-6D from the European Organization for Treatment and Research of Cancer Quality of Life Questionnaire Scores in Patients with Colorectal Cancer

Mar 1, 2013, 00:00 AM
Section Title : Preference-Based Assessments
Section Order : 16
First Page : 373


To develop a mapping model for estimating six-dimensional health state short form (SF-6D) utility scores from the European Organization for Research and Treatment of Cancer Quality of Life Questionnaires (QLQ-C30 and QLQ-CR29) scores in patients with colorectal cancer (CRC), with and without adjustment for clinical and demographic characteristics.


Ordinary least squares regression models were applied to a cross-sectional data set of 216 patients with CRC collected from a regional hospital in Hong Kong. Item responses or scale scores of cancer-specific (QLQ-C30) and colorectal-specific health-related quality-of-life (QLQ-CR38/CR29) data and selected demographic and clinical characteristics of patients were used to predict the SF-6D scores. Model goodness of fit was examined by using exploratory power (R and adjusted R ), Akaike information criterion, and Bayesian information criterion, and predictive performance was evaluated by using root mean square error, mean absolute error, and Spearman’s correlation coefficients between predicted and observed SF-6D scores. Models were validated by using an independent data set of 56 patients with CRC.


Both scale and item response models explained more than 67% of the variation in SF-6D scores. The best-performing model based on goodness of fit (R = 75.02%), predictive ability in the estimation (root mean square error = 0.080, mean absolute error = 0.065), and validation data set prediction (root mean square error = 0.103, mean absolute error = 0.081) included variables of main and interaction effects of the QLQ-C30 supplemented by QLQ-CR29 subset scale responses and a demographic (sex) variable.


SF-6D scores can be predicted from QLQ-C30 and QLQ-CR38/CR29 scores with satisfactory precision in patients with CRC. The mapping model can be applied to QLQ-C30 and QLQ-CR38/CR29 data sets to produce utility scores for the appraisal of clinical interventions targeting patients with CRC using economic evaluation.
HEOR Topics :
  • Gastrointestinal Disorders
  • Health State Utilities
  • Instrument Development, Validation, & Translation
  • Oncology
  • Patient-Centered Research
  • Specific Diseases & Conditions
Tags :
  • colorectal cancer
  • mapping
  • preference-based scores
  • quality of life
  • SF-6D
Regions :
  • Asia Pacific (including Oceania)