Mapping ODI onto EQ-5D-5L in Chinese Low Back Pain Patients

Mapping can translate utility values from other health-related quality-of-life scales, giving researchers and policymakers more comprehensive information. The primary objective of the study is to develop mapping algorithms that convert scores from the Oswestry Disability Index (ODI) to the 5-level EuroQol-5 Dimension (EQ-5D-5L). Data for this analysis was sourced from 272 patients suffering from low back pain. The development of the mapping algorithms involved the application of three distinct regression methods across four different settings: ordinary least squares regression, beta regression, and multivariate ordered probit regression. To evaluate the internal validity of these algorithms, we adopted a ‘hold-out’ approach for predictive performance assessment. Furthermore, to discern the most effective model, three goodness-of-fit tests were employed: the mean absolute error (MAE), the root-mean-square error (RMSE), and the Spearman rank correlation coefficients between the predicted and observed utilities. The study successfully developed several models capable of accurately predicting health utilities in the specified context. The best performing models for ODI to EQ-5D-5L mapping were beta regressions. Mapping algorithms developed in this study enable the estimation of utility values from the ODI. The algorithms formulated in this study facilitate the estimation of utility values based on the ODI, providing a valuable empirical foundation for estimating health utilities in scenarios where EQ-5D data is unavailable. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement Yes ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Low back pain patients were recruited at the General Hospital of Shenyang Military Area Command. The Ethics Committee of the General Hospital of Shenyang Military Area Command granted ethics approval (Code of Ethics: K (2017)22). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All relevant data are within the manuscript and its Supporting Information files. The raw data that used in this study has been published on .