Predicting EQ-5D-5L Utility Scores from the Oswestry Disability Index and Roland-Morris Disability Questionnaire for Low Back Pain
Bibliographic record
Abstract
Thomas G Poder,1– 3 Nathalie Carrier3 1School of Public Health, Department of Management, Evaluation and Health Policy, University of Montreal, Montreal, QC, Canada; 2Centre de recherche de l’Institut universitaire en santé mentale de Montréal, CIUSSS de l’Est-de-l’Île-de-Montréal, Montreal, QC, Canada; 3Centre de recherche du CHUS, CIUSSS de l’Estrie-CHUS, Sherbrooke, QC, CanadaCorrespondence: Thomas G PoderSchool of Public Health, Department of Management, Evaluation and Health Policy, University of Montreal, Montreal, QC, CanadaEmail thomas.poder@umontreal.caBackground: Cost utility analysis is important for measuring the impact of chronic disease and helps clinicians and policymakers in patient management and policy decisions, but generic preference-based measures are not always considered in clinical studies.Objective: To evaluate if health-related quality-of-life (HRQoL)-specific questionnaires used in chronic low back pain (CLBP) can predict EQ-5D-5L utility scores.Methods: The data come from an online survey on low back pain conducted between October 2018 and January 2019. Health utility scores for EuroQol Five Dimensions Five Levels (EQ-5D-5L) were calculated with the recommended model of Xie et al. The EQ-5D-5L health states ranged from − 0.148 for the worst (55555) to 0.949 for the best (11111). Univariate and multivariate linear regression were performed to predict EQ-5D-5L with Oswestry Disability Index (ODI), Roland-Morris Disability Questionnaire (RMDQ) and clinical variables.Results: Analyses were performed in 408 subjects who completed the questionnaires EQ-5D-5L, ODI or RMDQ. Median (range) of EQ-5D-5L was 0.622 (− 0.072 to 0.905). There was high correlation between EQ-5D-5L and ODI (r=− 0.78, p< 0.001), while it was moderate with RMDQ (r=− 0.62, p< 0.001). The multivariate model to predict EQ-5D-5L with ODI explained 67.6% of variability, and the correlation between actual and predicted EQ-5D-5L was 0.82. Principal predictors were ODI, duration of LBP, invalidity, health satisfaction (0– 10 cm), life satisfaction (0– 10 cm), and intensity of pain today (0– 10 cm).Conclusion: Data from this study demonstrated that individual correlation between ODI and EQ-5D-5L was high, but moderate with RMDQ. Correlations between actual and predicted EQ-5D-5L from multivariate models were higher and very high. Considering these results, the multivariate model can be used in similar studies for patient with CLBP to estimate the utility scores from the ODI when the EQ-5D-5L was not measured.Keywords: low back pain, EQ-5D-5L, utility score, QALY, health-related quality of life
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".