Med Decis Making - Mapping a patient-reported functional outcome measure to a utility measure for comparative effectiveness and economic evaluations in older adults with low back pain.

Tópicos

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Resumo

CKGROUND: Linking patient-reported back pain outcomes with health utility measures is valuable for informing economic evaluations.METHODS: We used the Back pain Outcomes using Longitudinal Data (BOLD) registry to assess back pain and quality-of-life measures. The BOLD registry includes participants =65 years from 3 health systems. We used multiple baseline outcome measures: Roland-Morris Disability Questionnaire (RMDQ), Euroqol-5D (EQ-5D), and back and leg pain numerical rating scales (NRS). To develop and validate a model, we used a standard split-sample method and a novel multisite validation approach. We applied linear regression to map RMDQ to EQ-5D, adjusting for age, sex, pain numerical rating scores, and nonlinear transformations of outcome measures. We computed R (2), root mean squared error, and mean absolute error (MAE) for purposes of model selection. The final model included EQ-5D as the dependent variable with independent variables of age, RMDQ, and back NRS. We used this model to predict EQ-5D scores in validation samples.RESULTS: In total, 5224 participants had both baseline RMDQ and EQ-5D. Mean age was 74 years (65% female). Negative correlations (-0.72) were observed at baseline for RMDQ and EQ-5D. The selected model from all developmental samples had R (2) >0.41 and MAE < 0.119. Validation analyses indicated no differences in estimated v. observed mean EQ-5D scores in the split sample. Validation using the multisite validation approach identified prediction error variability, MAE of 0.081 to 0.119, when predicting EQ-5D.LIMITATIONS: The statistical relationship may not generalize well to all study populations as we demonstrated in our multisite analysis.CONCLUSIONS: An empirical algorithm predicting EQ-5D weights from RMDQ scores provides a currently unavailable link for conducting economic evaluations in low back pain studies.

Resumo Limpo

ckground link patientreport back pain outcom health util measur valuabl inform econom evaluationsmethod use back pain outcom use longitudin data bold registri assess back pain qualityoflif measur bold registri includ particip year health system use multipl baselin outcom measur rolandmorri disabl questionnair rmdq euroqold eqd back leg pain numer rate scale nrs develop valid model use standard splitsampl method novel multisit valid approach appli linear regress map rmdq eqd adjust age sex pain numer rate score nonlinear transform outcom measur comput r root mean squar error mean absolut error mae purpos model select final model includ eqd depend variabl independ variabl age rmdq back nrs use model predict eqd score valid samplesresult total particip baselin rmdq eqd mean age year femal negat correl observ baselin rmdq eqd select model development sampl r mae valid analys indic differ estim v observ mean eqd score split sampl valid use multisit valid approach identifi predict error variabl mae predict eqdlimit statist relationship may general well studi popul demonstr multisit analysisconclus empir algorithm predict eqd weight rmdq score provid current unavail link conduct econom evalu low back pain studi

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