الفهرس 
INTRODUCTIONOnly 14 pages are availabe for public view
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Abstract
EQ5D is a generic measure of health. It provides a single index value for health
status that can be used in the clinical and economic evaluation of healthcare. Oxford Knee
Score (OKS) is a joint-specific outcome measure tool designed to assess symptoms and
function in osteoarthritis patients after joint replacement surgery. Though widely used, it has
the disadvantage of lacking health index value. To fill the gap between functional and generic
questionnaires with economic value, we linked generic EQ-5D-5L to the specific OKS to
give a single index value for health status in KOA patients.
Questions/purposes: Developing and evaluating an algorithm to estimate EuroQoL generic
health utility scores (EQ-5D-5L) from the disease-specific OKS using data from patients with
knee osteoarthritis (KO).
Patients and Methods:This is a cross-sectional study of 571 patients with KO. We used four
distinct mapping algorithms: Cumulative Probability for Ordinal Data, Penalized Ordinal
Regression, CART (Classification and Regression Trees), and Ordinal random forest. We
compared the resultant models’ degrees of accuracy.
Results:Mobility was best predicted by penalized regression with pre-processed predictors,
usual activities by random forest, pain/discomfort by cumulative probability with pre-
processed predictors, self-care by random forest with RFE (recursive feature elimination)
predictors, and anxiety/depression by CART with RFE predictors. Model accuracy was
lowest with anxiety/depression and highest with mobility and usual activities. Using available
country value sets, the average MAE was 0.098 ±0.022, ranging from 0.063 to 0.142; and the
average MSE was 0.020 ± 0.008 ranging from 0.008 to 0.042.
Conclusions: The current study derived accurate mapping techniques from OKS to the
domains of EQ-5D-5L, allowing for the computation of QALYs in economic evaluations. A
machine learning-based strategy offers a viable mapping alternative that merits further
exploration.