Evidence map›Paper›PMID 36732785›Full record

ArticleJournal of orthopaedic surgery and research2023

Mapping of disease-specific Oxford Knee Score onto EQ-5D-5L utility index in knee osteoarthritis.

Hadeer Fawaz, Omaima Yassine, Abdullah Hammad, Ramez Bedwani, Ghada Abu-Sheasha

Open access · goldAbstract read
In one paragraph

Article in Journal of orthopaedic surgery and research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 2 pooled it
2.2field-weighted citation impact, top 12% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 2 syntheses or guidelines pooled it, 9 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Hadeer FawazDepartment of Biomedical Informatics and Medical Statistics, Medical Research Institute, University of Alexandria, 165, Horreya Avenue, Hadara, Alexandria, Egypt. mri.hadeer.m.informatics17@alexu.edu.eg.
Omaima YassineDepartment of Biomedical Informatics and Medical Statistics, Medical Research Institute, University of Alexandria, 165, Horreya Avenue, Hadara, Alexandria, Egypt.
Abdullah HammadDepartment of Orthopaedic Surgery and Traumatology, El‑Hadra Hospital, University of Alexandria, Alexandria, Egypt.
Ramez BedwaniDepartment of Biomedical Informatics and Medical Statistics, Medical Research Institute, University of Alexandria, 165, Horreya Avenue, Hadara, Alexandria, Egypt.
Ghada Abu-SheashaDepartment of Biomedical Informatics and Medical Statistics, Medical Research Institute, University of Alexandria, 165, Horreya Avenue, Hadara, Alexandria, Egypt.
Alexandria University · EG

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEQ5D 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

methodsThis 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.

resultsMobility 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.

conclusionsThe 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.

Indexed as

Osteoarthritis, KneeCross-Sectional StudiesHealth StatusHumansPainQuality of LifeSurveys and QuestionnairesEQ-5D-5LModel mappingOxford Knee Score (OKS) questionnaireQuality of life utility index

Identifiers

PMID36732785
PMCPMC9896832
OpenAlexW4318982239

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.