ArticleRheumatology (Oxford, England)2022
Predicted and actual 2-year structural and pain progression in the IMI-APPROACH knee osteoarthritis cohort.
Article in Rheumatology (Oxford, England), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03883568 (A 2-year Multicentre, EU, Exploratory Study Without Therapeutic Benefit in Patients With Knee Osteoarthritis to Describe, Validate, and Predict Phenotypes of Knee Osteoarthritis by Use of Clinical, Imaging, and Biochemical), which is not on this map. Cited by 8 papers.
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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.
A 2-year Multicentre, EU, Exploratory Study Without Therapeutic Benefit in Patients With Knee Osteoarthritis to Describe, Validate, and Predict Phenotypes of Knee Osteoarthritis by Use of Clinical, Imaging, and Biochemical (Bio)Markers.
Who cites it
8 citing papers in PubMed.
- Trial
- Beyond the algorithms: Challenges in predicting knee osteoarthritis pain from a machine learning point of view.Osteoarthritis imaging · 2026Article
- Factors associated with radiographic progression of hand osteoarthritis over 2 years.RMD open · 2026Article
- Spatially resolved longitudinal changes in tibial subchondral trabecular bone texture for exploratory prediction of incident knee osteoarthritis.Frontiers in physiology · 2026Article
- Magnetic Resonance Imaging Biomarkers of Knee Osteoarthritis Progression.ACR open rheumatology · 2025Article
- Association between progression of knee osteoarthritis pathology and gait changes over two years: Data from the IMI-APPROACH cohort.Osteoarthritis imaging · 2024Article
- Short-term variations in trabecular bone texture parameters associated to radio-clinical biomarkers improve the prediction of radiographic knee osteoarthritis progression.Scientific reports · 2023Article
- Development and validation of a machine learning-supported strategy of patient selection for osteoarthritis clinical trials: the IMI-APPROACH study.Osteoarthritis and cartilage open · 2023Article
Corrections and comments
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Authors and funding
18 authors.
Funding
Abstract
objectivesThe IMI-APPROACH knee osteoarthritis study used machine learning (ML) to predict structural and/or pain progression, expressed by a structural (S) and pain (P) predicted-progression score, to select patients from existing cohorts. This study evaluates the actual 2-year progression within the IMI-APPROACH, in relation to the predicted-progression scores.
methodsActual structural progression was measured using minimum joint space width (minJSW). Actual pain (progression) was evaluated using the Knee injury and Osteoarthritis Outcomes Score (KOOS) pain questionnaire. Progression was presented as actual change (Δ) after 2 years, and as progression over 2 years based on a per patient fitted regression line using 0, 0.5, 1 and 2-year values. Differences in predicted-progression scores between actual progressors and non-progressors were evaluated. Receiver operating characteristic (ROC) curves were constructed and corresponding area under the curve (AUC) reported. Using Youden's index, optimal cut-offs were chosen to enable evaluation of both predicted-progression scores to identify actual progressors.
resultsActual structural progressors were initially assigned higher S predicted-progression scores compared with structural non-progressors. Likewise, actual pain progressors were assigned higher P predicted-progression scores compared with pain non-progressors. The AUC-ROC for the S predicted-progression score to identify actual structural progressors was poor (0.612 and 0.599 for Δ and regression minJSW, respectively). The AUC-ROC for the P predicted-progression score to identify actual pain progressors were good (0.817 and 0.830 for Δ and regression KOOS pain, respectively).
conclusionThe S and P predicted-progression scores as provided by the ML models developed and used for the selection of IMI-APPROACH patients were to some degree able to distinguish between actual progressors and non-progressors.
trial registrationClinicalTrials.gov, https://clinicaltrials.gov, NCT03883568.
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