TY - JOUR
T1 - Predicted and actual 2-year structural and pain progression in the IMI-APPROACH knee osteoarthritis cohort
AU - van Helvoort, Eefje M
AU - Jansen, Mylène P
AU - Marijnissen, Anne C A
AU - Kloppenburg, Margreet
AU - Blanco, Francisco J
AU - Haugen, Ida K
AU - Berenbaum, Francis
AU - Bay-Jensen, Anne-Christine C
AU - Ladel, Christoph
AU - Lalande, Agnes
AU - Larkin, Jonathan
AU - Loughlin, John
AU - Mobasheri, Ali
AU - Weinans, Harrie H
AU - Widera, Pawel
AU - Bacardit, Jaume
AU - Welsing, Paco M J
AU - Lafeber, Floris P J G
N1 - Publisher Copyright:
© 2022 The Author(s). Published by Oxford University Press on behalf of the British Society for Rheumatology.
PY - 2023/1/1
Y1 - 2023/1/1
N2 - OBJECTIVES: The 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. METHODS: Actual 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. RESULTS: Actual 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). CONCLUSION: The 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 REGISTRATION: ClinicalTrials.gov, https://clinicaltrials.gov, NCT03883568.
AB - OBJECTIVES: The 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. METHODS: Actual 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. RESULTS: Actual 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). CONCLUSION: The 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 REGISTRATION: ClinicalTrials.gov, https://clinicaltrials.gov, NCT03883568.
KW - Knee osteoarthritis
KW - biomarkers
KW - clinical trials and methods
KW - study design
UR - http://www.scopus.com/inward/record.url?scp=85144637025&partnerID=8YFLogxK
U2 - 10.1093/rheumatology/keac292
DO - 10.1093/rheumatology/keac292
M3 - Article
C2 - 35575381
SN - 1462-0324
VL - 62
SP - 147
EP - 157
JO - Rheumatology (Oxford, England)
JF - Rheumatology (Oxford, England)
IS - 1
ER -