Tool for osteoarthritis risk prediction (TOARP) over 8 years using baseline clinical data, X‐ray, and MRI: Data from the osteoarthritis initiative
Background Osteoarthritis (OA), a multifactorial disease causing joint degeneration, often leads to severe disability. The rising rates of disability highlight the need for implementing preventative measures at early stages of the disease, which would especially benefit subjects at high risk for OA...
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Published in | Journal of magnetic resonance imaging Vol. 47; no. 6; pp. 1517 - 1526 |
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Main Authors | , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
Wiley Subscription Services, Inc
01.06.2018
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Subjects | |
Online Access | Get full text |
ISSN | 1053-1807 1522-2586 1522-2586 |
DOI | 10.1002/jmri.25892 |
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Abstract | Background
Osteoarthritis (OA), a multifactorial disease causing joint degeneration, often leads to severe disability. The rising rates of disability highlight the need for implementing preventative measures at early stages of the disease, which would especially benefit subjects at high risk for OA development.
Purpose
To develop a risk prediction tool for moderate‐severe OA (TOARP) over 8 years based on subject characteristics, knee radiographs, and MRI data at baseline using data from the Osteoarthritis Initiative (OAI).
Study Type
Retrospective.
Subjects
641 subjects with no/mild radiographic OA (Kellgren–Lawrence [KL] 0–2) and no clinically significant symptoms (Western Ontario and McMaster Universities Arthritis Index [WOMAC] 0–1) were selected from the OAI.
Field Strength/Sequence
MR images were obtained using 3.0T.
Assessment
Compartment‐specific cartilage and meniscus morphology and cartilage T2 were assessed. Baseline subject demographics, risk factors, KL score, cartilage WORMS score, presence of meniscus tear, and cartilage T2 were used to predict the development of moderate/severe OA (KL = 3–4 or WOMAC pain ≥5 or total knee replacement [TKR]) over 8 years.
Statistical Tests
Best subsets variable selection followed by cross‐validation were used to assess which combinations of variables best predict moderate/severe OA.
Results
Model 1 included KL score, previous knee injury in the last 12 months, age, gender, and BMI. Model 2 included all variables in Model 1 plus presence of cartilage defects in the lateral femur and patella, and presence of a meniscal tear. Model 3 included all variables in Models 1 and 2, plus cartilage T2 in the medial tibia and medial femur. Compared to Model 1 (cross‐validated AUC = 0.67), Model 3 performed significantly better (AUC = 0.72, P = 0.04), while Model 2 showed a statistical trend (AUC = 0.71, P = 0.08).
Data Conclusion
We established a risk calculator for the development of moderate/severe knee OA over 8 years that includes radiographic and MRI data. The inclusion of MRI‐based morphological abnormalities and cartilage T2 significantly improved model performance.
Level of Evidence: 2
Technical Efficacy: Stage 3
J. Magn. Reson. Imaging 2018;47:1517–1526. |
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AbstractList | Background
Osteoarthritis (OA), a multifactorial disease causing joint degeneration, often leads to severe disability. The rising rates of disability highlight the need for implementing preventative measures at early stages of the disease, which would especially benefit subjects at high risk for OA development.
Purpose
To develop a risk prediction tool for moderate‐severe OA (TOARP) over 8 years based on subject characteristics, knee radiographs, and MRI data at baseline using data from the Osteoarthritis Initiative (OAI).
Study Type
Retrospective.
Subjects
641 subjects with no/mild radiographic OA (Kellgren–Lawrence [KL] 0–2) and no clinically significant symptoms (Western Ontario and McMaster Universities Arthritis Index [WOMAC] 0–1) were selected from the OAI.
Field Strength/Sequence
MR images were obtained using 3.0T.
Assessment
Compartment‐specific cartilage and meniscus morphology and cartilage T2 were assessed. Baseline subject demographics, risk factors, KL score, cartilage WORMS score, presence of meniscus tear, and cartilage T2 were used to predict the development of moderate/severe OA (KL = 3–4 or WOMAC pain ≥5 or total knee replacement [TKR]) over 8 years.
Statistical Tests
Best subsets variable selection followed by cross‐validation were used to assess which combinations of variables best predict moderate/severe OA.
Results
Model 1 included KL score, previous knee injury in the last 12 months, age, gender, and BMI. Model 2 included all variables in Model 1 plus presence of cartilage defects in the lateral femur and patella, and presence of a meniscal tear. Model 3 included all variables in Models 1 and 2, plus cartilage T2 in the medial tibia and medial femur. Compared to Model 1 (cross‐validated AUC = 0.67), Model 3 performed significantly better (AUC = 0.72, P = 0.04), while Model 2 showed a statistical trend (AUC = 0.71, P = 0.08).
Data Conclusion
We established a risk calculator for the development of moderate/severe knee OA over 8 years that includes radiographic and MRI data. The inclusion of MRI‐based morphological abnormalities and cartilage T2 significantly improved model performance.
Level of Evidence: 2
Technical Efficacy: Stage 3
J. Magn. Reson. Imaging 2018;47:1517–1526. Osteoarthritis (OA), a multifactorial disease causing joint degeneration, often leads to severe disability. The rising rates of disability highlight the need for implementing preventative measures at early stages of the disease, which would especially benefit subjects at high risk for OA development.BACKGROUNDOsteoarthritis (OA), a multifactorial disease causing joint degeneration, often leads to severe disability. The rising rates of disability highlight the need for implementing preventative measures at early stages of the disease, which would especially benefit subjects at high risk for OA development.To develop a risk prediction tool for moderate-severe OA (TOARP) over 8 years based on subject characteristics, knee radiographs, and MRI data at baseline using data from the Osteoarthritis Initiative (OAI).PURPOSETo develop a risk prediction tool for moderate-severe OA (TOARP) over 8 years based on subject characteristics, knee radiographs, and MRI data at baseline using data from the Osteoarthritis Initiative (OAI).Retrospective.STUDY TYPERetrospective.641 subjects with no/mild radiographic OA (Kellgren-Lawrence [KL] 0-2) and no clinically significant symptoms (Western Ontario and McMaster Universities Arthritis Index [WOMAC] 0-1) were selected from the OAI.SUBJECTS641 subjects with no/mild radiographic OA (Kellgren-Lawrence [KL] 0-2) and no clinically significant symptoms (Western Ontario and McMaster Universities Arthritis Index [WOMAC] 0-1) were selected from the OAI.MR images were obtained using 3.0T.FIELD STRENGTH/SEQUENCEMR images were obtained using 3.0T.Compartment-specific cartilage and meniscus morphology and cartilage T2 were assessed. Baseline subject demographics, risk factors, KL score, cartilage WORMS score, presence of meniscus tear, and cartilage T2 were used to predict the development of moderate/severe OA (KL = 3-4 or WOMAC pain ≥5 or total knee replacement [TKR]) over 8 years.ASSESSMENTCompartment-specific cartilage and meniscus morphology and cartilage T2 were assessed. Baseline subject demographics, risk factors, KL score, cartilage WORMS score, presence of meniscus tear, and cartilage T2 were used to predict the development of moderate/severe OA (KL = 3-4 or WOMAC pain ≥5 or total knee replacement [TKR]) over 8 years.Best subsets variable selection followed by cross-validation were used to assess which combinations of variables best predict moderate/severe OA.STATISTICAL TESTSBest subsets variable selection followed by cross-validation were used to assess which combinations of variables best predict moderate/severe OA.Model 1 included KL score, previous knee injury in the last 12 months, age, gender, and BMI. Model 2 included all variables in Model 1 plus presence of cartilage defects in the lateral femur and patella, and presence of a meniscal tear. Model 3 included all variables in Models 1 and 2, plus cartilage T2 in the medial tibia and medial femur. Compared to Model 1 (cross-validated AUC = 0.67), Model 3 performed significantly better (AUC = 0.72, P = 0.04), while Model 2 showed a statistical trend (AUC = 0.71, P = 0.08).RESULTSModel 1 included KL score, previous knee injury in the last 12 months, age, gender, and BMI. Model 2 included all variables in Model 1 plus presence of cartilage defects in the lateral femur and patella, and presence of a meniscal tear. Model 3 included all variables in Models 1 and 2, plus cartilage T2 in the medial tibia and medial femur. Compared to Model 1 (cross-validated AUC = 0.67), Model 3 performed significantly better (AUC = 0.72, P = 0.04), while Model 2 showed a statistical trend (AUC = 0.71, P = 0.08).We established a risk calculator for the development of moderate/severe knee OA over 8 years that includes radiographic and MRI data. The inclusion of MRI-based morphological abnormalities and cartilage T2 significantly improved model performance.DATA CONCLUSIONWe established a risk calculator for the development of moderate/severe knee OA over 8 years that includes radiographic and MRI data. The inclusion of MRI-based morphological abnormalities and cartilage T2 significantly improved model performance.2 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2018;47:1517-1526.LEVEL OF EVIDENCE2 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2018;47:1517-1526. BackgroundOsteoarthritis (OA), a multifactorial disease causing joint degeneration, often leads to severe disability. The rising rates of disability highlight the need for implementing preventative measures at early stages of the disease, which would especially benefit subjects at high risk for OA development.PurposeTo develop a risk prediction tool for moderate‐severe OA (TOARP) over 8 years based on subject characteristics, knee radiographs, and MRI data at baseline using data from the Osteoarthritis Initiative (OAI).Study TypeRetrospective.Subjects641 subjects with no/mild radiographic OA (Kellgren–Lawrence [KL] 0–2) and no clinically significant symptoms (Western Ontario and McMaster Universities Arthritis Index [WOMAC] 0–1) were selected from the OAI.Field Strength/SequenceMR images were obtained using 3.0T.AssessmentCompartment‐specific cartilage and meniscus morphology and cartilage T2 were assessed. Baseline subject demographics, risk factors, KL score, cartilage WORMS score, presence of meniscus tear, and cartilage T2 were used to predict the development of moderate/severe OA (KL = 3–4 or WOMAC pain ≥5 or total knee replacement [TKR]) over 8 years.Statistical TestsBest subsets variable selection followed by cross‐validation were used to assess which combinations of variables best predict moderate/severe OA.ResultsModel 1 included KL score, previous knee injury in the last 12 months, age, gender, and BMI. Model 2 included all variables in Model 1 plus presence of cartilage defects in the lateral femur and patella, and presence of a meniscal tear. Model 3 included all variables in Models 1 and 2, plus cartilage T2 in the medial tibia and medial femur. Compared to Model 1 (cross‐validated AUC = 0.67), Model 3 performed significantly better (AUC = 0.72, P = 0.04), while Model 2 showed a statistical trend (AUC = 0.71, P = 0.08).Data ConclusionWe established a risk calculator for the development of moderate/severe knee OA over 8 years that includes radiographic and MRI data. The inclusion of MRI‐based morphological abnormalities and cartilage T2 significantly improved model performance.Level of Evidence: 2Technical Efficacy: Stage 3J. Magn. Reson. Imaging 2018;47:1517–1526. Osteoarthritis (OA), a multifactorial disease causing joint degeneration, often leads to severe disability. The rising rates of disability highlight the need for implementing preventative measures at early stages of the disease, which would especially benefit subjects at high risk for OA development. To develop a risk prediction tool for moderate-severe OA (TOARP) over 8 years based on subject characteristics, knee radiographs, and MRI data at baseline using data from the Osteoarthritis Initiative (OAI). Retrospective. 641 subjects with no/mild radiographic OA (Kellgren-Lawrence [KL] 0-2) and no clinically significant symptoms (Western Ontario and McMaster Universities Arthritis Index [WOMAC] 0-1) were selected from the OAI. MR images were obtained using 3.0T. Compartment-specific cartilage and meniscus morphology and cartilage T were assessed. Baseline subject demographics, risk factors, KL score, cartilage WORMS score, presence of meniscus tear, and cartilage T were used to predict the development of moderate/severe OA (KL = 3-4 or WOMAC pain ≥5 or total knee replacement [TKR]) over 8 years. Best subsets variable selection followed by cross-validation were used to assess which combinations of variables best predict moderate/severe OA. Model 1 included KL score, previous knee injury in the last 12 months, age, gender, and BMI. Model 2 included all variables in Model 1 plus presence of cartilage defects in the lateral femur and patella, and presence of a meniscal tear. Model 3 included all variables in Models 1 and 2, plus cartilage T in the medial tibia and medial femur. Compared to Model 1 (cross-validated AUC = 0.67), Model 3 performed significantly better (AUC = 0.72, P = 0.04), while Model 2 showed a statistical trend (AUC = 0.71, P = 0.08). We established a risk calculator for the development of moderate/severe knee OA over 8 years that includes radiographic and MRI data. The inclusion of MRI-based morphological abnormalities and cartilage T significantly improved model performance. 2 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2018;47:1517-1526. |
Author | Heilmeier, Ursula Schwaiger, Benedikt J. Gersing, Alexandra S. Joseph, Gabby B. Lynch, John A. McCulloch, Charles E. Kretzschmar, Martin Nevitt, Michael C. Lane, Nancy E. Link, Thomas M. Neumann, Jan |
Author_xml | – sequence: 1 givenname: Gabby B. surname: Joseph fullname: Joseph, Gabby B. email: gabby.joseph@ucsf.edu organization: University of California – sequence: 2 givenname: Charles E. surname: McCulloch fullname: McCulloch, Charles E. organization: University of California – sequence: 3 givenname: Michael C. surname: Nevitt fullname: Nevitt, Michael C. organization: University of California – sequence: 4 givenname: Jan surname: Neumann fullname: Neumann, Jan organization: University of California – sequence: 5 givenname: Alexandra S. surname: Gersing fullname: Gersing, Alexandra S. organization: University of California – sequence: 6 givenname: Martin surname: Kretzschmar fullname: Kretzschmar, Martin organization: University of California – sequence: 7 givenname: Benedikt J. surname: Schwaiger fullname: Schwaiger, Benedikt J. organization: University of California – sequence: 8 givenname: John A. surname: Lynch fullname: Lynch, John A. organization: University of California – sequence: 9 givenname: Ursula surname: Heilmeier fullname: Heilmeier, Ursula organization: University of California – sequence: 10 givenname: Nancy E. surname: Lane fullname: Lane, Nancy E. organization: University of California – sequence: 11 givenname: Thomas M. surname: Link fullname: Link, Thomas M. organization: University of California |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/29143404$$D View this record in MEDLINE/PubMed |
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Osteoarthritis (OA), a multifactorial disease causing joint degeneration, often leads to severe disability. The rising rates of disability highlight... Osteoarthritis (OA), a multifactorial disease causing joint degeneration, often leads to severe disability. The rising rates of disability highlight the need... BackgroundOsteoarthritis (OA), a multifactorial disease causing joint degeneration, often leads to severe disability. The rising rates of disability highlight... |
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SubjectTerms | Abnormalities Aged Algorithms Area Under Curve Arthritis Arthroplasty, Replacement, Knee Background radiation Biocompatibility Biomarkers Body mass Cartilage Cartilage - diagnostic imaging Cartilage diseases cartilage T2 Degeneration Demographics Demography Diagnosis, Computer-Assisted - methods Disabled Persons Female Femur Field strength Humans Knee Knee - diagnostic imaging Knee Joint - diagnostic imaging Longitudinal Studies Magnetic Resonance Imaging Male Mathematical models Meniscus Meniscus - injuries Middle Aged MRI Osteoarthritis Osteoarthritis, Knee - diagnostic imaging Pain Radiographs Radiography Reproducibility of Results Retrospective Studies Risk analysis Risk Assessment Risk factors risk model ROC Curve Sensitivity and Specificity Statistical analysis Statistical tests Surgical implants Tearing Tibia Variables X-Rays |
Title | Tool for osteoarthritis risk prediction (TOARP) over 8 years using baseline clinical data, X‐ray, and MRI: Data from the osteoarthritis initiative |
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