Machine Learning Approaches to the Prediction of Osteoarthritis Phenotypes and Outcomes

Murphy LB, Cisternas MG, Pasta DJ, Helmick CG, Yelin EH. Medical expenditures and earnings losses among us adults with arthritis in 2013. Arthritis Care Res (Hoboken). 2018;70(6):869–76.

Article  PubMed  Google Scholar 

Kolasinski SL, Neogi T, Hochberg MC, Oatis C, Guyatt G, Block J, et al. 2019 American College of Rheumatology/Arthritis Foundation Guideline for the Management of Osteoarthritis of the Hand, Hip, and Knee. Arthritis Rheumatol. 2020;72(2):220–33.

Article  PubMed  Google Scholar 

Grässel S, Muschter D. Recent advances in the treatment of osteoarthritis. F1000Res. 2020;9:F1000 Faculty Rev–325. https://doi.org/10.12688/f1000research.22115.1.

Loos NL, Hoogendam L, Souer JS, Slijper HP, Andrinopoulou ER, Coppieters MW, et al. Machine learning can be used to predict function but not pain after surgery for thumb carpometacarpal osteoarthritis. Clin Orthop Relat Res. 2022;480(7):1271–84.

Article  PubMed  PubMed Central  Google Scholar 

Bowes MA, Kacena K, Alabas OA, Brett AD, Dube B, Bodick N, et al. Machine-learning, MRI bone shape and important clinical outcomes in osteoarthritis: data from the Osteoarthritis Initiative. Ann Rheum Dis. 2021;80(4):502–8.

Article  PubMed  Google Scholar 

Chaudhari AS, Stevens KJ, Wood JP, Chakraborty AK, Gibbons EK, Fang Z, et al. Utility of deep learning super-resolution in the context of osteoarthritis MRI biomarkers. J Magn Reson Imaging. 2020;51(3):768–79.

Article  PubMed  Google Scholar 

Lester G. The Osteoarthritis Initiative: A NIH Public-Private Partnership. HSS J. 2012;8(1):62–3.

Article  PubMed  Google Scholar 

Chen G, Sullivan PF, Kosorok MR. Biclustering with heterogeneous variance. Proc Natl Acad Sci U S A. 2013;110(30):12253–8.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Cheng Y, Church GM. Biclustering of expression data. Proc Int Conf Intell Syst Mol Biol. 2000;8:93–103.

CAS  PubMed  Google Scholar 

Nelson AE, Keefe TH, Schwartz TA, Callahan LF, Loeser RF, Golightly YM, et al. Biclustering reveals potential knee OA phenotypes in exploratory analyses: Data from the Osteoarthritis Initiative. PLoS One. 2022;17(5):e0266964.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Demanse D, Saxer F, Lustenberger P, Tanko LB, Nikolaus P, Rasin I, et al. Unsupervised machine-learning algorithms for the identification of clinical phenotypes in the osteoarthritis initiative database. Semin Arthritis Rheum. 2023;58:152140.

Article  CAS  PubMed  Google Scholar 

Trajerova M, Kriegova E, Mikulkova Z, Savara J, Kudelka M, Gallo J. Knee osteoarthritis phenotypes based on synovial fluid immune cells correlate with clinical outcome trajectories. Osteoarthritis Cartilage. 2022;30(12):1583–92.

Article  CAS  PubMed  Google Scholar 

Deveza LA, Nelson AE, Loeser RF. Phenotypes of osteoarthritis: Current state and future implications. Clin Exp Rheumatol. 2019;37 Suppl;120(5):64–72.

Google Scholar 

Mobasheri A, van Spil WE, Budd E, Uzieliene I, Bernotiene E, Bay-Jensen AC, et al. Molecular taxonomy of osteoarthritis for patient stratification, disease management and drug development: Biochemical markers associated with emerging clinical phenotypes and molecular endotypes. Curr Opin Rheumatol. 2019;31(1):80–9.

Article  PubMed  Google Scholar 

Steinberg J, Southam L, Fontalis A, Clark MJ, Jayasuriya RL, Swift D, et al. Linking chondrocyte and synovial transcriptional profile to clinical phenotype in osteoarthritis. Ann Rheum Dis. 2021;80(8):1070–4. Used machine learning to assess gene expression profiles with results supporting the theory that osteoarthritis is a continuum with less variation at later stages of disease; greater heterogeneity early in disease suggests an opportunity for tailored treatment.

Article  CAS  PubMed  Google Scholar 

Widera P, PMJ W, Ladel C, Loughlin J, Lafeber F, Petit Dop F, et al. Multi-classifier prediction of knee osteoarthritis progression from incomplete imbalanced longitudinal data. Sci Rep. 2020;10(1):8427. Rigorous statistical framework using advanced statistical techniques to account for classes imbalance and incomplete data. Used categorical rather than binary definition of the outcome, KOA progression.

Article  CAS  PubMed  PubMed Central  Google Scholar 

van Helvoort EM, van Spil WE, Jansen MP, Welsing PMJ, Kloppenburg M, Loef M, et al. Cohort profile: The Applied Public-Private Research enabling OsteoArthritis Clinical Headway (IMI-APPROACH) study: a 2-year, European, cohort study to describe, validate and predict phenotypes of osteoarthritis using clinical, imaging and biochemical markers. BMJ Open. 2020;10(7):e035101.

Article  PubMed  PubMed Central  Google Scholar 

Kraus VB, Collins JE, Hargrove D, Losina E, Nevitt M, Katz JN, et al. Predictive validity of biochemical biomarkers in knee osteoarthritis: Data from the FNIH OA biomarkers consortium. Ann Rheum Dis. 2017;76(1):186–95.

Article  CAS  PubMed  Google Scholar 

Bonakdari H, Pelletier JP, Abram F, Martel-Pelletier J. A machine learning model to predict knee osteoarthritis cartilage volume changes over time using baseline bone curvature. Biomedicines. 2022;10(6)

Raynauld JP, Pelletier JP, Delorme P, Dodin P, Abram F, Martel-Pelletier J. Bone curvature changes can predict the impact of treatment on cartilage volume loss in knee osteoarthritis: data from a 2-year clinical trial. Rheumatology (Oxford). 2017;56(6):989–98.

Article  PubMed  Google Scholar 

Raynauld JP, Martel-Pelletier J, Bias P, Laufer S, Haraoui B, Choquette D, et al. Protective effects of licofelone, a 5-lipoxygenase and cyclo-oxygenase inhibitor, versus naproxen on cartilage loss in knee osteoarthritis: a first multicentre clinical trial using quantitative MRI. Ann Rheum Dis. 2009;68(6):938–47.

Article  CAS  PubMed  Google Scholar 

Ilse M, Tomczak J, Welling M. Attention-based deep multiple instance learning. In: International conference on machine learning. PMLR; 2018. p. 2127–36.

Google Scholar 

Schiratti JB, Dubois R, Herent P, Cahane D, Dachary J, Clozel T, et al. A deep learning method for predicting knee osteoarthritis radiographic progression from MRI. Arthritis Res Ther. 2021;23(1):262. Developed a weakly supervised deep learning algorithm to predict OA progression over a short time frame; encouraging results suggest that such algorithms can feasibility be integrated into the screening phase of clinical trials and improve how inclusion criteria are determined.

Article  PubMed  PubMed Central  Google Scholar 

Selvaraju RR, Cogswell M, Das A, Vedantam R, Parikh D, Batra D. Grad-CAM: Visual explanations from deep networks via gradient-based localization. Int J Comput Vis. 2020;128(2):336–59.

Article  Google Scholar 

Guan B, Liu F, Haj-Mirzaian A, Demehri S, Samsonov A, Neogi T, et al. Deep learning risk assessment models for predicting progression of radiographic medial joint space loss over a 48-MONTH follow-up period. Osteoarthritis Cartilage. 2020;28(4):428–37.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Guan B, Liu F, Mizaian AH, Demehri S, Samsonov A, Guermazi A, et al. Deep learning approach to predict pain progression in knee osteoarthritis. Skeletal Radiol. 2022;51(2):363–73.

Article  PubMed  Google Scholar 

Nelson AE, Arbeeva L. Narrative review of machine learning in rheumatic and musculoskeletal diseases for clinicians and researchers: biases, goals, and future directions. J Rheumatol. 2022;49(11):1191–200. Review of machine learning in rheumatic and musculoskeletal diseases beyond osteoarthritis, providing extensive discussion around potential biases and limitations.

CAS  PubMed  Google Scholar 

Yoo HJ, Jeong HW, Kim SW, Kim M, Lee JI, Lee YS. Prediction of progression rate and fate of osteoarthritis: Comparison of machine learning algorithms. J Orthop Res. 2023;41(3):583–90.

Article  CAS  PubMed  Google Scholar 

Dunn CM, Sturdy C, Velasco C, Schlupp L, Prinz E, Izda V, et al. Peripheral blood DNA methylation-based machine learning models for prediction of knee osteoarthritis progression: Biologic specimens and data from the osteoarthritis initiative and johnston county osteoarthritis project. Arthritis Rheumatol. 2023;75(1):28–40. Use of fully independent data for external validation and investigation of potentially novel epigenetic biomarkers for useful clinical progression definitions are strengths of this work.

Article  CAS  PubMed  Google Scholar 

Bonakdari H, Pelletier JP, Blanco FJ, Rego-Pérez I, Durán-Sotuela A, Aitken D, et al. Single nucleotide polymorphism genes and mitochondrial DNA haplogroups as biomarkers for early prediction of knee osteoarthritis structural progressors: use of supervised machine learning classifiers. BMC Med. 2022;20(1):316.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Dore D, Martens A, Quinn S, Ding C, Winzenberg T, Zhai G, et al. Bone marrow lesions predict site-specific cartilage defect development and volume loss: a prospective study in older adults. Arthritis Res Ther. 2010;12(6):R222.

Article  PubMed  PubMed Central  Google Scholar 

Leung K, Zhang B, Tan J, Shen Y, Geras KJ, Babb JS, et al. Prediction of total knee replacement and diagnosis of osteoarthritis by using deep learning on knee radiographs: data from the osteoarthritis initiative. Radiology. 2020;296(3):584–93.

Article  PubMed  Google Scholar 

Jamshidi A, Pelletier JP, Labbe A, Abram F, Martel-Pelletier J, Droit A. Machine learning-based individualized survival prediction model for total knee replacement in osteoarthritis: data from the osteoarthritis initiative. Arthritis Care Res (Hoboken). 2021;73(10):1518–27.

Article  PubMed  Google Scholar 

Tiulpin A, Saarakkala S, Mathiessen A, Hammer HB, Furnes O, Nordsletten L, et al. Predicting total knee arthroplasty from ultrasonography using machine learning. Osteoarthr Cartil Open. 2022;4(4):100319.

Article  PubMed  PubMed Central  Google Scholar 

Hirvasniemi J, Runhaar J, van der Heijden RA, Zokaeinikoo M, Yang M, Li X, et al. The KNee OsteoArthritis Prediction (KNOAP2020) challenge: An image analysis challenge to predict incident symptomatic radiographic knee osteoarthritis from MRI and X-ray images. Osteoarthritis Cartilage. 2023;31(1):115–25. The first biomedical challenge on the prediction of incident symptomatic radiographic knee OA, a step towards unbiased comparison between different models, robust validation and clinical translation of AI/ML algorithms.

Article  CAS  PubMed  Google Scholar 

Runhaar J, van Middelkoop M, Reijman M, Willemsen S, Oei EH, Vroegindeweij D, et al. Prevention of knee osteoarthritis in overweight females: the first preventive randomized controlled trial in osteoarthritis. Am J Med. 2015;128(8):888–95. e4

Article  PubMed  Google Scholar 

Allen KD, Helmick CG, Schwartz TA, DeVellis RF, Renner JB, Jordan JM. Racial differences in self-reported pain and function among individuals with radiographic hip and knee osteoarthritis: the Johnston County Osteoarthritis Project. Osteoarthritis Cartilage. 2009;17(9):1132–6.

Article  CAS  PubMed  PubMed Central 

留言 (0)

沒有登入
gif