Biomarkers in osteoarthritis: current status and outlook - the FNIH Biomarkers Consortium PROGRESS OA study.


Journal

Skeletal radiology
ISSN: 1432-2161
Titre abrégé: Skeletal Radiol
Pays: Germany
ID NLM: 7701953

Informations de publication

Date de publication:
Nov 2023
Historique:
received: 17 07 2022
accepted: 12 01 2023
revised: 09 01 2023
medline: 20 9 2023
pubmed: 25 1 2023
entrez: 24 1 2023
Statut: ppublish

Résumé

Currently, no disease-modifying therapies are approved for osteoarthritis (OA) use. One obstacle to trial success in this field has been our existing endpoints' limited validity and responsiveness. To overcome this impasse, the Foundation for the NIH OA Biomarkers Consortium is focused on investigating biomarkers for a prognostic context of use for subsequent qualification through regulatory agencies. This narrative review describes this activity and the work underway, focusing on the PROGRESS OA study.

Identifiants

pubmed: 36692532
doi: 10.1007/s00256-023-04284-w
pii: 10.1007/s00256-023-04284-w
pmc: PMC10509067
doi:

Substances chimiques

Biomarkers 0

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

2323-2339

Informations de copyright

© 2023. The Author(s).

Références

Hunter DJ, Schofield D, Callander E. The individual and socioeconomic impact of osteoarthritis. Nat Rev Rheumatol. 2014;10(7):437–41.
doi: 10.1038/nrrheum.2014.44 pubmed: 24662640
Hunter DJ, March L, Chew M. Osteoarthritis in 2020 and beyond: a Lancet Commission. Lancet. 2020;396(10264):1711–2.
doi: 10.1016/S0140-6736(20)32230-3 pubmed: 33159851
Prevalence of disabilities and associated health conditions among adults--United States, 1999. MMWR Morb Mortal Wkly Rep. 2001;50(7):120–5 erratum appears in MMWR Morb Mortal Wkly Rep 2001;50(8):149.
Guccione AA, et al. The effects of specific medical conditions on the functional limitations of elders in the Framingham Study. Am J Public Health. 1994;84(3):351–8.
doi: 10.2105/AJPH.84.3.351 pubmed: 8129049 pmcid: 1614827
Hunter DJ, et al. A pathway and approach to biomarker validation and qualification for osteoarthritis clinical trials. Curr Drug Targets. 2010;11(5):536–45.
doi: 10.2174/138945010791011947 pubmed: 20199395 pmcid: 3261486
Oo WM, et al. The development of disease-modifying therapies for osteoarthritis (DMOADs): the evidence to date. Drug Des Devel Ther. 2021;15:2921–45.
doi: 10.2147/DDDT.S295224 pubmed: 34262259 pmcid: 8273751
Eckstein F, et al. Intra-articular sprifermin reduces cartilage loss in addition to increasing cartilage gain independent of location in the femorotibial joint: post-hoc analysis of a randomised, placebo-controlled phase II clinical trial. Ann Rheum Dis. 2020;79(4):525–8.
doi: 10.1136/annrheumdis-2019-216453 pubmed: 32098758
Conaghan PG, et al. Disease-modifying effects of a novel cathepsin K inhibitor in osteoarthritis: a randomized controlled trial. Ann Intern Med. 2020;172(2):86–95.
doi: 10.7326/M19-0675 pubmed: 31887743
Thomas D, Burns J, Audette J, Carroll A, Dow-Hygelund C, Hay M. Clinical development success rates 2006-2015: Biotechnology Innovation Organization (BIO). Biomedtracker and Amplion. 2016:1–26. https://www.bio.org/sites/default/files/legacy/bioorg/docs/Clinical%20Development%20Success%20Rates%202006-2015%20-%20BIO,%20Biomedtracker,%20Amplion%202016.pdf
Burstein D, Hunter DJ. "Why aren’t we there yet?" Re-examining standard paradigms in imaging of OA: summary of the 2nd annual workshop on imaging based measures of osteoarthritis. Osteoarthritis Cartilage. 2009;17(5):571–8.
doi: 10.1016/j.joca.2009.01.008 pubmed: 19233336
FDA, USA. Guidance for industry. clinical development programs for drugs, devices, and biological products intended for the treatment of osteoarthritis (OA). 1999. http://www.fda.gov/Cber/gdlns/osteo.htm .
Mazzuca SA, Brandt KD. Is knee radiography useful for studying the efficacy of a disease-modifying osteoarthritis drug in humans?. [Review] [22 refs]. Rheum Dis Clin North Am. 2003;29(4):819–30.
doi: 10.1016/S0889-857X(03)00055-3 pubmed: 14603585
Mazzuca SA, et al. Pitfalls in the accurate measurement of joint space narrowing in semiflexed, anteroposterior radiographic imaging of the knee. Arthritis Rheum. 2004;50(8):2508–15.
doi: 10.1002/art.20363 pubmed: 15334464
Hunter DJ, et al. Biomarkers for osteoarthritis: current position and steps towards further validation. Best Prac. Res Clin Rheumatol. 2014;28(1):61–71.
doi: 10.1016/j.berh.2014.01.007
Menetski JP, et al. The Foundation for the National Institutes of Health Biomarkers Consortium: past accomplishments and new strategic direction. Clin Pharmacol Ther. 2019;105(4):829–43.
doi: 10.1002/cpt.1362 pubmed: 30648736 pmcid: 6593617
FDA. Biomarker qualification project 2018; Available from: https://www.fda.gov/media/128254/download .
Eckstein F, et al. Cartilage thickness change as an imaging biomarker of knee osteoarthritis progression - data from the foundation for the National Institutes of Health Osteoarthritis biomarkers consortium. Arthritis Rheumatol. 2015;67:3184–9.
doi: 10.1002/art.39324 pubmed: 26316262 pmcid: 5495918
Roemer FW, et al. Semi-quantitative MRI biomarkers of knee osteoarthritis progression in the FNIH biomarkers consortium cohort - methodologic aspects and definition of change. BMC Musculoskelet Disord. 2016;17(1):466.
doi: 10.1186/s12891-016-1310-6 pubmed: 27832771 pmcid: 5105263
Collins JE, et al. Semiquantitative imaging biomarkers of knee osteoarthritis progression: data from the Foundation for the National Institutes of Health Osteoarthritis Biomarkers Consortium. Arthritis Rheumatol. 2016;68(10):2422–31.
doi: 10.1002/art.39731 pubmed: 27111771 pmcid: 5599158
Kraus VB, 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.
doi: 10.1136/annrheumdis-2016-209252 pubmed: 27296323
Kraus VB, et al. Predictive validity of radiographic trabecular bone texture in knee osteoarthritis: the Osteoarthritis Research Society International/Foundation for the National Institutes of Health Osteoarthritis Biomarkers Consortium. Arthritis Rheumatol. 2018;70(1):80–7.
doi: 10.1002/art.40348 pubmed: 29024470
Hunter DJ, et al. Multivariable modeling of biomarker data from the phase 1 Foundation for the NIH Osteoarthritis Biomarkers Consortium. Arthritis Care Res (Hoboken). 2022;74(7):1142–53.
doi: 10.1002/acr.24557 pubmed: 33421361 pmcid: 8267050
Bauer DC, et al. Classification of osteoarthritis biomarkers: a proposed approach. Osteoarthritis Cartilage. 2006;14(8):723–7.
doi: 10.1016/j.joca.2006.04.001 pubmed: 16733093
Enrichment strategies for clinical trials to support approval of human drugs and biological products. 2016.
Almhdie-Imjabbar A, et al. Trabecular bone texture analysis of conventional radiographs in the assessment of knee osteoarthritis: review and viewpoint. Arthritis Res Ther. 2021;23(1):208.
doi: 10.1186/s13075-021-02594-9 pubmed: 34362427 pmcid: 8344203
Kraus VB, et al. Trabecular morphometry by fractal signature analysis is a novel marker of osteoarthritis progression. Arthritis Rheum. 2009;60(12):3711–22.
doi: 10.1002/art.25012 pubmed: 19950282 pmcid: 3711179
Peterfy CG, et al. Whole-organ magnetic resonance imaging score (WORMS) of the knee in osteoarthritis. Osteoarthritis Cartilage. 2004;12(3):177–90.
doi: 10.1016/j.joca.2003.11.003 pubmed: 14972335
Biswal S, et al. Risk factors for progressive cartilage loss in the knee: a longitudinal magnetic resonance imaging study in forty-three patients. Arthritis Rheum. 2002;46(11):2884–92.
doi: 10.1002/art.10573 pubmed: 12428228
Hunter D, et al. The reliability of a new scoring system for knee osteoarthritis MRI and the validity of bone marrow lesion assessment: BLOKS (Boston Leeds Osteoarthritis Knee Score). Ann Rheum Dis. 2008;67(2):206–11.
doi: 10.1136/ard.2006.066183 pubmed: 17472995
Kornaat PR, et al. MRI assessment of knee osteoarthritis: knee osteoarthritis scoring system (KOSS)--inter-observer and intra-observer reproducibility of a compartment-based scoring system. Skeletal Radiol. 2005;34(2):95–102.
doi: 10.1007/s00256-004-0828-0 pubmed: 15480649
Hunter D, Hellio Le Graverand M, Eckstein F. Radiologic markers of osteoarthritis progression. Curr Opin Rheumatol. 2009;21(2):110–7.
doi: 10.1097/BOR.0b013e3283235add pubmed: 19339920
Eckstein F, Burstein D, Link TM. Quantitative MRI of cartilage and bone: degenerative changes in osteoarthritis. [Review] [238 refs]. NMR Biomed. 2006;19(7):822–54.
doi: 10.1002/nbm.1063 pubmed: 17075958
Burgkart R, et al. Magnetic resonance imaging-based assessment of cartilage loss in severe osteoarthritis: accuracy, precision, and diagnostic value. Arthritis Rheum. 2001;44(9):2072–7.
doi: 10.1002/1529-0131(200109)44:9<2072::AID-ART357>3.0.CO;2-3 pubmed: 11592369
Graichen H, et al. Quantitative assessment of cartilage status in osteoarthritis by quantitative magnetic resonance imaging: technical validation for use in analysis of cartilage volume and further morphologic parameters. Arthritis Rheum. 2004;50(3):811–6.
doi: 10.1002/art.20191 pubmed: 15022323
Berthiaume MJ, et al. Meniscal tear and extrusion are strongly associated with progression of symptomatic knee osteoarthritis as assessed by quantitative magnetic resonance imaging. Ann Rheum Dis. 2005;64(4):556–63.
doi: 10.1136/ard.2004.023796 pubmed: 15374855
Wluka AE, et al. How does tibial cartilage volume relate to symptoms in subjects with knee osteoarthritis? Ann Rheum Dis. 2004;63(3):264–8.
doi: 10.1136/ard/2003.007666 pubmed: 14962960 pmcid: 1754924
Cicuttini FM, et al. Rate of cartilage loss at two years predicts subsequent total knee arthroplasty: a prospective study. Ann Rheum Dis. 2004;63(9):1124–7.
doi: 10.1136/ard.2004.021253 pubmed: 15115714 pmcid: 1755122
Raynauld JP, et al. Quantitative magnetic resonance imaging evaluation of knee osteoarthritis progression over two years and correlation with clinical symptoms and radiologic changes. Arthritis Rheum. 2004;50(2):476–87.
doi: 10.1002/art.20000 pubmed: 14872490
Cicuttini F, et al. Gender differences in knee cartilage volume as measured by magnetic resonance imaging. Osteoarthr Cartil 1999;7(3):265–71.
doi: 10.1053/joca.1998.0200 pubmed: 10329301
Peterfy C, et al. Quantification of articular cartilage in the knee with pulsed saturation transfer subtraction and fat-suppressed MR imaging: optimization and validation. Radiology. 1994;192(2):485–91.
doi: 10.1148/radiology.192.2.8029420 pubmed: 8029420
Kshirsagar AA, et al. Measurement of localized cartilage volume and thickness of human knee joints by computer analysis of three-dimensional magnetic resonance images. Invest Radiol. 1998;33(5):289–99.
doi: 10.1097/00004424-199805000-00006 pubmed: 9609488
Kraus VB, et al. Subchondral bone trabecular integrity predicts and changes concurrently with radiographic and magnetic resonance imaging-determined knee osteoarthritis progression. Arthritis Rheum. 2013;65(7):1812–21.
doi: 10.1002/art.37970 pubmed: 23576116 pmcid: 4152231
Janvier T, et al. Subchondral tibial bone texture analysis predicts knee osteoarthritis progression: data from the osteoarthritis initiative: tibial bone texture & knee OA progression. Osteoarthritis Cartilage. 2017;25(2):259–66.
doi: 10.1016/j.joca.2016.10.005 pubmed: 27742531
Almhdie-Imjabbar A, et al. Prediction of knee osteoarthritis progression using radiological descriptors obtained from bone texture analysis and Siamese neural networks: data from OAI and MOST cohorts. Arthritis Res Ther. 2022;24(1):66.
doi: 10.1186/s13075-022-02743-8 pubmed: 35260192 pmcid: 8903620
Kraus VB, et al. Establishment of reference intervals for osteoarthritis-related soluble biomarkers: the FNIH/OARSI OA Biomarkers Consortium. Ann Rheum Dis. 2017;76(1):179–85.
doi: 10.1136/annrheumdis-2016-209253 pubmed: 27343253
Hellio Le Graverand MP, et al. A 2-year randomised, double-blind, placebo-controlled, multicentre study of oral selective iNOS inhibitor, cindunistat (SD-6010), in patients with symptomatic osteoarthritis of the knee. Ann Rheum Dis. 2013;72(2):187–95.
doi: 10.1136/annrheumdis-2012-202239 pubmed: 23144445
Hellio Le Graverand MP, et al. Considerations when designing a disease-modifying osteoarthritis drug (DMOAD) trial using radiography. Semin Arthritis Rheum. 2013;43(1):1–8.
doi: 10.1016/j.semarthrit.2012.11.006 pubmed: 23290692
Karsdal MA, et al. Treatment of symptomatic knee osteoarthritis with oral salmon calcitonin: results from two phase 3 trials. Osteoarthritis Cartilage. 2015;23(4):532–43.
doi: 10.1016/j.joca.2014.12.019 pubmed: 25582279
Arden NK, et al. The effect of vitamin D supplementation on knee osteoarthritis, the VIDEO study: a randomised controlled trial. Osteoarthritis Cartilage. 2016;24(11):1858–66.
doi: 10.1016/j.joca.2016.05.020 pubmed: 27264058 pmcid: 5045720
Reginster JY, et al. Efficacy and safety of strontium ranelate in the treatment of knee osteoarthritis: results of a double-blind, randomised placebo-controlled trial. Ann Rheum Dis. 2013;72(2):179–86.
doi: 10.1136/annrheumdis-2012-202231 pubmed: 23117245
Fleischmann RM, et al. A phase II trial of lutikizumab, an anti-interleukin-1alpha/beta Dual variable domain immunoglobulin, in knee osteoarthritis patients with synovitis. Arthritis Rheumatol. 2019;71(7):1056–69.
doi: 10.1002/art.40840 pubmed: 30653843
Manno RL, et al. OARSI-OMERACT initiative: defining thresholds for symptomatic severity and structural changes in disease modifying osteoarthritis drug (DMOAD) clinical trials. Osteoarthritis Cartilage. 2012;20(2):93–101.
doi: 10.1016/j.joca.2011.11.013 pubmed: 22178465
Hosmer DW Jr, Lemeshow S, Sturdivant RX. Applied logistic regression, vol. 398: John Wiley & Sons; 2013.
doi: 10.1002/9781118548387
Frank E, et al. Tutorial in biostatistics multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat Med. 1996;15:361–87.
doi: 10.1002/(SICI)1097-0258(19960229)15:4<361::AID-SIM168>3.0.CO;2-4
Hastie T, et al. The elements of statistical learning: data mining, inference, and prediction, vol. 2: Springer; 2009.
doi: 10.1007/978-0-387-84858-7
Steyerberg EW, et al. Assessing the performance of prediction models: a framework for traditional and novel measures. Epidemiology. 2010;21(1):128–38.
doi: 10.1097/EDE.0b013e3181c30fb2 pubmed: 20010215 pmcid: 3575184
FDA, USA. Osteoarthritis: structural Endpoints for the Development of Drugs 2018; Available from: https://www.fda.gov/regulatory-information/search-fda-guidance-documents/osteoarthritis-structural-endpoints-development-drugs .
FDA, USA. Reviews: qualification of biomarker: clusterin (CLU), cystatin-C (CysC), kidney injury molecule-1 (KIM-1), N-acetyl-beta-D-glucosaminidase (NAG), neutrophil gelatinase-associated lipocalin (NGAL), and osteopontin (OPN). 2020; Available from: https://www.fda.gov/drugs/biomarker-qualification-program/reviews-qualification-biomarker-clusterin-clu-cystatin-c-cysc-kidney-injury-molecule-1-kim-1-n .
Abramson SB, et al. Introduction to OARSI FDA initiative OAC special edition. Osteoarthritis Cartilage. 2011;19(5):475–7.
doi: 10.1016/j.joca.2010.12.013 pubmed: 21396473
OARSI. OARSI white paper- OA as a serious disease. 2016; Available from: https://oarsi.org/education/oarsi-resources/oarsi-white-paper-oa-serious-disease .
Jordan JM, Henrotin Y. Osteoarthritis research society international initiative on recommendations for conducting clinical trials in osteoarthritis: overview. Osteoarthritis Cartilage. 2015;23(5):671–3.
doi: 10.1016/j.joca.2015.03.016 pubmed: 25952339
Foundation, Arthritis. The voice of the patient. 2017; Available from: https://www.arthritis.org/getmedia/6f33fa0d-afed-4800-9238-056460c37ae2/OA-Voice-of-the-Patient-Report.pdf .
Kraus VB, et al. Proposed study designs for approval based on a surrogate endpoint and a post-marketing confirmatory study under FDA’s accelerated approval regulations for disease modifying osteoarthritis drugs. Osteoarthritis Cartilage. 2019;27(4):571–9.
doi: 10.1016/j.joca.2018.11.002 pubmed: 30465809
Kim Y, et al. Concept end points informing design considerations for confirmatory clinical trials in osteoarthritis. Arthritis Care Res (Hoboken). 2022;74(7):1154–62.
doi: 10.1002/acr.24549 pubmed: 33345469

Auteurs

David J Hunter (DJ)

Sydney Musculoskeletal Health, Kolling Institute, Faculty of Medicine, University of Sydney, Australia and Rheumatology Department, Royal North Shore Hospital, St Leonards, NSW, 2065, Australia. David.Hunter@sydney.edu.au.

Jamie E Collins (JE)

Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.

Leticia Deveza (L)

Sydney Musculoskeletal Health, Kolling Institute, Faculty of Medicine, University of Sydney, Australia and Rheumatology Department, Royal North Shore Hospital, St Leonards, NSW, 2065, Australia.

Steven C Hoffmann (SC)

Foundation for the National Institutes of Health, Bethesda, North, MD, USA.

Virginia B Kraus (VB)

Duke Molecular Physiology Institute, and Department of Medicine|, Duke University, Durham, NC, USA.

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