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Predictive validity of biochemical biomarkers in knee osteoarthritis: data from the FNIH OA Biomarkers Consortium
  1. Virginia Byers Kraus1,
  2. Jamie E Collins2,
  3. David Hargrove3,
  4. Elena Losina2,
  5. Michael Nevitt4,
  6. Jeffrey N Katz4,
  7. Susanne X Wang5,
  8. Linda J Sandell6,
  9. Steven C Hoffmann7,
  10. David J Hunter8
  11. for the OA Biomarkers Consortium
  1. 1Duke Molecular Physiology Institute and Division of Rheumatology, Duke University School of Medicine, Durham, North Carolina, USA
  2. 2Brigham and Women's Hospital, Boston, Massachusetts, USA
  3. 3LabCorp Clinical Trials, San Leandro, California, USA
  4. 4Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California, USA
  5. 5AbbVie, North Chicago, Illinois, USA
  6. 6Department of Orthopaedic Surgery, Musculoskeletal Research Center, Washington University in St. Louis, St Louis, Missouri, USA
  7. 7Foundation for the National Institutes of Health, Bethesda, Maryland, USA
  8. 8Rheumatology Department, Royal North Shore Hospital and Institute of Bone and Joint Research, Kolling Institute, University of Sydney, Sydney, New South Wales, Australia
  1. Correspondence to Dr Virginia Byers Kraus, Box 104775, Duke Molecular Physiology Institute, 300 North Duke St, Durham, NC 27701, USA; vbk{at}


Objective To investigate a targeted set of biochemical biomarkers as predictors of clinically relevant osteoarthritis (OA) progression.

Methods Eighteen biomarkers were measured at baseline, 12 months (M) and 24 M in serum (s) and/or urine (u) of cases (n=194) from the OA initiative cohort with knee OA and radiographic and persistent pain worsening from 24 to 48 M and controls (n=406) not meeting both end point criteria. Primary analyses used multivariable regression models to evaluate the association between biomarkers (baseline and time-integrated concentrations (TICs) over 12 and 24 M, transposed to z values) and case status, adjusted for age, sex, body mass index, race, baseline radiographic joint space width, Kellgren-Lawrence grade, pain and pain medication use. For biomarkers with adjusted p<0.1, the c-statistic (area under the curve (AUC)), net reclassification index and the integrated discrimination improvement index were used to further select for hierarchical multivariable discriminative analysis and to determine the most predictive and parsimonious model.

Results The 24 M TIC of eight biomarkers significantly predicted case status (ORs per 1 SD change in biomarker): sCTXI 1.28, sHA 1.22, sNTXI 1.25, uC2C-HUSA 1.27, uCTXII, 1.37, uNTXI 1.29, uCTXIα 1.32, uCTXIβ 1.27. 24 M TIC of uCTXII (1.47–1.72) and uC2C-Human Urine Sandwich Assay (HUSA) (1.36–1.50) both predicted individual group status (pain worsening, joint space loss and their combination). The most predictive and parsimonious combinatorial model for case status consisted of 24 M TIC uCTXII, sHA and sNTXI (AUC 0.667 adjusted). Baseline uCTXII and uCTXIα both significantly predicted case status (OR 1.29 and 1.20, respectively).

Conclusions Several systemic candidate biomarkers hold promise as predictors of pain and structural worsening of OA.

  • Knee Osteoarthritis
  • Osteoarthritis
  • Disease Activity

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  • Handling editor Tore K Kvien

  • Correction notice This article has been corrected since it was published Online First. Text changes have been made to the first paragraph of the section ‘Biomarker assays.’ In tables 1,3 and 4 ‘serum C2C-HUSA’ has been corrected to ‘serum-C2C (ng/ml)’ and ‘Urine C2C-HUSA HUSA (ng/mmol Cr)’ has been corrected to ‘Urine C2C-HUSA (ng/mmol Cr).’

  • Twitter Follow David Hunter at @ProfDavidHunter

  • Contributors Study conception and design: VBK, DJH, MN, JEC, EL, JNK, EL and LJS. Acquisition of data: DH and MN. Analysis and interpretation of data: All authors. Writing of first manuscript draft: VBK. Critical manuscript revision and approval of final manuscript: All authors. JC had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

  • Funding In-kind donations to support biochemical testing was provided by Alere, ARTIALIS S.A., BioVendor—Laboratorni medicina a.s., IBEX Pharmaceuticals, Immunodiagnostic Systems and Quidel Corporation. Scientific and financial support for the Foundations for National Institutes of Health (FNIH) OA Biomarkers Consortium and the study are made possible through grants, direct and in-kind contributions provided by: AbbVie, Amgen, Arthritis Foundation, Bioiberica S.A., DePuy Mitek, Flexion Therapeutics, GlaxoSmithKline, Merck Serono, Rottapharm | Madaus, Sanofi, Stryker, The Pivotal OAI MRI Analyses study, NIH NHLBI HHSN2682010000. We thank the Osteoarthritis Research Society International for their leadership and expertise on the FNIH OA Biomarker Consortium project. The osteoarthritis initiative (OAI) is a public-private partnership comprising five contracts (N01-AR-2-2258, N01-AR-2-2259, N01-AR-2-2260, N01-AR-2-2261 and N01-AR-2-2262) funded by the National Institutes of Health. Funding partners include Merck Research Laboratories, Novartis Pharmaceuticals Corporation, GlaxoSmithKline and Pfizer. Private sector funding for the Consortium and OAI is managed by the FNIH. The statistical analysis and writing of this article was independent from and not contingent upon approval from the study sponsors or kit suppliers.

  • Competing interests None declared.

  • Ethics approval University of California, San Francisco and all sites participating in the osteoarthritis initiative study.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data sharing statement All the data are made publically available for additional analyses and for comparison to other biomarkers that any researcher might do upon requesting the same sample set from the Biochemical Research Committee of the Osteoarthritis Initiative.

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