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Blood Test Bests Standard OA Prognostic Models in Early Study

— Multi-marker panel does a better job of predicting who will show rapid progression

MedpageToday
A close up of a healthcare worker drawing blood from a man’s arm.

A set of 15 blood-based biomarkers outperformed conventional prediction methods for knee osteoarthritis (OA) progression in a large preliminary study, researchers said.

Based on data from 596 individuals with mild to moderate knee OA, the biomarker panel had an area under the receiver operating characteristic curve (AUC) of 73% for distinguishing those showing substantial worsening during 4 years of clinical follow-up, whereas an AUC of 59% was found for a standard model using radiographic data and pain severity at baseline, according to Virginia Byers Kraus, MD, PhD, of Duke University in Durham, North Carolina, and colleagues.

A current single-biomarker test that measures urinary carboxyl-terminal cross-linked telopeptide of type II collagen came in with an AUC of 58%, the researchers .

"In addition to being more accurate, this new biomarker has an additional advantage of being a blood-based test," Kraus said in a statement issued by Duke. "Blood is a readily accessible biospecimen, making it an important way to identify people for clinical trial enrollment and those most in need of treatment."

OA patients vary widely in rates of disease progression: when showing early signs of joint damage, some will worsen to the point of needing knee replacement in just a few years while others never reach that point.

This is especially important when designing trials of potential drug or other therapies, as enriching samples for rapid progressors reduces both the number of patients and the length of follow-up needed to determine whether a treatment is working. Reliably identifying patients at high risk for progression obviously has benefits for their individual management as well. No current prognostic model is quite that accurate.

Previous studies had tentatively identified a number of blood-based biomarkers as related to OA progression, Kraus and colleagues explained.

The cohort of 596 knee OA patients had been assembled early in the last decade, with blood samples collected at baseline. Members were followed for 48 months with x-ray measurement of joint space width and self-reported pain. At baseline, participants had Kellgren-Lawrence ratings of 1-3 (12% grade 1, 51% grade 2, and 37% grade 3), with mean pain scores of 12 on the Western Ontario-McMaster Universities Osteoarthritis Index system. About one-third of cohort members did not show pain or radiographic progression; another third showed progression for both; and about 100 each progressed for one but not the other.

Kraus and colleagues quantitatively measured more than 100 peptides derived from 64 proteins in the blood samples. Further analysis eventually narrowed these down to 15 markers, corresponding to 13 total proteins, which provided the best fit for predicting rapid progression.

Three proteins appeared particularly important for prognosis. One of these was vitamin D binding protein, which previous studies had indicated "has a multitude of functions," the researchers noted. Curiously, it doesn't seem to be expressed within the joint, yet "it nevertheless reflects processes relevant to OA pathology," Kraus and colleagues wrote. The other two proteins, CRAC1 and C1R, are produced in synovial tissue and "might be considered 'direct' biomarkers ... associated with the causal pathway," the group indicated.

The 15-marker panel was then tested in a separate cohort of 86 knee OA patients, who were followed clinically for 3-4 years for radiographic progression; 49 of these did not show substantial worsening and 37 did. In this group, the 15-marker panel yielded an AUC of 70% for predicting radiographic worsening.

Kraus and colleagues stopped short of endorsing the panel as ready for routine clinical application. Rather, they concluded, the data "provide a basis for future development of means of identifying individuals most in need of surveillance and disease modifying therapies."

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    John Gever was Managing Editor from 2014 to 2021; he is now a regular contributor.

Disclosures

The study was funded through National Institutes of Health grants. Three co-authors reported that they were listed as inventors on a patent application covering the work. Other authors declared they had no relevant financial interests.

Primary Source

Science Advances

Zhou K, et al "A 'best-in-class' systemic biomarker predictor of clinically relevant knee osteoarthritis structural and pain progression" Sci Advances 2023; DOI: 10.1126/sciadv.abq5095.