Identifying Phenotypes of Knee Osteoarthritis by Separate Quantitative Radiographic Features May Improve Patient Selection for More Targeted Treatment
From the Department of Rheumatology and Clinical Immunology, University Medical Center Utrecht, Utrecht The Journal of Rheumatology
(Impact Factor: 3.19).
05/2013; 40(6). DOI: 10.3899/jrheum.121004
Expression of osteoarthritis (OA) varies significantly between individuals, and over time, suggesting the existence of different phenotypes, possibly with specific etiology and targets for treatment. Our objective was to identify phenotypes of progression of radiographic knee OA using separate quantitative features.
Separate radiographic features of OA were measured by Knee Images Digital Analysis (KIDA) in individuals with early knee OA (the CHECK cohort: Cohort Hip & Cohort Knee), at baseline and at 2-year and 5-year followup. Hierarchical clustering was performed to identify phenotypes of radiographic knee OA progression. The phenotypes identified were compared for changes in joint space width (JSW), varus angle, osteophyte area, eminence height, bone density, for Kellgren-Lawrence (K-L) grade, and for clinical characteristics. Logistic regression analysis evaluated whether baseline radiographic features and demographic/clinical characteristics were associated with each of the specific phenotypes.
The 5 clusters identified were interpreted as "Severe" or "No," "Early" or "Late" progression of the radiographic features, or specific involvement of "Bone density." Medial JSW, varus angle, osteophyte area, eminence height, and bone density at baseline were associated with the Severe and Bone density phenotypes. Lesser eminence height and bone density were associated with Early and Late progression. Larger varus angle and smaller osteophyte area were associated with No progression.
Five phenotypes of radiographic progression of early knee OA were identified using separate quantitative features, which were associated with baseline radiographic features. Such phenotypes might require specific treatment and represent relevant subgroups for clinical trials.
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ABSTRACT: In 2010, in Osteoarthritis and Cartilage, we published a comprehensive systematic review applying the consensus BIPED criteria on serum and urinary biochemical markers for knee and hip osteoarthritis (OA) using publications that were available at that time. It appeared that none of the biochemical markers at that time were sufficiently discriminating to allow diagnosis and prognosis of osteoarthritis in individual or limited numbers of patients, nor performed so consistently that they could function as primary outcome parameters in clinical trials. Also at present, almost 3 years later, this ultimate goal has not been reached (yet). Frankly, it might be questioned whether we are making the most adequate steps ahead and maybe we have to take a step back to reconsider our approaches. Some reflections are made and discussed: A critical review of molecular metabolism in osteoarthritis and validation of currently investigated marker molecules in this may be vital and may lead to new and better markers. Creating cohorts in which synovial fluid is obtained in a systematic way, together with serum and urine, may also bring the field a further step ahead. Thirdly, better understanding of different phenotypes (subtypes) of OA may facilitate identification and validation of biochemical markers. Finally, the systems biology approach as discussed in the last years OA in review on biomarkers, although very complex, might provide steps forward. Looking ahead, we are optimistic but realistic in our expectations, we believe that the field can be brought forward by critically and cautiously reconsidering our approaches, and making changes forward, one step at a time.
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ABSTRACT: Osteoarthritis (OA) is a complex disease characterized by cartilage degeneration, secondary synovial membrane inflammation and subchondral bone changes. In recent years, many studies have confirmed that interleukin-18 (IL-18) is involved in the inflammatory process of inflammatory joint diseases. In the present study, we investigated IL-18 levels in plasma, synovial fluid and articular cartilage of patients with primary knee OA (n = 33) to analyze their relationship with radiographic severity. Compared to healthy controls (n = 15), OA patients had higher plasma and synovial fluid IL-18 concentrations (45.8 ± 22.1 vs. 23.7 ± 13.6 pg/ml, P < 0.001 and 75.2 ± 40.1 vs. 28.3 ± 11.6 pg/ml, P < 0.001) as measured by enzyme-linked immunosorbent assay. Also, the percentage of immunofluorescent IL-18 positive cells in articular cartilage was significantly increased in OA compared to controls (46.5 ± 10.3 vs. 2.9 ± 1.7, P < 0.001). Moreover, plasma, synovial fluid and articular cartilage IL-18 significantly positively correlated with radiographic severity, respectively (r = 0.663, P < 0.001, r = 0.56, P = 0.001 and r = 0.884, P < 0.001). Subsequent analysis revealed that plasma, synovial fluid and articular cartilage IL-18 levels positively correlated with each other (r = 0.632, P < 0.001, r = 0.489, P = 0.004 and r = 0.620, P < 0.001). These data suggested that plasma, synovial fluid and articular cartilage IL-18 levels were significantly increased in OA patients, and these elevated levels were positively correlated with radiographic severity. Accordingly, our study supports the role of IL-18 in the pathophysiology of OA.
Available from: Virginia B Kraus
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ABSTRACT: For both economic and ethical reasons, identification of the optimal treatment for each individual patient is a pressing concern, not only for the patients and their physician, but also healthcare payers and the pharmaceutical industry. In the field of osteoarthritis (OA) this is of particular relevance, due to the heterogeneity of the disease and the very large number of affected individuals. There is a need to pair the right patients with the right therapeutic modes of action. At present, the clinical trial failures in osteoarthritis may be a consequence of both bona fide treatment failures and trial failures due to clinical design deficiencies. Tools are needed for characterization and segregation of patients with OA. Key lessons may be learned from advances with another form of arthritis, namely Rheumatoid Arthritis (RA). Personalized health care (PHC) may be more advantageous for a number of specific indications which are characterized by costly therapy, low response rates and significant problems associated with trial and error prescription, including the risk of serious side effects. We discuss the use of diagnostic practices guiding RA treatment, which may serve as a source of key insights for diagnostic practices in OA. We discuss the emerging concept of PHC, and outline the opportunities and current successes and failures across the RA field, as the OA field collects further data to support the hypothesis. We attempt to outline a possible path forward to assist patients, physicians, payers and the pharmaceutical industry in assuring the 'right' patients are treated with the 'right drug' in OA. Finally we highlight methods for possible segregation of OA patients that would allow identification of patient subtypes, such as OA driven by inflammation that may be ideally suited for PHC and for targeted therapies.
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