such as "Introduction", "Conclusion"..etc
July 27, 2009 — A combination of biochemical
and MRI markers will allow improved measurement of osteoarthritis (OA)
progression. The biomarkers will be useful for the design and
interpretation of trials of new disease modifying drugs.
Erik Dam, from Nordic Bioscience, Denmark, worked with a team of
researchers to develop and evaluate the markers. He said, "Presently,
there is no disease-modifying OA drug with a consistent, documented
effect despite several clinical attempts in late stage phases. We
believe that effective therapies could be demonstrated, if tools were
available that allow identification of rapid progressors for inclusion
in trials. With this in mind, we investigated whether combinations of
biochemical and MRI-based biomarkers might improve diagnosis and
prognosis of knee osteoarthritis".
Dam and his colleagues included 159 subjects in their trial. After
exclusions, a total of 287 knees were measured. At baseline and after
21 months, biochemical (urinary collagen type II C-telopeptide
fragment, CTX-II) and MRI-based markers were quantified. MRI markers
included cartilage volume, thickness, area, roughness, homogeneity, and
curvature in the medial tibio-femoral compartment. Joint space width,
the presently accepted marker for population selection in clinical
studies, was measured from radiographs. According to Dam, "The best
individual diagnostic marker was cartilage roughness and the best
individual prognostic marker was homogeneity. The aggregate cartilage
longevity marker (combining CTX-II, volume, area, thickness, congruity,
roughness, and homogeneity) performed very well both diagnostically and
prognostically – and superior to the individual biochemical and MRI
markers. We attribute this to the combination of markers with
complementary information about cartilage quantity (e.g. volume),
quality (e.g. homogeneity), and breakdown (CTX-II) that together allow
The proposed aggregate marker methodology may have a direct impact
on the design of clinical studies. The researchers claim, "By allowing
the selection of a high risk population, the study sample size can be
lowered while still improving the chance of a positive study outcome.
This should facilitate the development of effective drugs".
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