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Abstract Number: 1373

Predictive Probabilities Are Superior in Communicating the Clinical Relevance of Cartilage Thickness As an Imaging Biomarker of Knee Osteoarthritis Progression

C. Kent Kwoh1,2, Erin L. Ashbeck1, Edward J. Bedrick3 and Felix Eckstein4,5, 1University of Arizona Arthritis Center, Tucson, AZ, 2Division of Rheumatology, Department of Medicine, The University of Arizona, Tucson, AZ, 3Department of Epidemiology and Biostatistics, University of Arizona, Tucson, AZ, 4Institute of Anatomy, Paracelsus Medical University, Salzburg, Austria, 5Chondrometrics GmbH, Ainring, Germany

Meeting: 2018 ACR/ARHP Annual Meeting

Keywords: biomarkers and cartilage, Joint replacement, Knee, MRI

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Session Information

Date: Monday, October 22, 2018

Title: Osteoarthritis – Clinical Poster II

Session Type: ACR Poster Session B

Session Time: 9:00AM-11:00AM

Background/Purpose: Establishing a threshold of clinically important cartilage loss is of great interest for the design and interpretation of knee OA trials of structure-modifying treatments. Our objective was to obtain predictive probabilities of knee replacement (KR) based on the combination of femorotibial joint (FTJ) cartilage thickness (CtTh) loss over 2 years, and CtTh at baseline.

Methods: Knees with symptomatic OA, defined by definite osteophyte (OARSI atlas grade 1-3) and participant-reported frequent knee symptoms at baseline, were selected prospectively from the Osteoarthritis Initiative (Project 09B). FTJ cartilage thickness at baseline and year 2 were measured quantitatively with MRI (3T; sagittal DESS sequence) and calculated as total  femorotibial cartilage volume divided by the cartilage surface area. KRs reported up to 7 years following the 2-year imaging window were self-reported and confirmed. We used a Bayesian discrete time logistic survival model with intercepts (αk) for each year of follow-up: logit[pk(x)] = αk + β′x. Diffuse reference prior distributions for the model parameters, αk, βj ~ N(0, 104) were specified. Posterior densities of the regression coefficients were estimated with 10,000 Markov Chain Monte Carlo samples generated with the R package R2OpenBUGS. Models were compared using deviance information criteria. Sensitivity of the results to the prior specification was considered. 

Results: Among 582 knees (one knee per participant), 95 underwent KR up to 7 years following the initial 2-year imaging window (median follow-up 6 years). Mean baseline CtTh was 1.85 mm (SD 0.29), while mean CtTh loss over 2 years was 0.04 mm (SD 0.07). Greater CtTh at baseline (standardized) was associated with lower odds of KR (OR=0.73 [95% credible interval (CI): 0.59, 0.90]; Pr(OR<1 | data) = 0.9995). Greater 2-year loss of CtTh (standardized) was associated with higher odds of KR (OR=1.71 [95%CI: 1.41, 2.05]; Pr(OR>1| data) =1.0). The figure presents three representative curves of predictive probabilities of KR as a function of 2-year CtTh loss corresponding to three baseline CtTh values. For example, a knee with baseline CtTh of 1.85 mm and 2 year loss of 0.17 mm has a probability of KR within 5 years of 0.27. A knee with less baseline CtTh, 1.56 mm (-1SD), has a probability of KR of 0.34 with the same measured loss, while a knee with greater CtTh at baseline, 2.14 mm (+1SD), has probability of KR of 0.20.

Conclusion: The same rate of 2-year FTJ cartilage thickness loss has varying predictive probability of future KR, depending on the baseline cartilage thickness, highlighting the difficulty of defining minimum clinically important differences in a tissue that eventually disappears entirely at the end-stage disease process. Predictive probabilities of clinically relevant outcomes provide a more interpretable way to communicate the clinical relevance of imaging biomarkers beyond traditionally reported odds ratios.


Disclosure: C. K. Kwoh, EMD Serono, 2, 5; E. L. Ashbeck, EMD Serono, 5; E. J. Bedrick, None; F. Eckstein, None.

To cite this abstract in AMA style:

Kwoh CK, Ashbeck EL, Bedrick EJ, Eckstein F. Predictive Probabilities Are Superior in Communicating the Clinical Relevance of Cartilage Thickness As an Imaging Biomarker of Knee Osteoarthritis Progression [abstract]. Arthritis Rheumatol. 2018; 70 (suppl 9). https://acrabstracts.org/abstract/predictive-probabilities-are-superior-in-communicating-the-clinical-relevance-of-cartilage-thickness-as-an-imaging-biomarker-of-knee-osteoarthritis-progression/. Accessed .
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