M. Nevitt

Evaluation of the Usefulness of Consensus Definitions of Sarcopenia in Older Men: Results from the Observational Osteoporotic Fractures in Men Cohort Study.

To evaluate the associations between definitions of sarcopenia and clinical outcomes and the ability of the definitions to discriminate those with a high likelihood of having these outcomes from those with a low likelihood.

Accelerometer-monitored sedentary behavior and observed physical function loss.

OBJECTIVES We examined whether objectively measured sedentary behavior is related to subsequent functional loss among community-dwelling adults with or at high risk for knee osteoarthritis. METHODS We analyzed longitudinal data (2008-2012) from 1659 Osteoarthritis Initiative participants aged 49 to 83 years in 4 cities. Baseline sedentary time was assessed by accelerometer monitoring. Functional loss (gait speed and chair stand testing) was regressed on baseline sedentary time and covariates (baseline function; socioeconomics [age, gender, race/ethnicity, income, education], health factors [obesity, depression, comorbidities, knee symptoms, knee osteoarthritis severity, prior knee injury, other lower extremity pain, smoking], and moderate-to-vigorous activity). RESULTS This cohort spent almost two thirds of their waking hours (average=9.8 h) in sedentary behaviors. Sedentary time was significantly positively associated with subsequent functional loss in both gait speed (-1.66 ft/min decrease per 10% increment sedentary percentage waking hours) and chair stand rate (-0.75 repetitions/min decrease), controlling for covariates. CONCLUSIONS Being less sedentary was related to less future decline in function, independent of time spent in moderate-to-vigorous activity. Both limiting sedentary activities and promoting physical activity in adults with knee osteoarthritis may be important in maintaining function.

397 CARTILAGE LOSS OCCURS IN THE SAME SUBREGIONS AS SUBCHONDRAL BONE ATTRITION: THE MOST STUDY

only a slight and not significant increase from deep to superficial cartilage (T2: p = 0.174; T2*: p = 0.150). Conclusions: In vivo T1 dGEMRIC assessment in healthy cartilage, as well as T2 and T2* mapping in healthy and reparative articular cartilage, seems to be possible at 7.0T MRI. For T2 and T2*, zonal variation of articular cartilage could also be evaluated at 7.0T. This zonal assessment of deep and superficial cartilage aspects shows promising results for the differentiation of healthy and affected articular cartilage. In future studies, optimized protocol selection and sophisticated coil technology, together with increased signal at ultra-high-field MRI, may lead to advanced biochemical cartilage imaging. Concluding, the next step to a potential clinical applicability of ultrahigh field MRI in biochemical cartilage evaluation in the follow-up of sophisticated surgical and non-surgical therapies of cartilage defects and osteoarthritis might not be so far away.

329 REVERSIBLE MRI FEATURES AND FLUCTUATION OF KNEE PAIN SEVERITY

K/L Grade K/L = 0 1.0 (ref) 1.0 (ref) K/L = 1 1.5 (0.9−2.3) 2.3 (0.9−5.8) K/L = 2 3.9 (2.4−6.5) 3.1 (1.3−7.4) K/L = 3 9.0 (5.2−15.6) 17.0 (5.6−51.9) K/L = 4 150.7 (43.1–526.4) 47.1 (9.9–225.6) P for trend P< 0.0001 P< 0.0001 Max OST & Max JSN (mutually adjusted for one another) OST=0 1.0 (ref) 1.0 (ref) OST=1 1.2 (0.8−1.8) 1.9 (0.9−4.1) OST=2 2.0 (1.1−3.7) 2.7 (0.9−7.8) OST=3 2.0 (1.0−4.2) 5.0 (1.3−19.1) P for trend P=0.07 P=0.04 JSN=0 1.0 (ref) 1.0 (ref) JSN=1 2.4 (1.5−3.8) 1.4 (0.6−3.6) JSN=2 5.4 (2.9−10.0) 5.4 (1.6−18.7) JSN=3 96.7 (26.4–353.9) 12.5 (2.3−67.3) P for trend P< 0.0001 P=0.0005

Harmonising measures of knee and hip osteoarthritis in population-based cohort studies: an international study

OBJECTIVE Population-based osteoarthritis (OA) cohorts provide vital data on risk factors and outcomes of OA, however the methods to define OA vary between cohorts. We aimed to provide recommendations for combining knee and hip OA data in extant and future population cohort studies, in order to facilitate informative individual participant level analyses. METHOD International OA experts met to make recommendations on: 1) defining OA by X-ray and/or pain; 2) compare The National Health and Nutrition Examination Survey (NHANES)-type OA pain questions; 3) the comparability of the Western Ontario & McMaster Universities Osteoarthritis Index (WOMAC) scale to NHANES-type OA pain questions; 4) the best radiographic scoring method; 5) the usefulness of other OA outcome measures. Key issues were explored using new analyses in two population-based OA cohorts (Multicenter Osteoarthritis Study; MOST and Osteoarthritis Initiative OAI). RESULTS OA should be defined by both symptoms and radiographs, with symptoms alone as a secondary definition. Kellgren and Lawrence (K/L) grade ≥2 should be used to define radiographic OA (ROA). The variable wording of pain questions can result in varying prevalence between 41.0% and 75.4%, however questions where the time anchor is similar have high sensitivity and specificity (91.2% and 89.9% respectively). A threshold of 3 on a 0-20 scale (95% CI 2.1, 3.9) in the WOMAC pain subscale demonstrated equivalence with the preferred NHANES-type question. CONCLUSION This research provides recommendations, based on expert agreement, for harmonising and combining OA data in existing and future population-based cohorts.

THU0195 Semiquantitatively Assessed Bone Marrow Lesions, Cartilage Damage, Meniscal Damage and Extrusion PREDICT Quantitatively Measured Cartilage Thickness Loss in the Same Femorotibial Compartment: the Most Study

Background Studies have shown associations of structural progression of knee OA with several MRI-assessed pathologic features such as bone marrow lesions (BMLs) cartilage damage and meniscal lesions1,2. However previous studies commonly evaluated one risk factor at a time and not in a combination simultaneously, though these features are known to partly coexist. Objectives To determine which radiographic and semiquantitative MRI-based OA features predict cartilage thickness loss in the same femorotibial compartment (FTC). Methods One knee of each subject of a subcohort of Multicenter OA Study (MOST) was evaluated. The subcohort comprised persons who volunteered for a longitudinal study, in which quantitative MRI-based cartilage thickness was done. These subjects also had MRI for semiquantitative Whole Organ MRI Score based evaluation of BMLs, cartilage damage, meniscal damage and extrusion, Hoffa-synovitis and effusion-synovitis, at baseline and at 30-month. Progression in medial or lateral FTC (MFTC/LFTC) was defined as cartilage thinning exceeding the change observed in OAI control cohort knees (mean ± 2xSD, MFTC/LFTC: -162μm/-145μm). All MRI predictors were dichotomized into present/absent. Differences in baseline scores of predictor variables in the same FTC were compared between progressor and nonprogressor knees using multivariable logistic regression adjusting for age, sex, BMI and alignment axis. We combined MFTC and LFTC to calculate adjusted odds ratio (aOR) and 95% CI of cartilage thickness loss across compartments (ie. medial cartilage thinning with medial risk factors and lateral cartilage thinning with lateral risk factors) using GEE. ORs and 95%CIs were also calculated for MFTC and LFTC cartilage thickness loss, individually. Results 196 persons with mean age 59.8±6.3 years, mean BMI 29.5±4.6 and 62% women were included. 46 knees had baseline radiographic knee OA (KL grade≥2). In the MFTC/LFTC, 35/29 progressors and 161/167 nonprogressors were observed, respectively. Change in MFTC cartilage thickness was -63.0μm and that in LFTC cartilage thickness -25.1μm. For combined MFTC+LFTC analysis, predictors of cartilage thinning were baseline BML (aOR 1.9 95%CI [1.1-3.3]), cartilage damage (2.6 [1.4-5.0]), meniscal damages (4.5 [2.4-8.4]) and meniscal extrusion (3.3 [1.9-5.8]), all in the same FTC. Hoffa- and effusion-synovitis did not predict cartilage thinning. In MFTC-only analysis MFTC progressors showed higher aOR for having baseline meniscal damage (2.4 [1.1-5.6]) and meniscal extrusion (2.6 [1.1-5.8]). In LFTC-only analysis baseline cartilage damage (3.4 [1.3-9.3]), meniscal damage (13.9 [3.3-9.0]) and meniscal extrusion (5.0 [1.4-18.0]) predicted LFTC progression. Conclusions The presence of semiquantitatively assessed BMLs, cartilage damage, meniscal damage and extrusion in the same FTC predict cartilage thickness loss over 30-months. References Roemer et al. Arthritis Rheum 2012;64:1888-98. Crema et al. Osteoarthritis Cartilage 2010;18:336-43. Disclosure of Interest : A. Guermazi Shareholder of: Boston Imaging Core Lab, LLC, Consultant for: Merck Serono, TissueGene, Sanofi Aventis, F. Eckstein Shareholder of: Chondrometrics GmbH, Consultant for: MerckSerono and Abbvie, D. Hayashi: None declared, F. Roemer Shareholder of: Boston Imaging Core Lab, LLC, Consultant for: Merck Serono and the NIH, W. Wirth Shareholder of: Chondrometrics, GmbH, T. Yang: None declared, J. Niu: None declared, L. Sharma: None declared, M. Nevitt: None declared, C. Lewis: None declared, J. Torner: None declared, D. Felson: None declared DOI 10.1136/annrheumdis-2014-eular.2558

SAT0319 Prediction models for progression of knee osteoarthritis in the multicenter osteoarthritis study (MOST)

Background Although individual risk factors for incident and progressive knee osteoarthritis (OA) have been identified, less is known about models to predict progression of knee OA. Objectives A prospective cohort study was conducted to identify predictors for progression of radiographic knee OA over 30 months. Methods The NIH-funded Multicenter Osteoarthritis Study (MOST) is an observational study of 3026 persons age 50 to 79 years with either symptomatic knee OA or at high risk of disease. Weight-bearing, fixed flexion, in-frame posterior-anterior knee radiographs were taken at baseline and 30-month follow-up clinic visits between 2003 and 2007. Knees were included with Kellgren/Lawrence (K/L) grades of 2 or 3 at baseline. Two outcome definitions were prespecified: (1) progression to K/L grade 3 or 4 over 30 months, or incident first knee replacement (KR); (2) tibiofemoral joint space narrowing (JSN) progression by 1 grade or more, or incident first KR. Fourteen potential predictors were considered for inclusion: body mass index (BMI), height, weight, race (white vs non-white), education (partial graduate/graduate, partial college or college, vs. high school or below), occupation (labor vs. non-labor vs. other), Western Ontario McMaster (WOMAC) knee pain subscale, WOMAC function subscale, baseline K/L grade or baseline maximal tibiofemoral JSN score, malalignment (varus vs. valgus vs. neutral), history of knee injury, depressive symptoms. Additionally, age and sex were forced into all models. We used a 10-fold cross-validation procedure to select logistic regression models using as criteria: (1) higher area under curve (AUC) measured as c-statistics; (2) higher positive predictive value (PPV). Results 1603 knees without missing data in any outcome or predictor parameters were included in this analysis. The best model to predict K/L progression based on AUC included age, sex, race, malalignment and WOMAC pain (c-statistic 0.59). The best model for K/L progression based on PPV using cut point of 0.25 included age, sex, BMI, weight and weight squared, and WOMAC pain (PPV 0.32). The best model to predict JSN progression based on AUC included age, sex, race, malalignment, WOMAC pain, and baseline maximal JSN score (c-statistic 0.55). The best model to predict JSN progression based on maximizing PPV at a cut point of 0.25 included age, sex, BMI, race, occupation, depression, WOMAC pain and WOMAC function (PPV=0.36). Conclusions Models including known risk factors have moderate power to predict progression of radiographic knee OA over a 30 month period. Disclosure of Interest B. Wise Grant/Research support from: Pfizer, Inc., Y. Zhang Grant/Research support from: Pfizer, Inc., N. Lane: None Declared, C. McCulloch: None Declared, D. Felson: None Declared, M. Nevitt: None Declared, J. Torner: None Declared, C. Lewis: None Declared, A. Sadosky Employee of: Pfizer, Inc., J. Niu Grant/Research support from: Pfizer, Inc.

371 MRI-BASED CARTILAGE THICKNESS LOSS AND JOINT SPACE NARROWING IN AN OAI CORE PROGRESSION SAMPLE, AND THEIR RELATIONSHIP WITH AGE, SEX, AND BMI

Purpose: Recent evidence suggests that peri-articular bone changes are integral to knee osteoarthritis (OA) pathophysiology. Peri-articular trabecular morphology changes have been associated with radiographic knee OA severity and may identify individuals at risk for knee OA progression. However, it is unclear how patient characteristics are associated with peri-articular trabecular morphology in knees with OA. The purpose of this study was to evaluate the association between patient characteristics and trabecular morphology in knees with OA. Methods: The sample comprised a convenience sample of 337 participants in the Osteoarthritis Initiative (OAI) progression cohort who at the 30or 36-month OAI visit had 3-tesla magnetic resonance imaging that included coronal 3D Fast Imaging with Steady State Precession (FISP) trabecular morphometry sequences. We used a trabecular morphometry program with a modified algorithm (calcDCN, University of CaliforniaSan Francisco) to evaluate 4 peri-articular trabecular morphology measures: bone volume fraction (BVF), trabecular number (tb.n), spacing (tb.sp), and thickness (tb.th). The four measures were calculated for 20 consecutive central slices within a 15mm x 3.75mm region of interest placed in the peri-articular medial tibia and then averaged. Intratester reproducibility was high (ICC = 0.99). The association between demographic data or knee-specific data (from the 24-month OAI visit) and trabecular morphometry were evaluated with independent sample t-tests or Wilcoxon rank-sum tests (when applicable) and Spearman correlations. Among a subset of 285 patients with 24-month joint space narrowing (JSN) scores, four forward-selection multiple linear regression models were used to further evaluate the associations between patient characteristics and each trabecular morphometry measure. Results: Participants were 66±9 years of age, body mass index 29.6±4.8 kg/m, and 50% female. Peri-articular trabecular morphometry was averaged (± standard deviation) for the cohort: BVF = 0.12±0.08, tb.sp = 1.53±1.25mm, tb.n = 0.86±0.39mm−1, and tb.th = 0.13±0.03mm. Peri-articular trabecular morphometry was not significantly different (p > 0.05) between participants with or without college degrees (n = 208, n = 127; respectively), with or without history of smoking (n =147, n = 188; respectively), and with or without knee symptoms at the 24month OAI visit (n = 191, n = 145; respectively). Many variables were associated with trabecular morphometry (see table). Age correlated with BVF (r = −0.16), tb.n (r = −0.18), and tb.sp (r = 0.17), but not tb.th (r = −0.08). Body mass index also correlated with BVF (r = 0.12), tb.n (r = 0.14), and tb.sp (r = −0.14), but not tb.th (r = 0.07). The 400-meter walk time (24-month visit) was related to tb.sp (r = 0.12). In multiple linear regression models, the presence of medial JSN and female gender were associated with all 4 trabecular morphometry measures. Three patient characteristics were associated with select measures: age (associated with tb.sp, tb.n), history of knee injury/surgery (associated with BVF, tb.th), and race (associated with tb.th).

380 CARTILAGE THICKNESS, DENUDED AREAS, AND BONE SIZE IN KNEES PRIOR TO TOTAL KNEE REPLACEMENT (TKR) – DATA FROM THE OSTEOARTHRITIS INITIATIVE

380 CARTILAGE THICKNESS, DENUDED AREAS, AND BONE SIZE IN KNEES PRIOR TO TOTAL KNEE REPLACEMENT (TKR) – DATA FROM THE OSTEOARTHRITIS INITIATIVE F. Eckstein, C.K. Kwoh, R. Boudreau, Z. Wang, M.J. Hannon, S. Cotofana, M. Hudelmaier, W. Wirth, A. Guermazi, M. Nevitt, M.R. John, D.J. Hunter, for the OAI investigators. Paracelsus Med. Univ. & Chondrometrics GmbH, Salzburg, Austria; Div. of Rheumatology and Clinical Immunology, Univ. of Pittsburgh and Pittsburgh VAHS, Pittsburgh, PA, USA; Dept. of Epidemiology, Grad. Sch. of Publ. Hlth., Univ. of Pittsburgh, Pittsburgh, PA, USA; BICL Inc. & Boston Univ., Boston, MA, USA; OAI Coordinating Ctr., UCSF, San Francisco, CA, USA; Novartis Pharma AG, Basel, Switzerland; Royal North Shore Hosp. & Northern Clinical Sch., Univ. Sydney, Sydney, Australia

404 DIRECT COMPARISION OF ONE- AND TWO-YEAR SENSITIVITY TO CHANGE OF FIXED FLEXION RADIOGRAPHY VERSUS SUBREGIONAL MRI CARTILAGE MORPHOLOGY: DATA FROM THE OSTEOARTHRITIS IN1TATIVE

Purpose: To overcome challenges of the spatial heterogeneity of MRI-based subregional cartilage loss in OA, an ordered value (OV) approach was proposed. This approach ranks subregional cartilage thickness changes in each knee according to magnitude, assigning the region with the greatest cartilage loss to OV1, the one with the 2nd greatest loss to OV2, and the one with the smallest loss or largest increase in thickness to OV16. The approach includes 8 medial and 8 lateral femorotibial subregions and was shown to be effective in differentiating rates of cartilage loss in OA knees with and without JSN. Here we explore, by simulation, to what extent the OV approach is superior in identifying potential effects of a DMOAD on structural progression in OA. Methods: 610 knees with radiographic OA (300 with JSN; 310 without) from the Osteoarthritis Initiative were analyzed at baseline and 12 month follow-up (public use data sets 0.E.1, 1.E.1, 0.2.2). The knees were randomized into two equally sized groups. The following simulations were performed: A) all negative subregional changes (thickness loss) were reduced in the treatment group, B) all positive changes (thickening; swelling or hypertrophy) were reduced, C) both types of changes were reduced, assuming a 25% reduction by a DMOAD. For each of the three simulation types, the following models were run 1) homogeneous reduction of 25% in each subregion in the treatment group; 2) random reductions between 0% and 50% (mean=25%, SD=12.5%) across knees, but the same value in all subregions of each knee; 3) random reductions between 0% and 50% (mean 25%; SD=12.5%) across different subregions and knees. Effects were reported when consistent results were obtained for simulating the DMOAD effect in each of the randomized subcohorts versus the other (as a placebo [Mann-Whitney-U test; p<0.01]). Results: Running simulations A-C and models 1-3, significant treatment effects were occasionally observed in cartilage compartments, plates and subregions, but in no case these were consistent when simulating treatment effects in the other randomized subcohort. In contrast, OV1 revealed consistent significant differences in the treated vs. placebo group (p for OV1 between 4.4×10-7 and 1.1×10-11), and OV1-5 displayed significant results in all models, independent of whether the treatment was simulated for one or the other randomized subcohort. This also applied when simulating a DMOAD reducing cartilage thickening, with OV16 displaying treatmentrelated p-values of 1.5×10-8 to 7.7×10-12, and with OV13-16 displaying consistent significance across all models. Simulation of a DMOAD stabilizing cartilage generated p-values for treatment effects between 1.2×10-6 and 9.2×10-11 in OV1, and values of 3.3×10-096 to 4.0×10-11 in OV16, independent of which randomized subcohort was used. Conclusion: Limitations of the study are that subregional changes are partly due to precision error, and that it is unknown to what extent DMOADs can reduce (subregional) cartilage thinning or thickening. Therefore, a conservative DMOAD effect of only 25% was applied. A strength of the approach was that the simulation accounted for potential variability of treatment effects between knees and regions, and that the simulation was based on actual measurements of (subregional) cartilage change in OAI participants. Therefore, the principal observations should hold, even if the actual magnitude of the effect of a DMOAD was larger or smaller. The results suggest that a) the OV approach is more effective in detecting DMOAD effects than the conventional approach, b) that, unlike conventional approaches, it is capable of capturing effects of a drug stabilizing cartilage (i.e. reducing both loss and thickening), and c) that the OV approach is less sensitive to randomization effects than region based analysis of cartilage loss. These results will have to be confirmed empirically; the current simulation, however, suggests that ordered values (OVs) of subregional cartilage change in MRI are a potentially very powerful tool for detecting drug effects on structural progression in OA. 404