F Eymard1, C Parsons2, M H Edwards2, F Petit-Dop3, J-Y Reginster4, O Bruyère4, P Richette5, C Cooper2, X Chevalier6. 1. Department of Rheumatology, AP-HP Henri Mondor Hospital, F-94010 Créteil Cedex, France. 2. MRC Lifecourse Epidemiology Unit, Southampton General Hospital, SO16 6YD Southampton, UK. 3. Clinical Department, Servier Laboratory, 92150 Suresnes, France. 4. Department of Public Health and Health Economics, University of Liege, 4020 Liege, Belgium. 5. Department of Rheumatology, AP-HP Lariboisière Hospital, F-75475 Paris Cedex 10, France. 6. Department of Rheumatology, AP-HP Henri Mondor Hospital, F-94010 Créteil Cedex, France. Electronic address: xavier.chevalier@hmn.aphp.fr.
Abstract
PURPOSE: Recent studies have suggested that metabolic factors (obesity, diabetes, hypertension and dyslipidemia) and their clustering in metabolic syndrome (MetS) might be involved in the pathophysiology of knee osteoarthritis (OA). We investigated their impact on radiographic progression by an annualised measure of the joint space narrowing (JSN) of the medial tibiofemoral compartment. METHODS: 559 patients older than 50 years with symptomatic knee OA were recruited for the placebo arm of the SEKOIA trial. The presence of diabetes, hypertension and dyslipidemia was determined at baseline interview. Body mass index (BMI) was calculated, obesity was considered >30 kg/m(2). MetS was defined by the sum of metabolic factors ≥ 3. Minimal medial tibiofemoral joint space on plain radiographs was measured by an automated method at baseline and then annually for up to 3 years. RESULTS: The mean age of patients was 62.8 [62.2-63.4] years; 392 were women. A total of 43.8% was obese, 6.6% had type 2 diabetes, 45.1% hypertension, 27.6% dyslipidemia and 13.6% MetS. Mean annualised JSN was greater for patients with type 2 diabetes than without diabetes (0.26 [-0.35 to -0.17] vs 0.14 [-0.16 to -0.12] mm; P = 0.001). This association remained significant after adjustment for sex, age, BMI, hypertension and dyslipidemia (P = 0.018). In subgroup analysis, type 2 diabetes was a significant predictor of JSN in males but not females. The other metabolic factors and MetS were not associated with annualised JSN. CONCLUSION: Type 2 diabetes was a predictor of joint space reduction in men with established knee OA. No relationships were found between MetS or other metabolic factors and radiographic progression.
PURPOSE: Recent studies have suggested that metabolic factors (obesity, diabetes, hypertension and dyslipidemia) and their clustering in metabolic syndrome (MetS) might be involved in the pathophysiology of knee osteoarthritis (OA). We investigated their impact on radiographic progression by an annualised measure of the joint space narrowing (JSN) of the medial tibiofemoral compartment. METHODS: 559 patients older than 50 years with symptomatic knee OA were recruited for the placebo arm of the SEKOIA trial. The presence of diabetes, hypertension and dyslipidemia was determined at baseline interview. Body mass index (BMI) was calculated, obesity was considered >30 kg/m(2). MetS was defined by the sum of metabolic factors ≥ 3. Minimal medial tibiofemoral joint space on plain radiographs was measured by an automated method at baseline and then annually for up to 3 years. RESULTS: The mean age of patients was 62.8 [62.2-63.4] years; 392 were women. A total of 43.8% was obese, 6.6% had type 2 diabetes, 45.1% hypertension, 27.6% dyslipidemia and 13.6% MetS. Mean annualised JSN was greater for patients with type 2 diabetes than without diabetes (0.26 [-0.35 to -0.17] vs 0.14 [-0.16 to -0.12] mm; P = 0.001). This association remained significant after adjustment for sex, age, BMI, hypertension and dyslipidemia (P = 0.018). In subgroup analysis, type 2 diabetes was a significant predictor of JSN in males but not females. The other metabolic factors and MetS were not associated with annualised JSN. CONCLUSION: Type 2 diabetes was a predictor of joint space reduction in men with established knee OA. No relationships were found between MetS or other metabolic factors and radiographic progression.
Authors: Nicola Veronese; Cyrus Cooper; Jean-Yves Reginster; Marc Hochberg; Jaime Branco; Olivier Bruyère; Roland Chapurlat; Nasser Al-Daghri; Elaine Dennison; Gabriel Herrero-Beaumont; Jean-François Kaux; Emmanuel Maheu; René Rizzoli; Roland Roth; Lucio C Rovati; Daniel Uebelhart; Mila Vlaskovska; André Scheen Journal: Semin Arthritis Rheum Date: 2019-01-11 Impact factor: 5.532
Authors: Tara S Rogers-Soeder; Nancy E Lane; Mona Walimbe; Ann V Schwartz; Irina Tolstykh; David T Felson; Cora E Lewis; Neil A Segal; Michael C Nevitt Journal: Arthritis Care Res (Hoboken) Date: 2020-01 Impact factor: 4.794
Authors: Nattagan Chanchek; Alexandra S Gersing; Benedikt J Schwaiger; Michael C Nevitt; Jan Neumann; Gabby B Joseph; Nancy E Lane; Julia Zarnowski; Felix C Hofmann; Ursula Heilmeier; Charles E McCulloch; Thomas M Link Journal: J Magn Reson Imaging Date: 2017-05-26 Impact factor: 4.813
Authors: Jan Neumann; Julio B Guimaraes; Ursula Heilmeier; Gabby B Joseph; Michael C Nevitt; Charles E McCulloch; Thomas M Link Journal: Skeletal Radiol Date: 2018-10-24 Impact factor: 2.199
Authors: J Neumann; F C Hofmann; U Heilmeier; W Ashmeik; K Tang; A S Gersing; B J Schwaiger; M C Nevitt; G B Joseph; N E Lane; C E McCulloch; T M Link Journal: Osteoarthritis Cartilage Date: 2018-03-29 Impact factor: 6.576