Literature DB >> 23962456

Prediction model for knee osteoarthritis incidence, including clinical, genetic and biochemical risk factors.

H J M Kerkhof1, S M A Bierma-Zeinstra2, N K Arden3, S Metrustry4, M Castano-Betancourt1, D J Hart4, A Hofman5, F Rivadeneira6, E H G Oei7, Tim D Spector4, A G Uitterlinden6, A C J W Janssens5, A M Valdes8, J B J van Meurs1.   

Abstract

OBJECTIVE: To develop and validate a prognostic model for incident knee osteoarthritis (KOA) in a general population and determine the value of different risk factor groups to prediction.
METHODS: The prognostic model was developed in 2628 individuals from the Rotterdam Study-I (RS-I). Univariate and multivariate analyses were performed for questionnaire/easily obtainable variables, imaging variables, genetic and biochemical markers. The extended multivariate model was tested on discrimination (receiver operating characteristic curve and area under the curve (AUC)) in two other population-based cohorts: Rotterdam Study-II and Chingford Study.
RESULTS: In RS-I, there was moderate predictive value for incident KOA based on the genetic score alone in subjects aged <65 years (AUC 0.65), while it was only 0.55 for subjects aged ≥65 years. The AUC for gender, age and body mass index (BMI) in prediction for KOA was 0.66. Addition of the questionnaire variables, genetic score or biochemical marker urinary C-terminal cross-linked telopeptide of type II collagen to the model did not change the AUC. However, when adding the knee baseline KL score to the model the AUC increased to 0.79. Applying external validation, similar results were observed in the Rotterdam Study-II and the Chingford Study.
CONCLUSIONS: Easy obtainable 'Questionnaire' variables, genetic markers, OA at other joint sites and biochemical markers add only modestly to the prediction of KOA incidence using age, gender and BMI in an elderly population. Doubtful minor radiographic degenerative features in the knee, however, are a very strong predictor of future KOA. This is an important finding, as many radiologists do not report minor degenerative changes in the knee. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Entities:  

Keywords:  Epidemiology; Knee Osteoarthritis; Osteoarthritis

Mesh:

Substances:

Year:  2013        PMID: 23962456     DOI: 10.1136/annrheumdis-2013-203620

Source DB:  PubMed          Journal:  Ann Rheum Dis        ISSN: 0003-4967            Impact factor:   19.103


  48 in total

1.  The Rotterdam Study: 2016 objectives and design update.

Authors:  Albert Hofman; Guy G O Brusselle; Sarwa Darwish Murad; Cornelia M van Duijn; Oscar H Franco; André Goedegebure; M Arfan Ikram; Caroline C W Klaver; Tamar E C Nijsten; Robin P Peeters; Bruno H Ch Stricker; Henning W Tiemeier; André G Uitterlinden; Meike W Vernooij
Journal:  Eur J Epidemiol       Date:  2015-09-19       Impact factor: 8.082

2.  The incident tibiofemoral osteoarthritis with rapid progression phenotype: development and validation of a prognostic prediction rule.

Authors:  D L Riddle; P W Stratford; R A Perera
Journal:  Osteoarthritis Cartilage       Date:  2016-07-05       Impact factor: 6.576

Review 3.  Imaging in rheumatology in 2013. From images to data to theory.

Authors:  Felix Eckstein; C Kent Kwoh
Journal:  Nat Rev Rheumatol       Date:  2013-12-24       Impact factor: 20.543

Review 4.  Call for standardized definitions of osteoarthritis and risk stratification for clinical trials and clinical use.

Authors:  V B Kraus; F J Blanco; M Englund; M A Karsdal; L S Lohmander
Journal:  Osteoarthritis Cartilage       Date:  2015-04-09       Impact factor: 6.576

5.  Incidence and prevalence of total joint replacements due to osteoarthritis in the elderly: risk factors and factors associated with late life prevalence in the AGES-Reykjavik Study.

Authors:  Helgi Jonsson; Sigurbjorg Olafsdottir; Solveig Sigurdardottir; Thor Aspelund; Gudny Eiriksdottir; Sigurdur Sigurdsson; Tamara B Harris; Lenore Launer; Vilmundur Gudnason
Journal:  BMC Musculoskelet Disord       Date:  2016-01-12       Impact factor: 2.362

6.  Tool for osteoarthritis risk prediction (TOARP) over 8 years using baseline clinical data, X-ray, and MRI: Data from the osteoarthritis initiative.

Authors:  Gabby B Joseph; Charles E McCulloch; Michael C Nevitt; Jan Neumann; Alexandra S Gersing; Martin Kretzschmar; Benedikt J Schwaiger; John A Lynch; Ursula Heilmeier; Nancy E Lane; Thomas M Link
Journal:  J Magn Reson Imaging       Date:  2017-11-16       Impact factor: 4.813

7.  Determinants of knee replacement in subjects with a history of arthroscopy: data from the osteoarthritis initiative.

Authors:  Bashir Zikria; Nima Hafezi-Nejad; John Wilckens; James R Ficke; Shadpour Demehri
Journal:  Eur J Orthop Surg Traumatol       Date:  2016-07-05

8.  Predicting Incident Radiographic Knee Osteoarthritis in Middle-Aged Women Within Four Years: The Importance of Knee-Level Prognostic Factors.

Authors:  Cesar Garriga; Maria T Sánchez-Santos; Andrew Judge; Deborah Hart; Tim Spector; Cyrus Cooper; Nigel K Arden
Journal:  Arthritis Care Res (Hoboken)       Date:  2020-01       Impact factor: 4.794

Review 9.  Strategies for the prevention of knee osteoarthritis.

Authors:  Ewa M Roos; Nigel K Arden
Journal:  Nat Rev Rheumatol       Date:  2015-10-06       Impact factor: 20.543

Review 10.  Nutritional, metabolic and genetic considerations to optimise regenerative medicine outcome for knee osteoarthritis.

Authors:  Kholoud Hafsi; Janine McKay; Jinjie Li; José Fábio Lana; Alex Macedo; Gabriel Silva Santos; William D Murrell
Journal:  J Clin Orthop Trauma       Date:  2018-10-15
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