Literature DB >> 31912407

Identifying subgroups of community-dwelling older adults and their prospective associations with long-term knee osteoarthritis outcomes.

Ishanka P Munugoda1, Feng Pan2, Karen Wills2, Siti M Mattap2, Flavia Cicuttini3, Stephen E Graves4, Michelle Lorimer5, Graeme Jones2, Michele L Callisaya2,6, Dawn Aitken2.   

Abstract

OBJECTIVES: To identify subgroups of community-dwelling older adults and to assess their longitudinal associations with long-term osteoarthritis (OA) outcomes.
METHODS: 1046 older adults aged 50-80 years were studied. At baseline, body mass index (BMI), pedometer-measured ambulatory activity (AA), and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) determined knee pain and information on comorbidities were obtained. Tibial cartilage volume and bone-marrow lesions (BMLs) were assessed using MRI at baseline and 10 years and total knee replacements (TKR) by data linkage to the Australian Orthopaedic Association National Joint Replacement Registry. Latent class analysis was used to determine participant subgroups, considering baseline BMI, AA, pain and comorbidities, and linear mixed-effects or log-binomial models were used to assess the associations.
RESULTS: Three subgroups/classes were identified: subgroup 1 (43%): Normal/overweight participants with higher AA, lower pain and lower comorbidities; subgroup 2 (32%): Overweight participants with lower AA, mild pain and higher comorbidities; subgroup 3 (25%): Obese participants with lower AA, mild pain and higher comorbidities. Subgroup 3 had greater cartilage volume loss (β - 60.56 mm3, 95% CI - 105.91, - 15.21) and a higher risk of TKR (RR 3.19, 95% CI 1.75, 5.81), compared to subgroup 1. Subgroup 2 was not associated with cartilage volume change (β 13.06 mm3, 95% CI - 30.87, 57.00) or risk of TKR (RR 1.16, 95% CI 0.56, 2.36), compared to subgroup 1. Subgroup membership was not associated with worsening BMLs.
CONCLUSIONS: Our findings suggest the existence of homogeneous subgroups of participants and support the utility of identifying patterns of characteristics/risk factors that may cluster together and using them to identify subgroups of people who may be at a higher risk of developing and/or progressing OA. Key Points • Complex interplay among characteristics/factors leads to conflicting evidence between ambulatory activity and knee osteoarthritis. • Distinct subgroups are identifiable based on ambulatory activity, body mass index, knee pain, and comorbidities. • Identifying subgroups can be used to determine those who are at risk of developing/progressing osteoarthritis.

Entities:  

Keywords:  Bone-marrow lesions; Cartilage volume; Latent-class analysis; Osteoarthritis; Total knee replacement

Year:  2020        PMID: 31912407     DOI: 10.1007/s10067-019-04920-8

Source DB:  PubMed          Journal:  Clin Rheumatol        ISSN: 0770-3198            Impact factor:   2.980


  26 in total

1.  Identifying different osteoarthritis phenotypes through epidemiology.

Authors:  D T Felson
Journal:  Osteoarthritis Cartilage       Date:  2010-02-06       Impact factor: 6.576

Review 2.  Etiopathogenesis of osteoarthritis.

Authors:  Kenneth D Brandt; Paul Dieppe; Eric L Radin
Journal:  Rheum Dis Clin North Am       Date:  2008-08       Impact factor: 2.670

3.  The global burden of hip and knee osteoarthritis: estimates from the global burden of disease 2010 study.

Authors:  Marita Cross; Emma Smith; Damian Hoy; Sandra Nolte; Ilana Ackerman; Marlene Fransen; Lisa Bridgett; Sean Williams; Francis Guillemin; Catherine L Hill; Laura L Laslett; Graeme Jones; Flavia Cicuttini; Richard Osborne; Theo Vos; Rachelle Buchbinder; Anthony Woolf; Lyn March
Journal:  Ann Rheum Dis       Date:  2014-02-19       Impact factor: 19.103

Review 4.  Running and Knee Osteoarthritis: A Systematic Review and Meta-analysis.

Authors:  Kate A Timmins; Richard D Leech; Mark E Batt; Kimberley L Edwards
Journal:  Am J Sports Med       Date:  2016-08-20       Impact factor: 6.202

Review 5.  Knee osteoarthritis phenotypes and their relevance for outcomes: a systematic review.

Authors:  L A Deveza; L Melo; T P Yamato; K Mills; V Ravi; D J Hunter
Journal:  Osteoarthritis Cartilage       Date:  2017-08-25       Impact factor: 6.576

6.  The association between ambulatory activity, body composition and hip or knee joint replacement due to osteoarthritis: a prospective cohort study.

Authors:  I P Munugoda; K Wills; F Cicuttini; S E Graves; M Lorimer; G Jones; M L Callisaya; D Aitken
Journal:  Osteoarthritis Cartilage       Date:  2018-02-21       Impact factor: 6.576

Review 7.  Obesity punches above its weight in osteoarthritis.

Authors:  Richard M Aspden
Journal:  Nat Rev Rheumatol       Date:  2010-08-17       Impact factor: 20.543

8.  Subgroups of older adults with osteoarthritis based upon differing comorbid symptom presentations and potential underlying pain mechanisms.

Authors:  Susan L Murphy; Angela K Lyden; Kristine Phillips; Daniel J Clauw; David A Williams
Journal:  Arthritis Res Ther       Date:  2011-08-24       Impact factor: 5.156

Review 9.  Identification of clinical phenotypes in knee osteoarthritis: a systematic review of the literature.

Authors:  A Dell'Isola; R Allan; S L Smith; S S P Marreiros; M Steultjens
Journal:  BMC Musculoskelet Disord       Date:  2016-10-12       Impact factor: 2.362

10.  Relationship between body adiposity measures and risk of primary knee and hip replacement for osteoarthritis: a prospective cohort study.

Authors:  Yuanyuan Wang; Julie Anne Simpson; Anita E Wluka; Andrew J Teichtahl; Dallas R English; Graham G Giles; Stephen Graves; Flavia M Cicuttini
Journal:  Arthritis Res Ther       Date:  2009-03-05       Impact factor: 5.156

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  1 in total

1.  Serum Metabolomic Signatures for Knee Cartilage Volume Loss over 10 Years in Community-Dwelling Older Adults.

Authors:  Zikun Xie; Dawn Aitken; Ming Liu; Guanghua Lei; Graeme Jones; Flavia Cicuttini; Guangju Zhai
Journal:  Life (Basel)       Date:  2022-06-10
  1 in total

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