Article Text

Download PDFPDF
Development and validation of risk stratification trees for incident slow gait speed in persons at high risk for knee osteoarthritis
  1. Leena Sharma1,
  2. Kent Kwoh2,
  3. Jungwha (Julia) Lee3,
  4. Jane Cauley4,
  5. Rebecca Jackson5,
  6. Marc Hochberg6,
  7. Alison H Chang7,
  8. Charles Eaton8,
  9. Michael Nevitt9,
  10. Jing Song10,
  11. Orit Almagor10,
  12. Joan S Chmiel3
  1. 1Departments of Medicine and Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
  2. 2University of Arizona, Tucson, Arizona, USA
  3. 3Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
  4. 4University of Pittsburgh, Pittsburgh, Pennsylvania, USA
  5. 5Ohio State University, Columbus, Ohio, USA
  6. 6University of Maryland Baltimore, Baltimore, Maryland, USA
  7. 7Physical Therapy and Human Movement Sciences, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
  8. 8Brown University Warren Alpert Medical School, Providence, Rhode Island, USA
  9. 9University of California San Francisco, San Francisco, California, USA
  10. 10Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
  1. Correspondence to Professor Leena Sharma, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA; l-sharma{at}northwestern.edu

Abstract

Objectives Disability prevention strategies are more achievable before osteoarthritis disease drives impairment. It is critical to identify high-risk groups, for strategy implementation and trial eligibility. An established measure, gait speed is associated with disability and mortality. We sought to develop and validate risk stratification trees for incident slow gait in persons at high risk for knee osteoarthritis, feasible in community and clinical settings.

Methods Osteoarthritis Initiative (derivation cohort) and Multicenter Osteoarthritis Study (validation cohort) participants at high risk for knee osteoarthritis were included. Outcome was incident slow gait over up to 10-year follow-up. Derivation cohort classification and regression tree analysis identified predictors from easily assessed variables and developed risk stratification models, then applied to the validation cohort. Logistic regression compared risk group predictive values; area under the receiver operating characteristic curves (AUCs) summarised discrimination ability.

Results 1870 (derivation) and 1279 (validation) persons were included. The most parsimonious tree identified three risk groups, from stratification based on age and WOMAC Function. A 7-risk-group tree also included education, strenuous sport/recreational activity, obesity and depressive symptoms; outcome occurred in 11%, varying 0%–29 % (derivation) and 2%–23 % (validation) depending on risk group. AUCs were comparable in the two cohorts (7-risk-group tree, 0.75, 95% CI 0.72 to 0.78 (derivation); 0.72, 95% CI 0.68 to 0.76 (validation)).

Conclusions In persons at high risk for knee osteoarthritis, easily acquired data can be used to identify those at high risk of incident functional impairment. Outcome risk varied greatly depending on tree-based risk group membership. These trees can inform individual awareness of risk for impaired function and define eligibility for prevention trials.

  • osteoarthritis
  • knee osteoarthritis
  • disability
  • functional impairment
  • prevention
View Full Text

Statistics from Altmetric.com

Footnotes

  • Handling editor Josef S Smolen

  • Correction notice This article has been corrected since it published Online First. The author affiliations have been updated.

  • Contributors Every author met the ICMJE criteria for authorship.

  • Funding This work was supported by NIH/NIAMS R01 AR065473, R01AR066601, P30AR072579 grants. The Osteoarthritis Initiative is a public-private partnership comprised of five NIH contracts (N01-AR-2-2258; N01-AR-2-2259; N01-AR-2-2260; N01-AR-2-2261;N01-AR-2-2262) funded by the NIH and conducted by the OAI Study Investigators. Private sector funding for the OAI is managed by the Foundation for the NIH.The Multicenter Osteoarthritis Study is supported by NIH grants U01-AG-18820,U01-AG-18832, U01-AG-18947, and U01-AG-19079.

  • Competing interests None declared.

  • Patient consent for publication Not required.

  • Ethics approval The Institutional Review Board at each site approved the study.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data availability statement Data are available on reasonable request.

Request Permissions

If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.