Osteoarthritis disease progression model using six year follow-up data from the osteoarthritis initiative

Chaitali Passey, Holly Kimko, Partha Nandy, Leonid Kagan

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

The objective was to develop a quantitative model of disease progression of knee osteoarthritis over 6 years using the total WOMAC score from patients enrolled into the Osteoarthritis Initiative (OAI) study. The analysis was performed using data from the Osteoarthritis Initiative database. The time course of the total WOMAC score of patients enrolled into the progression cohort was characterized using non-linear mixed effect modeling in NONMEM. The effect of covariates on the status of the disease and the progression rate was investigated. The final model provided a good description of the experimental data using a linear progression model with a common baseline (19 units of the total WOMAC score). The WOMAC score decreased by 1.77 units/year in 89% of the population or increased by 1.74 units/year in 11% of the population. Multiple covariates were found to affect the baseline and the rate of progression, including BMI, sex, race, the use of pain medications, and the limitation in activity due to symptoms. A mathematical model to describe the disease progression of osteoarthritis in the studied population was developed. The model identified two sub-populations with increasing or decreasing total WOMAC score over time, and the effect of important covariates was quantified.

Original languageEnglish (US)
Pages (from-to)269-278
Number of pages10
JournalJournal of Clinical Pharmacology
Volume55
Issue number3
DOIs
StatePublished - Mar 1 2015

All Science Journal Classification (ASJC) codes

  • Pharmacology
  • Pharmacology (medical)

Keywords

  • Knee osteoarthritis
  • WOMAC
  • disease progression
  • non-linear mixed effects modeling

Fingerprint Dive into the research topics of 'Osteoarthritis disease progression model using six year follow-up data from the osteoarthritis initiative'. Together they form a unique fingerprint.

Cite this