| Authors | Vahid Arbabi |
| Journal | BMJ Open |
| Page number | 1-13 |
| Serial number | 14 |
| Volume number | 77907 |
| Paper Type | Full Paper |
| Published At | 2024 |
| Journal Type | Typographic |
| Journal Country | Iran, Islamic Republic Of |
| Journal Index | ISI،JCR،Scopus |
| Keywords | Hip osteoarthritis imaging analysis |
|---|
Abstract
Purpose Hip osteoarthritis (OA) is a major cause of pain and
disability worldwide. Lack of effective therapies may reflect
poor knowledge on its aetiology and risk factors, and result
in the management of end- stage hip OA with costly joint
replacement. The Worldwide Collaboration on OsteoArthritis
prediCtion for the Hip (World COACH) consortium was
established to pool and harmonise individual participant data
from prospective cohort studies. The consortium aims to better
understand determinants and risk factors for the development
and progression of hip OA, to optimise and automate methods
for (imaging) analysis, and to develop a personalised prediction
model for hip OA.
Participants World COACH aimed to include participants of
prospective cohort studies with ≥200 participants, that have
hip imaging data available from at least 2 time points at least
4 years apart. All individual participant data, including clinical
data, imaging (data), biochemical markers, questionnaires
and genetic data, were collected and pooled into a single,
individual- level database.
Findings to date
World COACH currently consists of 9 cohorts,
with 38 021 participants aged 18–80 years at baseline. Overall,
71% of the participants were women and mean baseline age
was 65.3±8.6 years. Over 34 000 participants had baseline
pelvic radiographs available, and over 22 000 had an additional
pelvic radiograph after 8–12 years of follow- up. Even longer
radiographic follow- up (15–25 years) is available for over 6000
of these participants.
Future plans The World COACH consortium offers unique
opportunities for studies on the relationship between
determinants/risk factors and the development or progression
of hip OA, by using harmonised data on clinical findings, imaging, biomarkers, genetics and lifestyle. This provides
a unique opportunity to develop a personalised hip OA risk
prediction model and to optimise methods for imaging analysis
of the hip.
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