OA20 Radiographic hip osteoarthritis classified semi-automatically on dual-energy x-ray absorptiometry scans is strongly predictive of total hip replacement: findings from UK Biobank. (23rd April 2022)
- Record Type:
- Journal Article
- Title:
- OA20 Radiographic hip osteoarthritis classified semi-automatically on dual-energy x-ray absorptiometry scans is strongly predictive of total hip replacement: findings from UK Biobank. (23rd April 2022)
- Main Title:
- OA20 Radiographic hip osteoarthritis classified semi-automatically on dual-energy x-ray absorptiometry scans is strongly predictive of total hip replacement: findings from UK Biobank
- Authors:
- Faber, Benjamin G
Ebsim, Raja
Saunders, Fiona R
Frysz, Monika
Lindner, Claudia
Gregory, Jennifer S
Aspden, Richard M
Harvey, Nicholas C
Smith, George Davey
Cootes, Timothy
Tobias, Jonathan H - Abstract:
- Abstract: Background/Aims: Radiographic hip osteoarthritis (rHOA) is traditionally defined on hip x-rays, using subjective methods such as Kellgren-Lawrence scoring. Associations between subjective rHOA measures and symptoms are inconsistent. Applying digital tools to high-resolution dual-energy X-ray absorptiometry (DXA) scans, we aimed to develop a novel semi-automated classifier for rHOA and evaluate the face validity of the classifier based on relationships with hip pain, hospital diagnosed OA (HES OA), and risk of total hip replacement (THR). Methods: Using hip DXAs in UK Biobank, osteophyte grades 0-3 were assigned based on manually measured osteophyte area. Minimum joint space width (mJSW) was automatically measured using outline points placed by a machine learning-based algorithm and then used to categorise individuals into joint space narrowing (JSN) grades 0-3. Osteophyte and JSN grades were combined, using a novel system giving greater to weight to osteophytes, to categorise individuals into rHOA grades 0-4. Logistic regression giving odds ratios (OR) was used to examine associations between rHOA grade and hip pain, and HES OA. Cox proportional hazard models giving hazard ratios (HR) were used to examine associations between rHOA grade and subsequent THR. Our adjusted model included age, sex, height and weight as covariates. Results: 40, 340 individuals were included in the study (mean age 63.7 [range 44-82], 19294/21046 male/female). 32758 (81.2%) had rHOA gradeAbstract: Background/Aims: Radiographic hip osteoarthritis (rHOA) is traditionally defined on hip x-rays, using subjective methods such as Kellgren-Lawrence scoring. Associations between subjective rHOA measures and symptoms are inconsistent. Applying digital tools to high-resolution dual-energy X-ray absorptiometry (DXA) scans, we aimed to develop a novel semi-automated classifier for rHOA and evaluate the face validity of the classifier based on relationships with hip pain, hospital diagnosed OA (HES OA), and risk of total hip replacement (THR). Methods: Using hip DXAs in UK Biobank, osteophyte grades 0-3 were assigned based on manually measured osteophyte area. Minimum joint space width (mJSW) was automatically measured using outline points placed by a machine learning-based algorithm and then used to categorise individuals into joint space narrowing (JSN) grades 0-3. Osteophyte and JSN grades were combined, using a novel system giving greater to weight to osteophytes, to categorise individuals into rHOA grades 0-4. Logistic regression giving odds ratios (OR) was used to examine associations between rHOA grade and hip pain, and HES OA. Cox proportional hazard models giving hazard ratios (HR) were used to examine associations between rHOA grade and subsequent THR. Our adjusted model included age, sex, height and weight as covariates. Results: 40, 340 individuals were included in the study (mean age 63.7 [range 44-82], 19294/21046 male/female). 32758 (81.2%) had rHOA grade 0, 4565 (11.3%) grade 1, 2317 (5.7%) grade 2, 543 (1.3%) grade 3, 157 (0.4%) grade 4, with all features of rHOA being more common in males than females. rHOA grades ≥2 were associated with all three clinical outcomes in both unadjusted and adjusted models, a clear dose-response relationship was seen with each increase in grade showing a large rise in OR/HRs (Table 1). Grade 4 rHOA was strongly predictive of THR (HR 57.70 [95%CI 38.08-87.44]). Conclusion: We successfully applied a novel semi-automated classifier to over 40, 000 individuals from UKB. The validity of our classifier was supported by the strong and progressive relationships observed between rHOA and hip pain, and HES OA and risk of THR. We conclude that hip DXAs provide a promising means of defining rHOA, with potential screening applications in the clinic. Disclosure: B.G. Faber: None. R. Ebsim: None. F.R. Saunders: None. M. Frysz: None. C. Lindner: None. J.S. Gregory: None. R.M. Aspden: None. N.C. Harvey: None. G. Davey Smith: None. T. Cootes: None. J.H. Tobias: None. … (more)
- Is Part Of:
- Rheumatology. Volume 61(2022)Supplement 1
- Journal:
- Rheumatology
- Issue:
- Volume 61(2022)Supplement 1
- Issue Display:
- Volume 61, Issue 1 (2022)
- Year:
- 2022
- Volume:
- 61
- Issue:
- 1
- Issue Sort Value:
- 2022-0061-0001-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-04-23
- Subjects:
- Rheumatism -- Periodicals
Rheumatology -- Periodicals
616.723005 - Journal URLs:
- http://rheumatology.oupjournals.org ↗
http://rheumatology.oxfordjournals.org ↗
http://ukcatalogue.oup.com/ ↗
http://firstsearch.oclc.org ↗ - DOI:
- 10.1093/rheumatology/keac132.020 ↗
- Languages:
- English
- ISSNs:
- 1462-0324
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- Legaldeposit
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