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Osteoarthritis Cartilage. 2016 Apr;24(4):640-6. doi: 10.1016/j.joca.2015.11.013. Epub 2015 Nov 24.

Novel statistical methodology reveals that hip shape is associated with incident radiographic hip osteoarthritis among African American women.

Author information

1
Department of Statistics and Operations Research, University of North Carolina, Hanes Hall CB 3260, Chapel Hill, NC 27599, USA. Electronic address: ahwbest@email.unc.edu.
2
Department of Statistics and Operations Research, University of North Carolina, Hanes Hall CB 3260, Chapel Hill, NC 27599, USA. Electronic address: marron@unc.edu.
3
Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, 3106E McGavran-Greenberg Hall CB 7420, Chapel Hill, NC 27599, USA. Electronic address: Todd_Schwartz@unc.edu.
4
Department of Radiology, University of North Carolina, 509 Old Infirmary Bldg CB 7510, Chapel Hill, NC 27599, USA; Thurston Arthritis Research Center, University of North Carolina, 3300 Thurston Building CB 7280, Chapel Hill, NC 27599, USA. Electronic address: jordan_renner@med.unc.edu.
5
University of California at San Francisco, Mission Hall: Global Health & Clinical Sciences Bldg, 550 16th St, 2nd Floor, San Francisco, CA 94158-2549, USA. Electronic address: fliu@psg.ucsf.edu.
6
University of California at San Francisco, Mission Hall: Global Health & Clinical Sciences Bldg, 550 16th St, 2nd Floor, San Francisco, CA 94158-2549, USA. Electronic address: jlynch@psg.ucsf.edu.
7
University of California Davis School of Medicine, 451 Health Sciences Dr, Davis, CA 95616, USA. Electronic address: nelane@ucdavis.edu.
8
Thurston Arthritis Research Center, University of North Carolina, 3300 Thurston Building CB 7280, Chapel Hill, NC 27599, USA. Electronic address: joanne_jordan@med.unc.edu.
9
Thurston Arthritis Research Center, University of North Carolina, 3300 Thurston Building CB 7280, Chapel Hill, NC 27599, USA. Electronic address: aenelson@med.unc.edu.

Abstract

INTRODUCTION:

Hip shape is a risk factor for the development of hip osteoarthritis (OA), and current methods to assess hip shape from radiographs are limited; therefore this study explored current and novel methods to assess hip shape.

METHODS:

Data from a prior case-control study nested in the Johnston County OA Project were used, including 382 hips (from 342 individuals). Hips were classified by radiographic hip OA (RHOA) status as RHOA cases (baseline Kellgren Lawrence grade [KLG] 0 or 1, follow-up [mean 6 years] KLG ≥ 2) or controls (KLG = 0 or 1 at both baseline and follow-up). Proximal femur shape was assessed using a 60-point model as previously described. The current analysis explored commonly used principal component analysis (PCA), as well as novel statistical methodologies suited to high dimension low sample size settings (Distance Weighted Discrimination [DWD] and Distance Projection Permutation [DiProPerm] hypothesis testing) to assess differences between cases and controls.

RESULTS:

Using these novel methodologies, we were able to better characterize morphologic differences by sex and race. In particular, the proximal femurs of African American women demonstrated significantly different shapes between cases and controls, implying an important role for sex and race in the development of RHOA. Notably, discrimination was improved with the use of DWD and DiProPerm compared to PCA.

CONCLUSIONS:

DWD with DiProPerm significance testing provides improved discrimination of variation in hip morphology between groups, and enables subgroup analyses even under small sample sizes.

KEYWORDS:

Hip morphology; Hip osteoarthritis; Linear discriminant analysis; Principal component analysis; Racial differences

PMID:
26620089
PMCID:
PMC4799754
DOI:
10.1016/j.joca.2015.11.013
[Indexed for MEDLINE]
Free PMC Article

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