Exploring Early Lupus Subtypes Open Access

Speckman, Rebecca Ann (2010)

Permanent URL: https://etd.library.emory.edu/concern/etds/q811kj66v?locale=en
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Abstract

Abstract
Exploring early lupus subtypes
By Rebecca A. Speckman
Systemic lupus erythematosus (SLE), or lupus, is an autoimmune disease characterized by the presence of
autoantibodies to elements of the cell nucleus. SLE can cause permanent damage to any organ system. Di-
agnosis is made by the recognition of a "constellation of symptoms and signs," as there is no gold standard
test for SLE. Patients diagnosed with lupus by a physician or classified as having lupus by the accepted re-
search classification criteria have wide inter-patient variety in organ system involvement; many lupus patients
exhibit only a subset of the possible clinical manifestations. It is possible that several disease subtypes, or
alternatively several diseases with overlapping manifestations, are encompassed by what is currently called
lupus.
In my first study, I found that K-modes cluster analysis did not outperform K-means in the presence/absence
data examined. However, because the K-modes and K-means suggested different partitions in a real data set,
it may be useful to consider the two methods as complementary in the setting of subtype exploration (class
discovery). In my second study, I found that recommended indices for choosing the best presence/absence
data partition were not reliable. In my third study, I used K-means, K-modes, and latent class analysis to
create clusters of early lupus patients. A set of four clusters created by K-means was selected as candidate
early lupus subtypes.

Exploring early lupus subtypes
By
Rebecca A. Speckman
B.A., Washington University, 1999
Advisor: William M. McClellan, MD, MPH
A dissertation submitted to the Faculty of the
James T. Laney School of Graduate Studies of Emory University
in partial fulfillment of the requirements for the degree of
Doctor of Philosophy
in Epidemiology.
2010

Table of Contents

1 Introduction and context 1
1.1 Dissertation overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.2 Subtyping as case definition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
1.3 SLE case definition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
1.4 Georgia Lupus Registry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
2 Cluster analysis: Literature review 18
2.1 K-centroids cluster analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
2.2 The K-centroids method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
2.3 Choosing the best partition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
2.4 Measuring agreement between two partitions . . . . . . . . . . . . . . . . . . . . . . . . . 39
3 Paper 1: K-centroids variations for the identification of disease subtypes with presence/absence
attributes 52
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
3.2 Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
3.3 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
3.4 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
3.5 Figures and tables. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
4 Paper 2: A comparison of relative validity indices for choosing the best partition in presenceabsence
data 73
4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
4.2 Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
4.3 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
4.4 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85
4.5 Figures and tables. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
5 Paper 3: Using class discovery methods to explore early lupus subtypes in the Georgia Lupus
Registry 93
5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94
5.2 Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95
5.3 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98
5.4 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100
5.5 Figures and tables. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103
6 Paper 4: Exploring early lupus subtypes in the Georgia Lupus Registry 108
6.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109
6.2 Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109
6.3 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112
6.4 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113
6.5 Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116
7 Elaboration of results 118
7.1 Study 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118
8 Discussion 129
8.1 Summary and conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129
8.2 Strengths and Limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130
8.3 Future steps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131
A Additional methods background 133
A.1 Monte Carlo studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133
A.2 Data generation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137

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