PMID- 25854937
OWN - NLM
STAT- MEDLINE
DCOM- 20180514
LR  - 20240325
IS  - 1477-0334 (Electronic)
IS  - 0962-2802 (Print)
IS  - 0962-2802 (Linking)
VI  - 26
IP  - 3
DP  - 2017 Jun
TI  - A statistical method for studying correlated rare events and their risk factors.
PG  - 1416-1428
LID - 10.1177/0962280215581112 [doi]
AB  - Longitudinal studies of rare events such as cervical high-grade lesions or 
      colorectal polyps that can recur often involve correlated binary data. Risk 
      factor for these events cannot be reliably examined using conventional 
      statistical methods. For example, logistic regression models that incorporate 
      generalized estimating equations often fail to converge or provide inaccurate 
      results when analyzing data of this type. Although exact methods have been 
      reported, they are complex and computationally difficult. The current paper 
      proposes a mathematically straightforward and easy-to-use two-step approach 
      involving (i) an additive model to measure associations between a rare or 
      uncommon correlated binary event and potential risk factors and (ii) a 
      permutation test to estimate the statistical significance of these associations. 
      Simulation studies showed that the proposed method reliably tests and accurately 
      estimates the associations of exposure with correlated binary rare events. This 
      method was then applied to a longitudinal study of human leukocyte antigen (HLA) 
      genotype and risk of cervical high grade squamous intraepithelial lesions (HSIL) 
      among HIV-infected and HIV-uninfected women. Results showed statistically 
      significant associations of two HLA alleles among HIV-negative but not 
      HIV-positive women, suggesting that immune status may modify the HLA and cervical 
      HSIL association. Overall, the proposed method avoids model nonconvergence 
      problems and provides a computationally simple, accurate, and powerful approach 
      for the analysis of risk factor associations with rare/uncommon correlated binary 
      events.
FAU - Xue, Xiaonan
AU  - Xue X
AD  - Division of Biostatistics, Department Epidemiology and Population Health, Albert 
      Einstein College of Medicine, Bronx, NY, USA.
FAU - Kim, Mimi Y
AU  - Kim MY
AD  - Division of Biostatistics, Department Epidemiology and Population Health, Albert 
      Einstein College of Medicine, Bronx, NY, USA.
FAU - Wang, Tao
AU  - Wang T
AD  - Division of Biostatistics, Department Epidemiology and Population Health, Albert 
      Einstein College of Medicine, Bronx, NY, USA.
FAU - Kuniholm, Mark H
AU  - Kuniholm MH
AD  - Division of Biostatistics, Department Epidemiology and Population Health, Albert 
      Einstein College of Medicine, Bronx, NY, USA.
FAU - Strickler, Howard D
AU  - Strickler HD
AD  - Division of Biostatistics, Department Epidemiology and Population Health, Albert 
      Einstein College of Medicine, Bronx, NY, USA.
LA  - eng
GR  - U01 AI035004/AI/NIAID NIH HHS/United States
GR  - R01 AI057006/AI/NIAID NIH HHS/United States
GR  - R01 CA174634/CA/NCI NIH HHS/United States
GR  - R01 CA085178/CA/NCI NIH HHS/United States
GR  - P30 CA013330/CA/NCI NIH HHS/United States
PT  - Journal Article
DEP - 20150408
PL  - England
TA  - Stat Methods Med Res
JT  - Statistical methods in medical research
JID - 9212457
RN  - 0 (HLA Antigens)
SB  - IM
MH  - Female
MH  - HIV Infections/*complications/genetics
MH  - HLA Antigens/genetics
MH  - Humans
MH  - Logistic Models
MH  - Longitudinal Studies
MH  - Papillomavirus Infections/complications/genetics/virology
MH  - Randomized Controlled Trials as Topic/*methods
MH  - Risk Factors
MH  - Sample Size
MH  - Uterine Cervical Neoplasms/*complications/genetics/virology
MH  - Uterine Cervical Dysplasia/*complications/genetics/virology
PMC - PMC4879603
MID - NIHMS769198
OTO - NOTNLM
OT  - Correlated data
OT  - exact method
OT  - generalized estimating equation
OT  - permutation
OT  - rare events
COIS- Conflict of interest None declared.
EDAT- 2015/04/10 06:00
MHDA- 2018/05/15 06:00
PMCR- 2016/10/08
CRDT- 2015/04/10 06:00
PHST- 2015/04/10 06:00 [pubmed]
PHST- 2018/05/15 06:00 [medline]
PHST- 2015/04/10 06:00 [entrez]
PHST- 2016/10/08 00:00 [pmc-release]
AID - 0962280215581112 [pii]
AID - 10.1177/0962280215581112 [doi]
PST - ppublish
SO  - Stat Methods Med Res. 2017 Jun;26(3):1416-1428. doi: 10.1177/0962280215581112. 
      Epub 2015 Apr 8.