PMID- 24943381
OWN - NLM
STAT- MEDLINE
DCOM- 20150416
LR  - 20211021
IS  - 1556-679X (Electronic)
IS  - 1556-6811 (Print)
IS  - 1556-679X (Linking)
VI  - 21
IP  - 8
DP  - 2014 Aug
TI  - Matched longitudinal analysis of biomarkers associated with survival.
PG  - 1145-52
LID - 10.1128/CVI.00252-14 [doi]
AB  - The identification of host or pathogen factors linked to clinical outcome is a 
      common goal in many animal studies of infectious diseases. When the disease is 
      fatal, statistical analysis of such factors may be biased from missing 
      observations due to deaths. For example, when observations of a subject are 
      censored before completing the intended study period, the complete trajectory 
      will not be observed. Even if the factor is not associated with outcome, 
      comparisons of data from survivors with those from nonsurvivors may lead to the 
      wrong conclusions regarding associations with survival. Comparisons between 
      subjects must account for differing observation lengths for those who survive 
      relative to those who do not. Analyzing data over an interval common to all 
      subjects provides one solution but requires eliminating data, some of which may 
      be informative about the differences between groups. Here, we present a novel 
      approach, matched longitudinal analysis (MLA), for analyzing such data based on 
      matching biomarker intervals for survivors and nonsurvivors. We describe the 
      results from simulation studies and from a study of monkeypox virus infection in 
      nonhuman primates. In our application, MLA identified low monocyte 
      chemoattractant protein-1 (MCP-1) levels as having a statistically significant 
      association with survival, whereas the alternative methods did not identify an 
      association. The method has general application to longitudinal studies that seek 
      to find associations of biomarker changes with survival.
CI  - Copyright (c) 2014, American Society for Microbiology. All Rights Reserved.
FAU - Dodd, Lori E
AU  - Dodd LE
AD  - Biostatistics Research Branch, National Institute of Allergy and Infectious 
      Diseases, National Institutes of Health, Bethesda, Maryland, USA 
      doddl@mail.nih.gov.
FAU - Johnson, Reed F
AU  - Johnson RF
AD  - Emerging Viral Pathogens Section, National Institute of Allergy and Infectious 
      Diseases, National Institutes of Health, Bethesda, Maryland, USA.
FAU - Blaney, Joseph E
AU  - Blaney JE
AD  - Emerging Viral Pathogens Section, National Institute of Allergy and Infectious 
      Diseases, National Institutes of Health, Bethesda, Maryland, USA.
FAU - Follmann, Dean
AU  - Follmann D
AD  - Biostatistics Research Branch, National Institute of Allergy and Infectious 
      Diseases, National Institutes of Health, Bethesda, Maryland, USA.
LA  - eng
GR  - Intramural NIH HHS/United States
PT  - Journal Article
PT  - Research Support, N.I.H., Intramural
DEP - 20140618
PL  - United States
TA  - Clin Vaccine Immunol
JT  - Clinical and vaccine immunology : CVI
JID - 101252125
RN  - 0 (Biomarkers)
RN  - 0 (Chemokine CCL2)
SB  - IM
MH  - Animals
MH  - Biomarkers
MH  - Chemokine CCL2/*blood
MH  - Host-Pathogen Interactions
MH  - Macaca fascicularis
MH  - Matched-Pair Analysis
MH  - Monkeypox virus/*immunology
MH  - Poxviridae Infections/immunology/*mortality/virology
PMC - PMC4135908
EDAT- 2014/06/20 06:00
MHDA- 2015/04/17 06:00
PMCR- 2015/02/01
CRDT- 2014/06/20 06:00
PHST- 2014/06/20 06:00 [entrez]
PHST- 2014/06/20 06:00 [pubmed]
PHST- 2015/04/17 06:00 [medline]
PHST- 2015/02/01 00:00 [pmc-release]
AID - CVI.00252-14 [pii]
AID - 00252-14 [pii]
AID - 10.1128/CVI.00252-14 [doi]
PST - ppublish
SO  - Clin Vaccine Immunol. 2014 Aug;21(8):1145-52. doi: 10.1128/CVI.00252-14. Epub 
      2014 Jun 18.