PMID- 38297431
OWN - NLM
STAT- MEDLINE
DCOM- 20240318
LR  - 20240318
IS  - 1097-0258 (Electronic)
IS  - 0277-6715 (Linking)
VI  - 43
IP  - 7
DP  - 2024 Mar 30
TI  - Safety signal detection with control of latent factors.
PG  - 1397-1418
LID - 10.1002/sim.10015 [doi]
AB  - Postmarket drug safety database like vaccine adverse event reporting system 
      (VAERS) collect thousands of spontaneous reports annually, with each report 
      recording occurrences of any adverse events (AEs) and use of vaccines. We hope to 
      identify signal vaccine-AE pairs, for which certain vaccines are statistically 
      associated with certain adverse events (AE), using such data. Thus, the outcomes 
      of interest are multiple AEs, which are binary outcomes and could be correlated 
      because they might share certain latent factors; and the primary covariates are 
      vaccines. Appropriately accounting for the complex correlation among AEs could 
      improve the sensitivity and specificity of identifying signal vaccine-AE pairs. 
      We propose a two-step approach in which we first estimate the shared latent 
      factors among AEs using a working multivariate logistic regression model, and 
      then use univariate logistic regression model to examine the vaccine-AE 
      associations after controlling for the latent factors. Our simulation studies 
      show that this approach outperforms current approaches in terms of sensitivity 
      and specificity. We apply our approach in analyzing VAERS data and report our 
      findings.
CI  - (c) 2024 John Wiley & Sons Ltd.
FAU - Tan, Xianming
AU  - Tan X
AUID- ORCID: 0000-0002-5478-2269
AD  - Department of Biostatistics at Gillings School of Global Public Health, 
      University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
AD  - Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel 
      Hill, Chapel Hill, North Carolina, USA.
FAU - Wang, William
AU  - Wang W
AD  - Merck and Co., Inc., North Wales, Pennsylvania, USA.
FAU - Zeng, Donglin
AU  - Zeng D
AD  - Department of Biostatistics at Gillings School of Global Public Health, 
      University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
FAU - Liu, Guanghan F
AU  - Liu GF
AUID- ORCID: 0000-0001-7817-7656
AD  - Merck and Co., Inc., North Wales, Pennsylvania, USA.
FAU - Diao, Guoqing
AU  - Diao G
AUID- ORCID: 0000-0001-7304-9591
AD  - Department of Biostatistics and Bioinformatics, Milken Institute School of Public 
      Health, George Washington University, Washington, DC, USA.
FAU - Jafari, Niusha
AU  - Jafari N
AD  - Merck and Co., Inc., North Wales, Pennsylvania, USA.
FAU - Alt, Ethan M
AU  - Alt EM
AUID- ORCID: 0000-0002-6112-9030
AD  - Department of Biostatistics at Gillings School of Global Public Health, 
      University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
FAU - Ibrahim, Joseph G
AU  - Ibrahim JG
AUID- ORCID: 0000-0003-2428-6552
AD  - Department of Biostatistics at Gillings School of Global Public Health, 
      University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
LA  - eng
PT  - Journal Article
DEP - 20240131
PL  - England
TA  - Stat Med
JT  - Statistics in medicine
JID - 8215016
RN  - 0 (Vaccines)
SB  - IM
MH  - Humans
MH  - United States
MH  - *Adverse Drug Reaction Reporting Systems
MH  - *Vaccines/adverse effects
MH  - Databases, Factual
MH  - Computer Simulation
MH  - Software
OTO - NOTNLM
OT  - VAERS
OT  - generalized linear mixed models
OT  - multivariate logistic regression model
OT  - signal detection
OT  - variational inference (VI) method
EDAT- 2024/02/01 00:43
MHDA- 2024/03/18 06:43
CRDT- 2024/01/31 23:53
PHST- 2023/10/26 00:00 [revised]
PHST- 2023/01/23 00:00 [received]
PHST- 2023/12/27 00:00 [accepted]
PHST- 2024/03/18 06:43 [medline]
PHST- 2024/02/01 00:43 [pubmed]
PHST- 2024/01/31 23:53 [entrez]
AID - 10.1002/sim.10015 [doi]
PST - ppublish
SO  - Stat Med. 2024 Mar 30;43(7):1397-1418. doi: 10.1002/sim.10015. Epub 2024 Jan 31.