PMID- 28346083
OWN - NLM
STAT- MEDLINE
DCOM- 20180730
LR  - 20180730
IS  - 1520-5711 (Electronic)
IS  - 1054-3406 (Linking)
VI  - 27
IP  - 6
DP  - 2017
TI  - Logistic Regression Likelihood Ratio Test Analysis for Detecting Signals of 
      Adverse Events in Post-market Safety Surveillance.
PG  - 990-1008
LID - 10.1080/10543406.2017.1295250 [doi]
AB  - The Vaccine Adverse Event Reporting System (VAERS) and other product surveillance 
      systems compile reports of product-associated adverse events (AEs), and these 
      reports may include a wide range of information including age, gender, and 
      concomitant vaccines. Controlling for possible confounding variables such as 
      these is an important task when utilizing surveillance systems to monitor 
      post-market product safety. A common method for handling possible confounders is 
      to compare observed product-AE combinations with adjusted baseline frequencies 
      where the adjustments are made by stratifying on observable characteristics. 
      Though approaches such as these have proven to be useful, in this article we 
      propose a more flexible logistic regression approach which allows for covariates 
      of all types rather than relying solely on stratification. Indeed, a main 
      advantage of our approach is that the general regression framework provides 
      flexibility to incorporate additional information such as demographic factors and 
      concomitant vaccines. As part of our covariate-adjusted method, we outline a 
      procedure for signal detection that accounts for multiple comparisons and 
      controls the overall Type 1 error rate. To demonstrate the effectiveness of our 
      approach, we illustrate our method with an example involving febrile convulsion, 
      and we further evaluate its performance in a series of simulation studies.
FAU - Nam, Kijoeng
AU  - Nam K
AD  - a Merck Research Labs, Merck & Co., Inc, North Wales, Pennsylvania, USA.
FAU - Henderson, Nicholas C
AU  - Henderson NC
AD  - b Department of Oncology, Sidney Kimmel Comprehensive Cancer Center , Johns 
      Hopkins University, Baltimore, Maryland, USA.
FAU - Rohan, Patricia
AU  - Rohan P
AD  - c Division of Epidemiology, Office of Biostatistics and Epidemiology , CBER , FDA 
      , Silver Spring, Maryland, USA.
FAU - Woo, Emily Jane
AU  - Woo EJ
AD  - c Division of Epidemiology, Office of Biostatistics and Epidemiology , CBER , FDA 
      , Silver Spring, Maryland, USA.
FAU - Russek-Cohen, Estelle
AU  - Russek-Cohen E
AD  - d Division of Biostatistics, Office of Biostatistics and Epidemiology , CBER , 
      FDA , Silver Spring, Maryland, USA.
LA  - eng
PT  - Journal Article
DEP - 20170327
PL  - England
TA  - J Biopharm Stat
JT  - Journal of biopharmaceutical statistics
JID - 9200436
RN  - 0 (Influenza Vaccines)
SB  - IM
MH  - Adverse Drug Reaction Reporting Systems/standards/*statistics & numerical data
MH  - Humans
MH  - Influenza Vaccines/*adverse effects
MH  - Likelihood Functions
MH  - Logistic Models
MH  - Product Surveillance, Postmarketing/standards/*statistics & numerical data
MH  - Vaccination/*adverse effects/standards/*statistics & numerical data
OTO - NOTNLM
OT  - Adverse event
OT  - VAERS
OT  - febrile convulsion
OT  - signal detection
OT  - vaccine safety
EDAT- 2017/03/28 06:00
MHDA- 2018/07/31 06:00
CRDT- 2017/03/28 06:00
PHST- 2017/03/28 06:00 [pubmed]
PHST- 2018/07/31 06:00 [medline]
PHST- 2017/03/28 06:00 [entrez]
AID - 10.1080/10543406.2017.1295250 [doi]
PST - ppublish
SO  - J Biopharm Stat. 2017;27(6):990-1008. doi: 10.1080/10543406.2017.1295250. Epub 
      2017 Mar 27.