PMID- 32050050
OWN - NLM
STAT- MEDLINE
DCOM- 20210621
LR  - 20240402
IS  - 1097-0258 (Electronic)
IS  - 0277-6715 (Print)
IS  - 0277-6715 (Linking)
VI  - 39
IP  - 10
DP  - 2020 May 15
TI  - A hierarchical testing approach for detecting safety signals in clinical trials.
PG  - 1541-1557
LID - 10.1002/sim.8495 [doi]
AB  - Detecting safety signals in clinical trial safety data is known to be challenging 
      due to high dimensionality, rare occurrence, weak signal, and complex dependence. 
      We propose a new hierarchical testing approach for analyzing safety data from a 
      typical randomized clinical trial. This approach accounts for the hierarchical 
      structure of adverse events (AEs), that is, AEs are categorized by system organ 
      class (SOC). Our approach contains two steps: the first step tests, for each SOC, 
      whether any AEs within this SOC are differently distributed between treatment 
      arms; and the second step identifies signal AEs from SOCs passing the first step 
      tests. We show the superiority, in terms of power of detecting safety signals 
      given controlled false discovery rate, of the new approach comparing with 
      currently available approaches through simulation studies. We also demonstrate 
      this approach with two real data examples.
CI  - (c) 2020 John Wiley & Sons, Ltd.
FAU - Tan, Xianming
AU  - Tan X
AUID- ORCID: 0000-0002-5478-2269
AD  - Department of Biostatistics, UNC at Chapel Hill, Chapel Hill, North Carolina.
FAU - Chen, Bingshu E
AU  - Chen BE
AD  - Canadian Cancer Trials Group and Department of Public Health Sciences, Queen's 
      University, Kingston, Ontario, Canada.
FAU - Sun, Jianping
AU  - Sun J
AD  - Department of Mathematics and Statistics, UNC at Greensboro, Greensboro, North 
      Carolina.
FAU - Patel, Tejendra
AU  - Patel T
AD  - Division of Pharmacotherapy and Experimental Therapeutics, Eshelman School of 
      Pharmacy, UNC at Chapel Hill, Chapel Hill, North Carolina.
FAU - Ibrahim, Joseph G
AU  - Ibrahim JG
AUID- ORCID: 0000-0003-2428-6552
AD  - Department of Biostatistics, UNC at Chapel Hill, Chapel Hill, North Carolina.
LA  - eng
GR  - P01 CA142538/CA/NCI NIH HHS/United States
GR  - P30 CA016086/CA/NCI NIH HHS/United States
GR  - R01 GM070335/GM/NIGMS NIH HHS/United States
GR  - Natural Sciences and Engineering Research Council of Canada/International
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20200212
PL  - England
TA  - Stat Med
JT  - Statistics in medicine
JID - 8215016
SB  - IM
MH  - Clinical Trials as Topic
MH  - *Computer Simulation
MH  - Humans
PMC - PMC8258607
MID - NIHMS1713893
OTO - NOTNLM
OT  - MiST
OT  - clinical trials
OT  - drug safety
OT  - hierarchical testing
OT  - multiplicity
OT  - signal detection
COIS- CONFLICT OF INTEREST The authors declare no potential conflict of interests.
EDAT- 2020/02/13 06:00
MHDA- 2021/06/22 06:00
PMCR- 2021/07/06
CRDT- 2020/02/13 06:00
PHST- 2018/06/19 00:00 [received]
PHST- 2019/05/01 00:00 [revised]
PHST- 2019/08/16 00:00 [accepted]
PHST- 2020/02/13 06:00 [pubmed]
PHST- 2021/06/22 06:00 [medline]
PHST- 2020/02/13 06:00 [entrez]
PHST- 2021/07/06 00:00 [pmc-release]
AID - 10.1002/sim.8495 [doi]
PST - ppublish
SO  - Stat Med. 2020 May 15;39(10):1541-1557. doi: 10.1002/sim.8495. Epub 2020 Feb 12.