PMID- 32572773
OWN - NLM
STAT- MEDLINE
DCOM- 20210603
LR  - 20210603
IS  - 2168-4804 (Electronic)
IS  - 2168-4790 (Linking)
VI  - 55
IP  - 1
DP  - 2021 Jan
TI  - Spatial-Cluster Signal Detection in Medical Devices Using Likelihood Ratio Test 
      Method.
PG  - 56-64
LID - 10.1007/s43441-020-00190-8 [doi]
AB  - BACKGROUND: With more and more medical device databases being developed, there is 
      an increasing interest in learning the geographical patterns of 
      medical-device-related adverse events (AEs). For a specific medical device and an 
      adverse event (AE) of interest, our aim is to detect a spatial-cluster signal 
      that has a significantly higher AE rate than the AE rates for other regions, when 
      the exposure information is available. METHODS: We develop a likelihood ratio 
      test (LRT) method incorporating exposure information, by geographical region, for 
      spatial-cluster signal detection when the underlying observed health outcome 
      associated with the medical device of interest is a Poisson-modeled count data 
      (e.g., an outcome of AE count). RESULTS: An extensive simulation study shows that 
      this method has good power, sensitivity, specificity, positive predictive value 
      (PPV) and negative predictive value (NPV). The application of the method is 
      demonstrated by two hypothetical case studies regarding a medical device that is 
      used for patients who have reached end-stage heart failure. DISCUSSION: A 
      methodological framework for exploring geographic patterns in device safety 
      surveillance is discussed, including safety data collection, statistical tools, 
      and display of the analysis results. The proposed statistical method can be used 
      for spatial-cluster signal detection for an AE of interest from medical device 
      registries or other databases that have patient-level geographical information.
FAU - Hu, Tingting
AU  - Hu T
AD  - U.S. Food and Drug Administration, Silver Spring, MD, USA. tingting.hu@erau.edu.
AD  - Embry-Riddle Aeronautical University, Daytona Beach, FL, USA. 
      tingting.hu@erau.edu.
FAU - Huang, Lan
AU  - Huang L
AD  - U.S. Food and Drug Administration, Silver Spring, MD, USA. lan.huang@fda.hhs.gov.
FAU - Xu, Jianjin
AU  - Xu J
AD  - U.S. Food and Drug Administration, Silver Spring, MD, USA.
FAU - Tiwari, Ram
AU  - Tiwari R
AD  - U.S. Food and Drug Administration, Silver Spring, MD, USA.
LA  - eng
PT  - Journal Article
DEP - 20200622
PL  - Switzerland
TA  - Ther Innov Regul Sci
JT  - Therapeutic innovation & regulatory science
JID - 101597411
SB  - IM
MH  - Computer Simulation
MH  - Databases, Factual
MH  - Humans
MH  - Likelihood Functions
MH  - *Research Design
OTO - NOTNLM
OT  - Exposure information
OT  - Medical device safety data
OT  - Safety surveillance
OT  - Spatial-cluster signal
EDAT- 2020/06/24 06:00
MHDA- 2021/06/04 06:00
CRDT- 2020/06/24 06:00
PHST- 2020/03/10 00:00 [received]
PHST- 2020/06/11 00:00 [accepted]
PHST- 2020/06/24 06:00 [pubmed]
PHST- 2021/06/04 06:00 [medline]
PHST- 2020/06/24 06:00 [entrez]
AID - 10.1007/s43441-020-00190-8 [pii]
AID - 10.1007/s43441-020-00190-8 [doi]
PST - ppublish
SO  - Ther Innov Regul Sci. 2021 Jan;55(1):56-64. doi: 10.1007/s43441-020-00190-8. Epub 
      2020 Jun 22.