PMID- 15619136
OWN - NLM
STAT- MEDLINE
DCOM- 20050331
LR  - 20181113
IS  - 0031-6970 (Print)
IS  - 0031-6970 (Linking)
VI  - 60
IP  - 10
DP  - 2004 Dec
TI  - Postmarketing surveillance of potentially fatal reactions to oncology drugs: 
      potential utility of two signal-detection algorithms.
PG  - 747-50
AB  - PURPOSE: Several data mining algorithms (DMAs) are being studied in hopes of 
      enhancing screening of large post-marketing safety databases for signals of novel 
      adverse events (AEs). The objective of this study was to apply two DMAs to the 
      United States FDA Adverse Event Reporting System (AERS) database to see whether 
      signals of potentially fatal AEs with cancer drugs might have been identified 
      earlier than with traditional methods. METHODS: Screening algorithms used for 
      analysis were the multi-item gamma Poisson shrinker (MGPS) and proportional 
      reporting ratios (PRRs). Data mining was performed on data from the FDA AERS 
      database. When a signal was identified, it was compared with that in the year in 
      which the event was added to package insert and/or the year a "case series" was 
      published. A recent publication summarizing the time of dissemination of 
      information on potentially fatal AEs to cancer drugs provided the data set for 
      analysis. RESULTS: The peer-reviewed published analysis contained 21 drugs and 26 
      drug-event combinations (DECs) that were considered sufficiently specific for 
      data mining. Twenty-four of the DECs generated a signal of disproportionate 
      reporting with PRRs (6 at 1 year and 16 from 2 years to 18 years prior to either 
      a published "case series" or a package insert change) and 20 with MGPS (3 at 1 
      year and 11 from 2 years to 16 years prior to either a published "case series" or 
      a package insert change). Two DECs did not signal with either DMA. CONCLUSION: At 
      least one commonly cited DMA generated a signal of disproportionate reporting for 
      24 of 26 DECs for selected cancer drugs. For 16 DECs, one could conclude that a 
      signal was generated well in advance (> or =2 years) of standard techniques in 
      use with at least one DMA. DMAs might be useful in supplementing traditional 
      surveillance strategies with oncology drugs and other drugs with similar 
      features. (i.e., drugs that may be approved on an accelerated basis, are known to 
      have serious toxicity, are administered to patients with substantial and 
      complicated comorbid illness, are not available to the general medical community, 
      and may have a high frequency of "off-label" use).
FAU - Hauben, Manfred
AU  - Hauben M
AD  - Pfizer Inc, 150 E. 42nd Street, New York, NY 10017, USA.
FAU - Reich, Lester
AU  - Reich L
FAU - Chung, Stephanie
AU  - Chung S
LA  - eng
PT  - Journal Article
DEP - 20041117
PL  - Germany
TA  - Eur J Clin Pharmacol
JT  - European journal of clinical pharmacology
JID - 1256165
RN  - 0 (Antineoplastic Agents)
SB  - IM
MH  - Adverse Drug Reaction Reporting Systems/*statistics & numerical data
MH  - Algorithms
MH  - Antineoplastic Agents/*adverse effects
MH  - Drug Approval
MH  - Humans
MH  - *Mortality
MH  - Pharmacoepidemiology
MH  - Product Surveillance, Postmarketing/*methods/statistics & numerical data
MH  - Time Factors
MH  - United States
MH  - *United States Food and Drug Administration
EDAT- 2004/12/25 09:00
MHDA- 2005/04/01 09:00
CRDT- 2004/12/25 09:00
PHST- 2004/05/28 00:00 [received]
PHST- 2004/08/27 00:00 [accepted]
PHST- 2004/12/25 09:00 [pubmed]
PHST- 2005/04/01 09:00 [medline]
PHST- 2004/12/25 09:00 [entrez]
AID - 10.1007/s00228-004-0834-0 [doi]
PST - ppublish
SO  - Eur J Clin Pharmacol. 2004 Dec;60(10):747-50. doi: 10.1007/s00228-004-0834-0. 
      Epub 2004 Nov 17.