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An evaluation of a data mining signal for amyotrophic lateral sclerosis and statins detected in FDA's spontaneous adverse event reporting system by Eric Colman; Ana Szarfman; Jo Wyeth; Andrew Mosholder; Devanand Jillapalli; Jonathan Levine; Mark Avigan is a Medicine article available to read on EtoBox.

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## Abstract ## Background We detected disproportionate reporting of amyotrophic lateral sclerosis (ALS) with HMG‐CoA‐reductase inhibitors (statins) in the Food and Drug Administration's (FDA) spontaneous adverse event (AE) reporting system (AERS). ## Purpose To describe the original ALS signal and to provide additional context for interpreting the signal by conducting retrospective analyses of data from long‐term, placebo‐controlled clinical trials of statins. ## Methods The ALS signal was detected using the multi‐item gamma Poisson shrinker (MGPS) algorithm. All AERS cases of ALS reported in association with use of a statin were individually reviewed by two FDA neurologists. Manufacturers of lovastatin, pravastatin, simvastatin, fluvastatin, atorvastatin, cerivastatin, and rosuvastatin were requested to provide the number of cases of ALS diagnosed during all of their placebo‐controlled statin trials that were at least 6 months in duration. ## Results There were 91 US and foreign reports of ALS with statins in AERS. The data mining signal scores for ALS and statins ranged from 8.5 to 1.6. Data were obtained from 41 statin clinical trials ranging in duration from 6 months to 5 years

Who reads An evaluation of a data mining signal for amyotrophic lateral sclerosis and statins detected in FDA's spontaneous adverse event reporting system?

Author

Eric Colman; Ana Szarfman; Jo Wyeth; Andrew Mosholder; Devanand Jillapalli; Jonathan Levine; Mark Avigan

Publisher

John Wiley and Sons; Wiley (John Wiley & Sons); John Wiley & Sons Inc.; Wiley (ISSN 1053-8569)

Published

2008

Language

EN

Field

Medicine (Health Sciences)