Novel Data-Mining Methodologies for Adverse Drug Event Discovery and Analysis

被引：263

作者：

Harpaz, R. ^{[1
]}

DuMouchel, W. ^{[2
,3
]}

Shah, N. H. ^{[4
]}

Madigan, D. ^{[3
,5
]}

Ryan, P. ^{[3
,6
]}

Friedman, C. ^{[1
]}

机构：

[1] Columbia Univ, Med Ctr, Dept Biomed Informat, New York, NY 10027 USA

[2] Oracle Hlth Sci, Burlington, MA USA

[3] Fdn Natl Inst Hlth, Bethesda, MD USA

[4] Stanford Univ, Stanford Ctr Biomed Informat Res, Stanford, CA 94305 USA

[5] Columbia Univ, Dept Stat, New York, NY USA

[6] Janssen Res & Dev, Titusville, NJ USA

来源：

CLINICAL PHARMACOLOGY & THERAPEUTICS | 2012年 / 91卷 / 06期

关键词：

SIGNAL-DETECTION; HOSPITALIZED-PATIENTS; SAFETY; SURVEILLANCE; DATABASES; NETWORK; DESIGN; INFORMATION; ALGORITHMS; SYSTEMS;

D O I：

10.1038/clpt.2012.50

中图分类号：

R9 [药学];

学科分类号：

1007 ;

摘要：

An important goal of the health system is to identify new adverse drug events (ADEs) in the postapproval period. Data-mining methods that can transform data into meaningful knowledge to inform patient safety have proven essential for this purpose. New opportunities have emerged to harness data sources that have not been used within the traditional framework. This article provides an overview of recent methodological innovations and data sources used to support ADE discovery and analysis.

引用

页码：1010 / 1021

页数：12

共 72 条

[1]

Agrawal R., 1993, SIGMOD Record, V22, P207, DOI 10.1145/170036.170072

[2] Adverse drug event monitoring at the Food and Drug Administration - Your report can make a difference [J].

Ahmad, SR .

JOURNAL OF GENERAL INTERNAL MEDICINE, 2003, 18 (01) :57-60

[3] Novel statistical tools for monitoring the safety of marketed drugs [J].

Almenoff, J. S. ;

Pattishall, E. N. ;

Gibbs, T. G. ;

DuMouchel, W. ;

Evans, S. J. W. ;

Yuen, N. .

CLINICAL PHARMACOLOGY & THERAPEUTICS, 2007, 82 (02) :157-166

[4] Disproportionality analysis using empirical Bayes data mining: a tool for the evaluation of drug interactions in the post-marketing setting [J].

Almenoff, JS ;

DuMouchel, W ;

Kindman, LA ;

Yang, XH ;

Fram, D .

PHARMACOEPIDEMIOLOGY AND DRUG SAFETY, 2003, 12 (06) :517-521

[5]

[Anonymous], SENT IN NAT STRAT MO

[6] Managing Drug-Risk Information - What to Do with All Those New Numbers [J].

Avorn, Jerry ;

Schneeweiss, Sebastian .

NEW ENGLAND JOURNAL OF MEDICINE, 2009, 361 (07) :647-649

[7] Can Network Analysis Improve Pattern Recognition Among Adverse Events Following Immunization Reported to VAERS? [J].

Ball, R. ;

Botsis, T. .

CLINICAL PHARMACOLOGY & THERAPEUTICS, 2011, 90 (02) :271-278

[8] Quantitative signal detection using spontaneous ADR reporting [J].

Bate, A. ;

Evans, S. J. W. .

PHARMACOEPIDEMIOLOGY AND DRUG SAFETY, 2009, 18 (06) :427-436

[9] A Bayesian neural network method for adverse drug reaction signal generation [J].

Bate, A ;

Lindquist, M ;

Edwards, IR ;

Olsson, S ;

Orre, R ;

Lansner, A ;

De Freitas, RM .

EUROPEAN JOURNAL OF CLINICAL PHARMACOLOGY, 1998, 54 (04) :315-321

[10] Pharmacogenomics of adverse drug reactions: practical applications and perspectives [J].

Becquemont, Laurent .

PHARMACOGENOMICS, 2009, 10 (06) :961-969

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