Practical Aspects of Signal Detection in Pharmacovigilance

by
Edition: 1st
Format: Paperback
Pub. Date: 2010-09-30
Publisher(s): Stylus Pub Llc
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Summary

In recent years public expectations for rapid identification and prompt management of emerging drug safety issues have grown swiftly. Over a similar timeframe, the move from paper-based adverse event reporting systems to electronic capture and rapid transmission of data has resulted in the accrual of substantial datasets capable of complex analysis and querying by industry, regulators and other public health organizations. These two drivers have created a fertile environment for pharmacovigilance scientists, information technologists and statistical experts, working together, to deliver novel approaches to detect signals from these extensive and quickly growing datasets, and to manage them appropriately. In following this exciting story, this report looks at the practical consequences of these developments for pharmacovigilance practitioners. The report aims primarily to provide a comprehensive resource for those considering how to strengthen their pharmacovigilance systems and practices, and to give practical advice. But the report does not specify instant solutions. These will inevitably be situation specific and require careful consideration taking into account local needs. However, the CIOMS Working Group VIII is convinced that the combination of methods and a clear policy on the management of signals will strengthen current systems. Finally, in looking ahead, the report anticipates a number of ongoing developments, including techniques with wider applicability to other data forms than individual case reports. The ultimate test for pharmacovigilance systems is the demonstration of public health benefit and it is this test which signal detection methodologies need to meet if the expectations of all stakeholders are to be fulfilled.

Table of Contents

Prefacep. 7
Introduction and scope of CIOMS VIIIp. 9
Background - pharmacovigilance and key definitionsp. 13
Need for pharmacovigilance after regulatory approvalp. 13
Definition of pharmacovigilancep. 14
Definition and taxonomy of drug safety signalsp. 14
Conclusions and recommendationsp. 16
Overview of approaches to signal detectionp. 19
Traditional approachesp. 20
Emergence of statistical data mining methodsp. 21
Conceptual framework for integrating traditional and statistical data mining methodsp. 22
Interpretation of data mining results within an integrated approachp. 23
Conclusions and recommendationsp. 23
Spontaneously reported drug safety-related informationp. 25
Definitions of adverse event and reactionp. 25
Data elements in a spontaneous reporting systemp. 25
Mechanisms for reportingp. 27
Patient and consumer reportingp. 28
Limitations and challenges of spontaneous datap. 30
Reporting in special populationsp. 32
Conclusions and recommendationsp. 32
Databases that support signal detectionp. 35
Spontaneous reporting databasesp. 36
Other datasets that can be used for signal detectionp. 37
Data qualityp. 39
Pharmacoepidemiology resourcesp. 39
Conclusions and recommendationsp. 40
Traditional methods of signal detectionp. 43
Case and case series reviewp. 43
Simple analyses of larger datasetsp. 45
Conclusions and recommendationsp. 47
More complex quantitative signal detection methodsp. 49
Historyp. 49
Disproportionality analysis - general concepts and caveatsp. 49
Theory of disproportionality analysisp. 53
Basic methodologies and metricsp. 53
Bayesian methodologiesp. 55
Frequentist versus Bayesian approachesp. 59
Evaluating data mining performancep. 59
Disclosure and review of potential conflict of interestp. 62
Conclusions and recommendationsp. 62
How to develop a signal detection strategyp. 67
Stakeholder perspectivesp. 67
Expectations of consumersp. 67
Expectations of prescribersp. 68
Expectations of government regulatorsp. 68
Expectations for pharmaceutical companies (sponsors)p. 68
Regulatory considerations and international guidancep. 69
Pre-marketing signal detectionp. 69
Post-marketing surveillancep. 70
Value added for integrating data mining methods into a signal detection programp. 70
Practical, technical and strategic points to considerp. 71
Selection of data types and sourcesp. 71
Attributes of the datap. 73
Attributes of drugs under monitoringp. 75
Attributes of patient populations under monitoringp. 76
Choosing specifications for a quantitative signalling approachp. 76
Operational model and organizational infrastructurep. 79
Guiding principlesp. 79
Design and implementation of data management systemsp. 79
Quality assurance for the signal detection programp. 82
Guiding principlesp. 82
Measures of effectiveness and efficiencyp. 82
Compliancep. 83
Conclusions and recommendationsp. 84
Overview of signal managementp. 87
Signal prioritizationp. 88
Impact analysisp. 88
Further signal prioritizationp. 89
Signal evaluationp. 89
Obtaining a consistent approach across all sources of safety datap. 90
Assessing the strength of evidence from immediately available sourcesp. 90
Options analysisp. 93
Potential riskp. 93
Identified riskp. 94
Reporting and communicating signalsp. 95
Expectations for risk management planningp. 96
Conclusions and recommendationsp. 97
Future directions in signal detection, evaluation and communicationp. 101
Wider considerationsp. 101
New directions in data mining algorithms (DMAs)p. 101
Sensitivity and specificityp. 101
Denominatorsp. 102
Screening for drug-drug interactionsp. 102
Confirmatory data analysisp. 102
Data mining in non-SRS datasetsp. 103
Computerized longitudinal healthcare databasesp. 103
Sequential monitoringp. 103
Cross-sectional screening or data miningp. 104
Continuous disproportionality screeningp. 104
Data mining, meta-analysis and clinical trial datasetsp. 104
Use of ICSRs to evaluate impact of risk minimizationp. 105
Communication of signal informationp. 105
Message content and deliveryp. 105
Timing of signal communicationp. 106
Conclusions and recommendationsp. 106
Appendicesp. 109
Glossary and acronymsp. 109
Membership and working procedures of CIOMS Working Group VIIIp. 119
International and national spontaneous reporting systems (SRS) databasesp. 121
Epidemiologic studiesp. 137
Points to consider regarding differences between vaccines and drugs in signal detectionp. 139
Table of Contents provided by Ingram. All Rights Reserved.

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