Practical Aspects of Signal Detection in Pharmacovigilance
by Council for International Organizations of Medical Sciences-
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Summary
Table of Contents
| Preface | p. 7 |
| Introduction and scope of CIOMS VIII | p. 9 |
| Background - pharmacovigilance and key definitions | p. 13 |
| Need for pharmacovigilance after regulatory approval | p. 13 |
| Definition of pharmacovigilance | p. 14 |
| Definition and taxonomy of drug safety signals | p. 14 |
| Conclusions and recommendations | p. 16 |
| Overview of approaches to signal detection | p. 19 |
| Traditional approaches | p. 20 |
| Emergence of statistical data mining methods | p. 21 |
| Conceptual framework for integrating traditional and statistical data mining methods | p. 22 |
| Interpretation of data mining results within an integrated approach | p. 23 |
| Conclusions and recommendations | p. 23 |
| Spontaneously reported drug safety-related information | p. 25 |
| Definitions of adverse event and reaction | p. 25 |
| Data elements in a spontaneous reporting system | p. 25 |
| Mechanisms for reporting | p. 27 |
| Patient and consumer reporting | p. 28 |
| Limitations and challenges of spontaneous data | p. 30 |
| Reporting in special populations | p. 32 |
| Conclusions and recommendations | p. 32 |
| Databases that support signal detection | p. 35 |
| Spontaneous reporting databases | p. 36 |
| Other datasets that can be used for signal detection | p. 37 |
| Data quality | p. 39 |
| Pharmacoepidemiology resources | p. 39 |
| Conclusions and recommendations | p. 40 |
| Traditional methods of signal detection | p. 43 |
| Case and case series review | p. 43 |
| Simple analyses of larger datasets | p. 45 |
| Conclusions and recommendations | p. 47 |
| More complex quantitative signal detection methods | p. 49 |
| History | p. 49 |
| Disproportionality analysis - general concepts and caveats | p. 49 |
| Theory of disproportionality analysis | p. 53 |
| Basic methodologies and metrics | p. 53 |
| Bayesian methodologies | p. 55 |
| Frequentist versus Bayesian approaches | p. 59 |
| Evaluating data mining performance | p. 59 |
| Disclosure and review of potential conflict of interest | p. 62 |
| Conclusions and recommendations | p. 62 |
| How to develop a signal detection strategy | p. 67 |
| Stakeholder perspectives | p. 67 |
| Expectations of consumers | p. 67 |
| Expectations of prescribers | p. 68 |
| Expectations of government regulators | p. 68 |
| Expectations for pharmaceutical companies (sponsors) | p. 68 |
| Regulatory considerations and international guidance | p. 69 |
| Pre-marketing signal detection | p. 69 |
| Post-marketing surveillance | p. 70 |
| Value added for integrating data mining methods into a signal detection program | p. 70 |
| Practical, technical and strategic points to consider | p. 71 |
| Selection of data types and sources | p. 71 |
| Attributes of the data | p. 73 |
| Attributes of drugs under monitoring | p. 75 |
| Attributes of patient populations under monitoring | p. 76 |
| Choosing specifications for a quantitative signalling approach | p. 76 |
| Operational model and organizational infrastructure | p. 79 |
| Guiding principles | p. 79 |
| Design and implementation of data management systems | p. 79 |
| Quality assurance for the signal detection program | p. 82 |
| Guiding principles | p. 82 |
| Measures of effectiveness and efficiency | p. 82 |
| Compliance | p. 83 |
| Conclusions and recommendations | p. 84 |
| Overview of signal management | p. 87 |
| Signal prioritization | p. 88 |
| Impact analysis | p. 88 |
| Further signal prioritization | p. 89 |
| Signal evaluation | p. 89 |
| Obtaining a consistent approach across all sources of safety data | p. 90 |
| Assessing the strength of evidence from immediately available sources | p. 90 |
| Options analysis | p. 93 |
| Potential risk | p. 93 |
| Identified risk | p. 94 |
| Reporting and communicating signals | p. 95 |
| Expectations for risk management planning | p. 96 |
| Conclusions and recommendations | p. 97 |
| Future directions in signal detection, evaluation and communication | p. 101 |
| Wider considerations | p. 101 |
| New directions in data mining algorithms (DMAs) | p. 101 |
| Sensitivity and specificity | p. 101 |
| Denominators | p. 102 |
| Screening for drug-drug interactions | p. 102 |
| Confirmatory data analysis | p. 102 |
| Data mining in non-SRS datasets | p. 103 |
| Computerized longitudinal healthcare databases | p. 103 |
| Sequential monitoring | p. 103 |
| Cross-sectional screening or data mining | p. 104 |
| Continuous disproportionality screening | p. 104 |
| Data mining, meta-analysis and clinical trial datasets | p. 104 |
| Use of ICSRs to evaluate impact of risk minimization | p. 105 |
| Communication of signal information | p. 105 |
| Message content and delivery | p. 105 |
| Timing of signal communication | p. 106 |
| Conclusions and recommendations | p. 106 |
| Appendices | p. 109 |
| Glossary and acronyms | p. 109 |
| Membership and working procedures of CIOMS Working Group VIII | p. 119 |
| International and national spontaneous reporting systems (SRS) databases | p. 121 |
| Epidemiologic studies | p. 137 |
| Points to consider regarding differences between vaccines and drugs in signal detection | p. 139 |
| Table of Contents provided by Ingram. All Rights Reserved. |
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