Lecture 7: Pharmacoepidemiology: risk-benefit analysis and meta analysis Flashcards Preview

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Flashcards in Lecture 7: Pharmacoepidemiology: risk-benefit analysis and meta analysis Deck (16):
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Introduction to Risk Benefit Assessment (RBA)

Risk and benefit assessment monitoring are significant contributors to promoting safety and quality in the delivery of health care

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RBA (What is it?)

Quantitative methods for systematically evaluating the risks and benefits of new or existing medical interventions

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RBA (Why?)

These methods evaluate risk-benefit tradeoffs to assist regulatory and clinical decision making in the absence of directly comparable metrics

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RBA (Who?)

Regulators, clinicians and patients who routinely make decisions that require trading safety for desired clinical benefits

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Benefits

-any favorable outcome of the research to society or to the individual

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Risks

-refers both to the probability of a harm resulting from an activity and also to its magnitude (its HR, IRR, AEs)

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Challenges of RBA

-Heterogeneity of metrics (few common denominators)
-Multiplicity (multiple benefits and risks)
-Uncertainty (temporality)
-Paucity of data (exposure: patients and time distribution and outcomes)

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Some metrics of RBA

-NNT, QALYs (quality of life)

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Risk Management

1) Risk identification
2) Risk assessment
3) Risk prioritization and communication (improve collective and individual decision making)

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Current approaches to RBA

-there is no single approach to RBA, so regulatory bodies in the US and abroad are looking for ways to standardize it

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Problem states in RBA

-development strategies (when does increased benefit outweigh potential increased risk)
-regulatory approval (how do you know if risk outweighs benefit?)
-risk management (when do you require risk/benefit plans)

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Quantitative Approches and Techniques for RBA

1) Quantitative framework for risk and benefit assessment (QFRBA)
2) Beneft-less risk analysis (BLRA)
3) Quality adjusted time without symptoms and toxicity (Q-TWIST)
4) Number needed to treat (NNT) vs. Number Needed to Harm (NNH)
5) Relative Value adjusted number needed to treat (RV-NNT)
6) Minimum Clinical Efficacy (MCE)
7) Incremental Net Health Benefit (INHB)
8) Risk Benefit Plane (RBP) and Risk Benefit Acceptability Threshold (RBAT)
9) Probabilistic Simulation Methods (PSM)
10) Multi-Criteria Decision Analysis (MCDA)
11) Risk-Benefit Contour (RBC)

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RBA Framework

Measure background benefit, characterize background risk, design study, analyze relative risk benefit, communicate risk benefit to FDA all to optimize risk benefit of drug of interest

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Optimizing benefit-risk profile

demonstrate product benefit, characterize risk, quantify the benefit/risk, ensure appropriate use and communicate benefit/risk to stakeholders

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Conclusions

-Quantitative RBA and meta-analytic methods supplement, but do not replace the existing paradigms used by regulators and researchers
-New methods should be mathematically sound, involve relatively straight-forward computations and enhance the scientific validity of the current RB assessment
-multiple RBA techniques may be developed to triangulate the risk benefit profile of a product

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Points to Consider

-Deploy RBA as a continuous feedback cycle starting early in clinical development
-engage stakeholders to better understand and participate in RBA
-focus on the patient perspective when appraising risk-benefit