Benefit-Risk Analysis

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Abstract
Given the current status of benefit-risk analysis as a largely qualitative method, two techniques for a quantitative synthesis of a drug’s benefit and risk are proposed to allow a more objective approach. The recommended methods, relative-value adjusted number-needed-to-treat (RV-NNT) and its extension, minimum clinical efficacy (MCE) analysis, rely upon efficacy or effectiveness data, adverse event data and utility data from patients, describing their preferences for an outcome given potential risks. These methods, using hypothetical data for rheumatoid arthritis drugs, demonstrate that quantitative distinctions can be made between drugs which would better inform clinicians, drug regulators and patients about a drug’s benefit-risk profile. If the number of patients needed to treat is less than the relative-value adjusted number-needed-to-harm in an RV-NNT analysis, patients are willing to undergo treatment with the experimental drug to derive a certain benefit knowing that they may be at risk for any of a series of potential adverse events. Similarly, the results of an MCE analysis allow for determining the worth of a new treatment relative to an older one, given not only the potential risks of adverse events and benefits that may be gained, but also by taking into account the risk of disease without any treatment. Quantitative methods of benefit-risk analysis have a place in the evaluative armamentarium of pharmacovigilance, especially those that incorporate patients’ perspectives.