Using a Benefit–Risk Analysis Approach to Capture Regulatory Decision Making: Melanoma

Abstract

Drug regulators seek to make decisions regarding drug approvals based on analysis of the relevant benefits and risks. In this work, 25 US Food and Drug Administration (FDA) decisions on melanoma drugs were identified and analyzed based on clinical trial results published between 1999 and 2017. In each case, the benefits and risks of the new drug in each clinical trial relative to a comparator (typically the control arm of the same clinical trial) were quantified. The benefits and risks were analyzed using a common scale to allow for direct comparison. A sensitivity analysis was conducted using vemurafenib to explore the magnitude of uncertainty in the quantitative assessments. The associated FDA decision outcomes of the new drugs were consistent with the benefits and risks quantified in this work.Drug regulatory agencies base drug approval decisions on the benefits and risks of a drug (see representative quotations in Table S1). Benefit-risk assessment approaches 1,2 are valuable in providing a clear set of expectations and also have the potential to support the accessibility of safe and effective medicines to patients over the product lifecycle as new information becomes available. [3][4][5] As part of the Prescription Drug User Fee Act and the US Food and Drug Administration's (FDA) Safety and Innovation Act, the FDA committed to structuring their assessments of new drug applications and biological license applications as benefit-risk assessments. In prior work, a framework for such assessments was proposed 6 and used for analysis of FDA decision-making in new drug applications and biological license applications for the disease areas of non-small cell lung cancer (NSCLC) 7 and multiple myeloma. 8 In this work, that same approach is applied to the disease area of melanoma of the skin. In prior work on NSCLC 7 overall survival (OS) was used as the measure of benefit. In the prior work on multiple myeloma, 8 because FDA drug decisions were based primarily on other, non-OS metrics, 9 progression-free survival (PFS) was used as the common measure of benefit. In the present work, similar to prior work on NSCLC, 7 OS was used as the common measure of benefit.There were an estimated 1,169,351 people living with melanoma of the skin in the United States in 2014. 10 An estimated 91,270 new cases of and 9, 320 deaths related to melanoma of the skin were projected to occur in the United States in 2018. 11 Melanoma of the skin represented an estimated 5.2% of all new cases of cancer in the United States in 2017.Among patients newly diagnosed with melanoma, 84% are in the local (confined to the primary site) stage of the disease, 9% are in the regional (spread to regional lymph nodes) stage, 4% are in the distant metastatic stage, and the stage of 3% is unknown. The prognosis for melanoma patients varies by the stage of the disease at diagnosis. The 5-year relative survival of patients in the local, regional, and distant stages is 98.5%, 62.9%, and 19.9%, respectively. 10 With the advent of small molecule-targeted therapies...

A Framework for Assessing the Impact of Accelerated Approval

“…The overall benefit of a therapy in a given population will depend on how long it remains in use before it is replaced by superior therapeutic alternatives. [19, 21] The therapeutic alternatives at the time of accelerated approval will influence the initial impact of the AA, while subsequent approvals of other therapies for the same indication and patient population will impact the overall time course of this impact…”

A framework for assessing the impact of accelerated approval

“…Evaluations of the impact of AA do not take place in an innovative vacuum. The overall benefit of a therapy in a given population will depend on how long it remains in use before it is replaced by superior therapeutic alternatives [19,21]. The therapeutic alternatives at the time of accelerated approval will influence the initial impact of the AA, while subsequent approvals of other therapies for the same indication and patient population will impact the overall time course of this impact.…”

Predicting Regulatory Product Approvals Using a Proposed Quantitative Version of FDA’s Benefit–Risk Framework to Calculate Net-Benefit Score and Benefit–Risk Ratio

“…These include probabilistic decision analysis [ 4 ], use of spatial planes [ 5 ], Bayesian approaches [ 6 ], patient preferences [ 7 , 8 ], incremental net health benefit using simulation data [ 9 ], number-needed-to-treat (NNT) and number-needed-to-harm (NNH) [ 10 ], and a variety of other quantitative approaches [ 11 ]. Some notable studies involved the benefit–risk analysis of cancer-related endpoints of pivotal studies from 20 + products for non-small cell lung cancer [ 12 ], multiple myeloma [ 13 ], and melanoma [ 14 ], and another compared the quantitative profile of new chemical entities that were initially approved but subsequently withdrawn from the market [ 15 ]. While many approaches highlighted the features of the product’s benefits and risks and specifically the results of the pivotal studies, none of the reviewed publications factored in the critical contributions of risk management, defined in the BRT, as part of the overall decision-making process.…”