A Benefit–Risk Analysis Approach to Capture Regulatory Decision‐Making: Multiple Myeloma

Abstract

Drug regulators around the world make decisions about drug approvability based on qualitative benefit–risk analysis. In this work, a quantitative benefit–risk analysis approach captures regulatory decision‐making about new drugs to treat multiple myeloma (MM). MM assessments have been based on endpoints such as time to progression (TTP), progression‐free survival (PFS), and objective response rate (ORR) which are different than benefit–risk analysis based on overall survival (OS). Twenty‐three FDA decisions on MM drugs submitted to FDA between 2003 and 2016 were identified and analyzed. The benefits and risks were quantified relative to comparators (typically the control arm of the clinical trial) to estimate whether the median benefit–risk was positive or negative. A sensitivity analysis was demonstrated using ixazomib to explore the magnitude of uncertainty. FDA approval decision outcomes were consistent and logical using this benefit–risk framework.

Exposure–Response‐Based Product Profile–Driven Clinical Utility Index for Ipatasertib Dose Selection in Prostate Cancer

“…In this study, the CUI analysis did allow more transparent and efficient decision making for the phase III dose selection. Beyond dose selection, the CUI can also be applied to support other key decision making in drug development and regulatory evaluation …”

“…built on the US Food and Drug Administration qualitative benefit‐risk framework by combining benefits and risks in terms of a common metric (e.g., gain in adjusted years of remaining life vs. placebo), which is equivalent to a CUI. These articles reviewed the Food and Drug Administration decisions on drugs for multiple myeloma, non‐small cell lung cancer, multiple sclerosis, and tuberculosis …”

Using a Benefit–Risk Analysis Approach to Capture Regulatory Decision Making: Renal Cell Carcinoma

“…The rationale for using median OS as the measure of benefit in this work is similar to that of prior work and includes the intuitiveness of the median OS metric to the patient. Further, as seen in prior work, improvements in median OS or PFS over the control generally are reflected in lower hazard ratios, as seen in the Benefits, Risks, and Decisions section.…”

“…A benefit is a desirable (or positive) effect of a therapy (e.g., increase in duration of life and/or in quality of life) . This work, similar to prior work, uses median OS (directly measured or estimated as described below) as the measure of benefit.…”

“…In prior work, a quantitative benefit–risk analysis approach was proposed and used for analysis of regulatory decision making in NDAs and BLAs for treatment of patients with non‐small cell lung cancer and multiple myeloma . In this work, that approach is applied to renal cell carcinoma (RCC).…”