Abstract
Unlike conventional cancer treatment, immuno-oncology therapies are commonly associated with delayed clinical benefit and durable responses, as seen with immuno-oncology therapies for multiple myeloma (MM). Therefore, a longer-term approach to immuno-oncology data assessment is required. Appropriate study designs, end points and statistical methods are essential for evaluating immuno-oncology therapies to assess treatment outcomes, and may better accommodate immuno-oncology clinical trial data. In addition to conventional end points including median progression-free survival (PFS) and overall survival (OS), end points such as hazard ratios for PFS and OS over time, PFS and OS landmark analyses beyond the median, and immune-response end points might provide better indications of the efficacy of immuno-oncology therapies. Long-term data with these agents will allow better prediction of outcomes in MM.