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- Antje Hoering, Brian Durie, Hongwei Wang, and John Crowley.
- Cancer Research And Biostatistics (CRAB), Seattle, WA, USA.
- Future Oncol. 2017 Jun 1; 13 (13): 1181-1193.
AbstractUnlike 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.
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