Abstract
Mean survival, estimated by extrapolation of incomplete data, is commonly used by health technology assessment agencies to assess the value of new oncology treatments. A prolonged tail in the survival distribution, attributable to a subset of patients with durable response to treatment, will tend to improve estimates of mean survival. However, if the proportion of durable responders is small or moderate, the potential for increased mean survival may only become apparent with longer-term follow-up. This research seeks to identify the impact of longer follow-up on estimates of mean survival from clinical trials of immuno-oncology (IO) therapies.
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