To increase efficiency, interim comparisons can be made on an intermediate time-to-event outcome which is on the causal pathway to the definitive outcome.
In contrast, there was no correlation between differences in these intermediate time-to-event end points and differences in 5-year OS in indolent NHL (Table 3).
In this analysis, PFS and EFS were considered together as an intermediate time-to-event end point since the per-protocol definition of EFS always included progression and death as events; however, a separate analysis was also presented where possible.
The purpose of this study is to describe reporting of primary and secondary end points in RCTs of NHL and to determine the correlations between response, intermediate time-to-event, and survival end points in the treatment of NHL with the goal of identifying a surrogate end point for OS.
The nonparametric Spearman's rank correlation coefficient (rs) was used as a measure of correlation between the differences in (i) CR and intermediate time-to-event end points (3-year EFS/PFS or OS) and (ii) potential surrogate end points (CR, 3 year EFS/PFS) and 5-year OS.
Moreover, different studies disclosed that the decay of various messengers after treatment is heterogeneous: some transcripts persist for a long time [23], [24] while others disappear at once and others put an intermediate time to be completely degraded [10], [25].
We found that insects were on average killed by cooperator infections after 12 hours, 2 hours sooner than for cheat infections, and that mixed infections resulted in an intermediate time to death showed significant differences between all groups: P < 0.01 in all cases).
Start of surgery within 12 hours after the fracture event was considered early surgery (short time-to-surgery), start of surgery from 12 to 36 hours after the fracture event was classified as intermediate (medium time-to-surgery), and surgery that was begun more than 36 hours after the event was considered to be late surgery (longest time-to-surgery).
In multi-period stochastic formulation of classical mean variance portfolio optimization problem, an investor makes an investment decision based on expectations and/or scenarios up to some intermediate times prior to the horizon and, consequently, rebalances or restructures the portfolio.
Although Williamson et al. [ 11] also used survival probabilities at intermediate times (corresponding to their required common time points across trials), our method differs in that we use the additional probabilities to improve estimates of the numbers of events within each interval, whereas the motivation for Williamson et al. [ 11] was to establish common time intervals across trials.
