Comparison of absolute benefits of anticancer therapies determined by snapshot and area methods

Choice of treatment-effect measures when noninferiority margins originally defined in absolute difference translated into relative difference influenced the results of clinical trials

“…Previous studies have also provided empirical evidence regarding the comparison between effects measures of time-to-event outcomes in clinical trials. Seruga et al [27] compared the difference in survival probabilities at specific time points with the difference in RMST, and provided that difference in RMST is less dependent on the shape of survival curves and might be advantageous in the absolute treatment-effect investigations. Deeks [28] already showed that in 551 systematic reviews of clinical trials with binary outcomes, the RR and odds ratio models are on average more consistent than RD model.…”

The Net Chance of a Longer Survival as a Patient-Oriented Measure of Treatment Benefit in Randomized Clinical Trials

“…As it turns out, this statistic is also equal to the area under the curve of the Δ(m) for all values of m, restricted to the same time point as the area under the survival curve. 10,[21][22][23][24][25] The Δ has intuitive and descriptive appeal, but it also leads to a test of significance through a randomization test, which is asymptotically equivalent to Gehan's generalized Wilcoxon rank sum test. 12,26,27 When the treatment effect is tested for a single value of m (the most common case being m = 0), no adjustment for multiplicity is needed.…”

“…4 Other measures of treatment effect have been proposed, but none has been widely adopted or has a straightforward application to the individual patient. [7][8][9][10][11] We describe a new measure of treatment effect that directly addresses a question patients might raise, that is, "What is my net chance of surviving longer with treatment than without?" or, by extension, "What is my net chance of surviving at least 6 months longer with treatment than without?"…”

Harnessing the immune system to provide long-term survival in patients with melanoma and other solid tumors

“…However, median OS is a snapshot comparison of a single time point and thus provides a limited measure of benefit. In particular, differences in the durability of survival, i.e., information on those patients that may survive longer than the median value, are not conveyed 56 , 57 . Additionally, log-rank tests are used to determine if the difference observed between 2 survival curves at a certain time point is statistically significant.…”

“…HRs are a more precise way of reporting survival outcomes than median values. Furthermore, clinicians and patients are more likely to support or accept treatments based on relative increases in survival rather than absolute differences in the number of patients alive at a single timepoint 57 , 58 . Calculating the HR, however, assumes that the ratio remains constant with time, which is not always the case.…”