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The heterogeneity effect of surveillance intervals on progression free survival

Authors: Zihang Zhong; Min Yang; Senmiao Ni; Lixin Cai; Jingwei Wu; Jianling Bai; Hao Yu;

The heterogeneity effect of surveillance intervals on progression free survival

Abstract

Progression-free survival (PFS) is an increasingly important surrogate endpoint in cancer clinical trials. However, the true time of progression is typically unknown if the evaluation of progression status is only scheduled at given surveillance intervals. In addition, comparison between treatment arms under different surveillance schema is not uncommon. Our aim is to explore whether the heterogeneity of the surveillance intervals may interfere with the validity of the conclusion of efficacy based on PFS, and the extent to which the variation would bias the results. We conduct comprehensive simulation studies to explore the aforementioned goals in a two-arm randomized control trial. We introduce three steps to simulate survival data with predefined surveillance intervals under different censoring rate considerations. We report the estimated hazard ratios and examine false positive rate, power and bias under different surveillance intervals, given different baseline median PFS, hazard ratio and censoring rate settings. Results show that larger heterogeneous lengths of surveillance intervals lead to higher false positive rate and overestimate the power, and the effect of the heterogeneous surveillance intervals may depend upon both the life expectancy of the tumor prognoses and the censoring proportion of the survival data. We also demonstrate such heterogeneity effect of surveillance intervals on PFS in a phase III metastatic colorectal cancer trial. In our opinions, adherence to consistent surveillance intervals should be favored in designing the comparative trials. Otherwise, it needs to be appropriately taken into account when analyzing data.

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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Cancer Research
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