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Evaluating and Adjusting for Premature Censoring of Progression-Free Survival

Authors: Hong Laura Lu; Yuan Li Shen; Mei Jin; Kallappa Koti; Mark Rothmann; Kyung Yul Lee; Jenny J. Zhang; +1 Authors

Evaluating and Adjusting for Premature Censoring of Progression-Free Survival

Abstract

The intent-to-treat principle, grouping subjects as they were randomized and following all subjects to the endpoint or the end of study, allows valid statistical comparisons. Progression-free survival (PFS) has been used as a decision-making endpoint in oncology. It can be difficult to have a meaningful intent-to-treat analysis of PFS as some studies have extensive loss to follow-up for PFS. In the analysis, subjects lost to follow-up for PFS have their PFS times censored, with the censoring treated as noninformative. We use remaining overall survival to investigate whether premature censoring for PFS is informative and the potential bias in treating such censoring as noninformative.

Keywords

Models, Statistical, Endpoint Determination, Decision Making, Sensitivity and Specificity, Survival Analysis, Disease-Free Survival, Humans, Lost to Follow-Up, Randomized Controlled Trials as Topic

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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!
3
Average
Average
Average
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