Evaluation of the treatment time-lag effect for survival data

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Abstract

Medical treatments often take a period of time to reveal their impact on subjects, which is the so-called time-lag effect in the literature. In the survival data analysis literature, most existing methods compare two treatments in the entire study period. In cases when there is a substantial time-lag effect, these methods would not be effective in detecting the difference between the two treatments, because the similarity between the treatments during the time-lag period would diminish their effectiveness. In this paper, we develop a novel modeling approach for estimating the time-lag period and for comparing the two treatments properly after the time-lag effect is accommodated. Theoretical arguments and numerical examples show that it is effective in practice.

Keywords

Cox proportional hazards model Crossing hazard rates Lag effect Survival analysis Treatment comparison 

Notes

Acknowledgements

The authors thank the editor and two referees for their valuable comments which greatly improved the quality of this paper.

Supplementary material

10985_2017_9390_MOESM1_ESM.pdf (188 kb)
Supplementary material 1 (pdf 187 KB)

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Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  1. 1.Department of Mathematics and StatisticsOld Dominion UniversityNorfolkUSA
  2. 2.Department of BiostatisticsUniversity of FloridaGainesvilleUSA

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