Evaluation of the treatment time-lag effect for survival data

• Published in: Lifetime data analysis Vol. 24; no. 2; pp. 310 - 327
• Main Authors: Park, Kayoung, Qiu, Peihua
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.04.2018; Springer Nature B.V
• Subjects: Data analysis; Economics; Finance; Health Sciences; Health services; Insurance; Management; Mathematical models; Mathematics and Statistics; Medicine; Operations Research/Decision Theory; Quality Control; Reliability; Safety and Risk; Statistics; Statistics for Business; Statistics for Life Sciences; Survival; Survival analysis; Survival analysis; Crossing hazard rates; Lag effect; Treatment comparison; Cox proportional hazards model
• ISSN: 1380-7870; 1572-9249; 1572-9249
• DOI: 10.1007/s10985-017-9390-7

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.