Time-to-Event Modeling of Left- or Right-Censored Toxicity Data in Nonclinical Drug Toxicology. (21st May 2018)

• Record Type: Journal Article
• Authors: Berges, Alienor; Cerou, Marc; Sahota, Tarjinder; Liefaard, Lia; Ambery, Claire; Zamuner, Stefano; Chen, Chao; Hénin, Emilie
• Is Part Of: Toxicological sciences. Volume 165:Number 1(2018)
• Page Start: 50
• Page End: 60
• Publication Date: 2018-05-21
• Subjects: time-dose-toxicity relationship -- time-to-event modeling -- survival analysis; Toxicology -- Periodicals; Toxicology -- Periodicals; Toxicology; Periodicals; 615.9
• DOI: 10.1093/toxsci/kfy122
• Languages: English
• ISSNs: 1096-6080

Abstract

Abstract: A time-to-event (TTE) model has been developed to characterize a histopathology toxicity that can only be detected at the time of animal sacrifice. The model of choice was a hazard model with a Weibull distribution and dose was a significant covariate. The diagnostic plots showed a satisfactory fit of the data, despite the high degree of left and right censoring. Comparison to a probabilistic logit model shows similar performance in describing the data with a slight underestimation of survival by the Logit model. However, the TTE model was found to be more predictive in extrapolating toxicity risk beyond the observation range of a truncated dataset. The diagnostic and comparison outcomes would suggest using the TTE approach as a first choice for characterizing short and long-term risk from nonclinical toxicity studies. However, further investigations are needed to explore the domain of application of this kind of approach in drug safety assessment.