Time-to-Event Modeling of Left- or Right-Censored Toxicity Data in Nonclinical Drug Toxicology
| Autor: | Marc Cerou, Emilie Henin, Chao Chen, Alienor Berges, Claire Ambery, Tarjinder Sahota, Lia Liefaard, Stefano Zamuner |
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| Rok vydání: | 2018 |
| Předmět: |
Event modeling
Time Factors Drug Evaluation Preclinical Biostatistics Logistic regression Toxicology 030226 pharmacology & pharmacy Models Biological 03 medical and health sciences 0302 clinical medicine Predictive Value of Tests Statistics Covariate Medicine Computer Simulation Weibull distribution Proportional Hazards Models Toxicity data Dose-Response Relationship Drug business.industry Probabilistic logic Censoring (statistics) Survival Analysis Logistic Models 030220 oncology & carcinogenesis Data Interpretation Statistical Toxicity business |
| Zdroj: | Toxicological sciences : an official journal of the Society of Toxicology. 165(1) |
| ISSN: | 1096-0929 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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