bioRxivPharmacology & Toxicology
hb or not hb - when and why accounting for background mortality in toxicological survival models matters?
Abstract
Decisions in Environmental Risk Assessment (ERA) about impacts of chemical compounds on different species are based on critical effect indicators such as the 50% lethal concentration (LC50). Regulatory documents recommend concentration-response (or concentration-effect) model fitting on standard toxicity test data to get LC50 values. However, toxicokinetic-toxicodynamic (TKTD) models proved their efficiency to better exploit toxicity test data, at Tier-2 but also at Tier-1, delivering time-independent indicators. In particular, LC50 values can be obtained from the reduced General Unified Threshold model of Survival (GUTS-RED) with both variants, Stochastic Death and Individual Tolerance, that include parameter hb, the background mortality. Estimating hb during the fitting process or not depends on studies and fitting habits, while it may strongly influence the other GUTS-RED parameters, and consequently the LC50 estimate. We hypothesized that estimating hb from all data in all replicates over time should provide more precise LC50 estimates. We then explored how estimating hb impacted: (i) GUTS-RED model parameters; (ii) goodness-of-fit criteria (fitting plot, posterior predictive check, parameter correlation); (iii) LC50 accuracy and precision. We finally show that estimating hb does not impact the LC50 precision while providing more accurate and precise GUTS parameter estimates. Hence, estimating hb would lead to a more protective ERA. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=197 HEIGHT=200 SRC="FIGDIR/small/525496v2_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@3ee285org.highwire.dtl.DTLVardef@89931eorg.highwire.dtl.DTLVardef@19c70forg.highwire.dtl.DTLVardef@5bb72c_HPS_FORMAT_FIGEXP M_FIG C_FIG Specifications table O_TBL View this table: org.highwire.dtl.DTLVardef@156b31eorg.highwire.dtl.DTLVardef@109991borg.highwire.dtl.DTLVardef@122f597org.highwire.dtl.DTLVardef@29a3a7org.highwire.dtl.DTLVardef@1b75315_HPS_FORMAT_FIGEXP M_TBL C_TBL
- research focus: benchmarking
- research focus: drug response / drug discovery
- research focus: host-pathogen & immune response
- approach: statistical model
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