hb or not hb - When and why accounting for background mortality in toxicological survival models matters?

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 h_b, the background mortality. Estimating h_b 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 h_b from all data in all replicates over time should provide more precise LC₅₀ estimates. We then explored how estimating h_b impacted: (i) GUTS-RED model parameters; (ii) goodness-of-fit criteria (fitting plot, posterior predictive check, parameter correlations); (iii) LC₅₀ accuracy and precision. We finally show that estimating h_b does not impact the LC₅₀ precision while providing more accurate and precise GUTS parameter estimates. Hence, estimating h_b would lead to a more protective ERA.