While models of combined effect are available for such assessments, proper fitting of the data is critical to obtaining accurate conclusions.
In this study an asymmetry parameter (s) was evaluated for data-fitting and compared with our previous approach.
Inhibition of bioluminescence was assessed with Vibrio fischeri at 15, 30 and 45-min of exposure with seven or eight concentrations and a control (each duplicated) for each single-chemical (A or B) and mixture (A:B). Concentration-effect data were fitted to sigmoid curves using the four-parameter logistic function (4PL) and the five-parameter logistic minus one-parameter (5PL-1P) function.
For the 4PL, parameters included minimum effect, maximum effect, EC(50) and slope, while for the 5PL-1P the minimum effect parameter was removed and an asymmetry parameter was added. A total of 72 mixture toxicity data sets were evaluated, representing 432 single-chemical and 216 mixture curves.
Mean coefficients of determination (r(2)) for all 648 curves showed that the 5PL-1P gave better fitting (0.9982 ± 0.0018) than the 4PL (0.9973 ± 0.0030). For both functions, the sum-of-squares of the residuals (SS-Res) was determined for each curve.
The 5-parameter rational regression best described the relationship between the decrease in sum-of-squares of the residuals (i.e., 4PL: SS-Res - 5PL-1P: SS-Res) and log s, with fitting improved the most at low values of s (s<0.8). This held even when curves with r(2) values ≤ 0.9970 were removed from the analyses.
Subsequent review of the combined effects obtained via the 4PL and the 5PL-1P functions resulted in a change in the interpretation of combined effect in 39/216 (18%) cases.