scholarly journals Oil toxicity test methods must be improved

2018 ◽  
Vol 38 (2) ◽  
pp. 302-311 ◽  
Author(s):  
Peter V. Hodson ◽  
Julie Adams ◽  
R. Stephen Brown
Keyword(s):  
Toxicity Test ◽  
Test Methods ◽  
Oil Toxicity

A Comparison of Sediment Toxicity Test Methods at Three Great Lake Areas of Concern

1996 ◽  
Vol 22 (3) ◽  
pp. 495-511 ◽  
Author(s):  
G. Allen Burton ◽  
Christopher G. Ingersoll ◽  
LouAnn C. Burnett ◽  
Mary Henry ◽  
Mark L. Hinman ◽  
...  
Keyword(s):  
Toxicity Test ◽  
Great Lake ◽  
Sediment Toxicity ◽  
Test Methods ◽  
Sediment Toxicity Test ◽  
Areas Of Concern

scholarly journals Dredged Material Evaluations: Review of Zooplankton Toxicity Test Methods for Marine Water Quality Evaluations

2016 ◽  
Author(s):  
Alan J. Kennedy ◽  
Guilherme Lotufo ◽  
Jennifer G. Laird ◽  
J. D. Farrar
Keyword(s):  
Water Quality ◽  
Toxicity Test ◽  
Test Methods ◽  
Marine Water ◽  
Dredged Material

An investigation of new toxicity test method performance in validation studies: 1. toxicity test methods that have predictive capacity no greater than chance

2002 ◽  
Vol 21 (6) ◽  
pp. 305-312 ◽  
Author(s):  
L H Bruner ◽  
G J Carr ◽  
J W Harbell ◽  
R D Curren
Keyword(s):  
Predictive Value ◽  
Validation Studies ◽  
Toxicity Test ◽  
High Sensitivity ◽  
Test Methods ◽  
Test Method ◽  
Predictive Capacity ◽  
Worst Case ◽  
Method Performance ◽  
Sensitivity Specificity

An approach commonly used to measure new toxicity test method (NTM) performance in validation studies is to divide toxicity results into positive and negative classifications, and then identify true positive (TP), true negative (TN), false positive (FP) and false negative (FN) results. After this step is completed, the contingent probability statistics (CPS), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) are calculated. Although these statistics are widely used and often the only statistics used to assess the performance of toxicity test methods, there is little specific guidance in the validation literature on what values for these statistics indicate adequate performance. The purpose of this study was to begin developing data-based answers to this question by characterizing the CPS obtained from an NTM whose data have a completely random association with a reference test method (RTM). Determining the CPS of this worst-case scenario is useful because it provides a lower baseline from which the performance of an NTM can be judged in future validation studies. It also provides an indication of relationships in the CPS that help identify random or near-random relationships in the data. The results from this study of randomly associated tests show that the values obtained for the statistics vary significantly depending on the cut-offs chosen, that high values can be obtained for individual statistics, and that the different measures cannot be considered independently when evaluating the performance of an NTM. When the association between results of an NTM and RTM is random the sum of the complementary pairs of statistics (sensitivity+ specificity, NPV+PPV) is approximately 1, and the prevalence (i.e., the proportion of toxic chemicals in the population of chemicals) and PPV are equal. Given that combinations of high sensitivity–low specificity or low specificity–high sensitivity (i.e., the sum of the sensitivity and specificity equal to approximately 1) indicate lack of predictive capacity, an NTM having these performance characteristics should be considered no better for predicting toxicity than by chance alone.

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