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Information derived from sensitization test methods: test sensitivity, false positives and false negatives
Author(s) -
Basketter David A.,
Kimber Ian
Publication year - 2007
Publication title -
contact dermatitis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.524
H-Index - 96
eISSN - 1600-0536
pISSN - 0105-1873
DOI - 10.1111/j.1600-0536.2007.01009.x
Subject(s) - false positive paradox , false positives and false negatives , local lymph node assay , false negative reactions , test (biology) , medicine , true positive rate , sensitization , computer science , skin sensitization , machine learning , artificial intelligence , immunology , paleontology , biology
Predictive toxicology tests for the prospective identification of skin‐sensitizing chemicals are well known and have been used for many years. However, of these, only the local lymph node assay (LLNA) has actually undergone formal independent assessment to determine the accuracy of the predictions, particularly with respect to the likelihood of false positives and false negatives. Often, efforts to increase the sensitivity of a test (reducing false negatives) tend to increase the number of false positives. In this short review, these issues are discussed in particular relation to the 3 predictive tests available in regulatory toxicology, the guinea‐pig maximization test, the occluded patch test of Buehler and the LLNA. A key perspective is that no predictive test is without limitations; having a good appreciation of these limitations is necessary for making the best use of the information derived from these methods.