Two new approaches to improve the analysis of BALB/c 3T3 cell transformation assay data

Validation activities of the BALB/c 3T3 cell transformation assay (CTA) – a test method used for the assessment of the carcinogenic potential of compounds – have revealed the need for statistical analysis tailored to specific features of BALB/c 3T3 CTA data. Whereas a standard statistical approach for the Syrian hamster embryo (SHE) CTA was considered sufficient, an international expert group was gathered by the European Centre for the Validation of Alternative Methods (ECVAM) to review commonly applied statistical approaches for BALB/c 3T3 CTA. As it was concluded that none of the commonly applied approaches is entirely appropriate, two novel statistical approaches were found to be recommended for the evaluation of BALB/c 3T3 CTA data accounting for possible non-monotone concentration–response relationship and variance heterogeneity: a negative binomial generalised linear model with William's-type downturn-protected trend tests and a normalisation of the data by a specific transformation allowing for application of a general linear model that estimates effects assuming a normal distribution with William's-type protected tests. Both approaches are described in this article and their performance and the quality of the results they generate is demonstrated using exemplary data. Our work confirmed that both approaches are suitable for the statistical analysis of BALB/c 3T3 CTA data and that each of them is superior to commonly used methods. Furthermore, a procedure dichotomising data into negatives and positives is proposed which allows re-testing in cases where inconclusive data are encountered. The scripts of the statistical evaluation programs written in R – a freely available statistical software – are appended including exemplary outputs (Appendix A).

► Commonly applied approaches to analyse BALB/c 3T3 CTA data have shortcomings.
► Two novel statistical approaches are described.
► They can account for non-monotone concentration–response relationship.
► Their performance is demonstrated using exemplary data.
► An interpretation procedure to determine negatives and positives is proposed.