Causality methods in cosmetovigilance: comparison of Colipa and PLM versus global introspection.

Netherlands Pharmacovigilance Centre Lareb, Goudsbloemvallei 7, 5237 MH 's-Hertogenbosch, The Netherlands.
Regulatory Toxicology and Pharmacology (Impact Factor: 2.13). 05/2012; 63(3):409-17. DOI: 10.1016/j.yrtph.2012.05.005
Source: PubMed

ABSTRACT The European Cosmetics Regulation requires a post-marketing system for detection of undesirable effects on human health of cosmetic products. Colipa, the European Cosmetic, toiletry and perfumery association, provided guidelines for causality assessment of these effects. In addition another causality method originally designed for causality rating in Post Launch Monitoring (PLM) of novel foods has been employed to assess causality of cosmetic products. In this study these two causality schemes for consumer cosmetic products were validated against clinical assessment, using the method of global introspection (GI) in 100 reported cases. Causality assessments were performed by three experienced assessors in pharmacovigilance. In the event of discordance between the assessors, an adapted Delphi method was used. The overall Spearman correlation coefficient was 0.74 for comparison of Colipa versus GI, whereas this was 0.50 for PLM versus GI. According to current guidelines, the sensitivity was 0.95 for both the Colipa and PLM method, specificity was 0.84 for Colipa and 0.40 for PLM. From these results it can be concluded the performance of the Colipa causality method yielded better correlation to GI than PLM causality method. The factor identified from comparison of these two schemes as having greatest impact was the course of the reaction.

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    ABSTRACT: This is a handbook for behavioral or biosocial scientists who use statistical inference. It is assumed only that the reader knows how to proceed to perform a test of statistical significance. The first chapter presents a general description of statistical hypotheses testing. There are described four parameters of statistical inference: power, significance criterion (a), sample size (n) and effect size (ES). Chapters 2 to 10 present different statistical tests. They are organized in the following way: 1. The test is introduced; 2. the ES index is described and discussed; 3. the power tables are presented together with the method of their use; 4. the sample size tables are presented and the method of their use is described. Chapters 2, 3, 4, 5, 6 and 8 are equipped with numerous illustrative examples. One can find the following tests: The t test for means (ch. 2); the Pearson product-moment correlation coefficient r s (ch. 3); testing of hypotheses concerning differences between population correlation coefficients (ch. 4); the sign test and the test that some defined characteristic is one- half (ch. 5); testing of hypotheses concerning differences between independent population proportions (ch. 6); chi-square tests (ch. 7); the analysis of variance (ch. 8); multiple regression and correlation analysis (ch. 9); set correlation and multivariate methods (ch. 10). The major changes in comparison with the first edition are: there is a new chapter 10 and a new chapter 11 treating the power analysis in more integrated form: effect size, psychometric reliability and the efficacy of “qualifying” dependent variables. Also, the references have been updated.
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