Literature DB >> 16298467

Statistical analysis used in the nutritional assessment of novel food using the proof of safety.

Ludwig A Hothorn1, Regina Oberdoerfer.   

Abstract

The safety assessment of Novel Food, including GM biotechnology-derived crops, starts with the comparison of the Novel Food with a traditional counterpart that is generally accepted as safe based on a history of human food use. Substantial equivalence is established if no meaningful difference from the conventional counterpart was found, leading to the conclusion that the Novel Food is as safe and nutritious as its traditional counterpart. In general, the non-significance of p value is used for the proof of safety. From a statistical perspective, the problems connected with such an approach are demonstrated, namely that quite different component-specific false negative error rates result. As an alternative, the proof of safety is discussed with the inherently related definition of safety thresholds. Moreover, parametric and non-parametric confidence intervals for the difference and the ratio to control (conventional line) are described in detail. Finally, the treatment of multiple components for a global proof of safety is explained.

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Year:  2005        PMID: 16298467     DOI: 10.1016/j.yrtph.2005.10.001

Source DB:  PubMed          Journal:  Regul Toxicol Pharmacol        ISSN: 0273-2300            Impact factor:   3.271


  7 in total

1.  Natural variation in crop composition and the impact of transgenesis.

Authors:  George G Harrigan; Denise Lundry; Suzanne Drury; Kristina Berman; Susan G Riordan; Margaret A Nemeth; William P Ridley; Kevin C Glenn
Journal:  Nat Biotechnol       Date:  2010-05       Impact factor: 54.908

2.  Comparative statistical component analysis of transgenic, cyanophycin-producing potatoes in greenhouse and field trials.

Authors:  Kerstin Schmidt; Jörg Schmidtke; Yvonne Mast; Eva Waldvogel; Wolfgang Wohlleben; Friederike Klemke; Wolfgang Lockau; Tina Hausmann; Maja Hühns; Inge Broer
Journal:  Transgenic Res       Date:  2017-05-10       Impact factor: 2.788

3.  A statistical assessment of differences and equivalences between genetically modified and reference plant varieties.

Authors:  Hilko van der Voet; Joe N Perry; Billy Amzal; Claudia Paoletti
Journal:  BMC Biotechnol       Date:  2011-02-16       Impact factor: 2.563

4.  Comments on the paper "A statistical assessment of differences and equivalences between genetically modified and reference plant varieties" by van der Voet et al. 2011.

Authors:  Keith J Ward; Margaret A Nemeth; Cavell Brownie; Bonnie Hong; Rod A Herman; Regina Oberdoerfer
Journal:  BMC Biotechnol       Date:  2012-04-25       Impact factor: 2.563

5.  Covering chemical diversity of genetically-modified tomatoes using metabolomics for objective substantial equivalence assessment.

Authors:  Miyako Kusano; Henning Redestig; Tadayoshi Hirai; Akira Oikawa; Fumio Matsuda; Atsushi Fukushima; Masanori Arita; Shin Watanabe; Megumu Yano; Kyoko Hiwasa-Tanase; Hiroshi Ezura; Kazuki Saito
Journal:  PLoS One       Date:  2011-02-16       Impact factor: 3.240

6.  Equivalence Testing Approaches in Genetically Modified Organism Risk Assessment.

Authors:  Hilko van der Voet; Claudia Paoletti
Journal:  J Agric Food Chem       Date:  2019-11-27       Impact factor: 5.279

7.  A statistical simulation model for field testing of non-target organisms in environmental risk assessment of genetically modified plants.

Authors:  Paul W Goedhart; Hilko van der Voet; Ferdinando Baldacchino; Salvatore Arpaia
Journal:  Ecol Evol       Date:  2014-03-15       Impact factor: 2.912

  7 in total

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