Semi-correlations as a tool to model for skin sensitization
Copyright © 2021 Elsevier Ltd. All rights reserved..
Semi-correlation specifically assesses the correlation between a binary variable and a continuous variable. Semi-correlations were applied to develop binary models for various endpoints. We applied the semi-correlation to develop models of two kinds of skin sensitization one related to animals (local lymph node assay LLNA) and one to human beings (direct peptide reactivity assay DPRA and/or human cell line activation test h-CLAT). The models refer to binary classification for a two-level strategy: the first level (analysis of all compounds) is used in the format "sensitizer or non-sensitizer", and the second level (only sensitizers) is a further classification in the format "strong or weak sensitizer". The ranges of statistical characteristics of the models depend on the endpoint, LLNA or DPRA/h-CLAT: for the first level, sensitivity: 0.69-0.88, specificity: 0.75-0.89, accuracy: 0.77-0.87, Matthew's correlation coefficient (MCC): 0.54-0.57 and for the second level, sensitivity: 0.70-1.0, specificity: 0.78-0.83, accuracy: 0.77-0.87, MCC: 0.54-0.76. Thus, the described approach can be applied to building up models of the skin sensitization potency.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2021 |
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| Erschienen: |
2021 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:157 |
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| Enthalten in: |
Food and chemical toxicology : an international journal published for the British Industrial Biological Research Association - 157(2021) vom: 08. Nov., Seite 112580 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Toropova, Alla P [VerfasserIn] |
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| Links: |
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| Themen: |
Allergens |
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| Anmerkungen: |
Date Completed 09.02.2022 Date Revised 09.02.2022 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1016/j.fct.2021.112580 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| 520 | |a Copyright © 2021 Elsevier Ltd. All rights reserved. | ||
| 520 | |a Semi-correlation specifically assesses the correlation between a binary variable and a continuous variable. Semi-correlations were applied to develop binary models for various endpoints. We applied the semi-correlation to develop models of two kinds of skin sensitization one related to animals (local lymph node assay LLNA) and one to human beings (direct peptide reactivity assay DPRA and/or human cell line activation test h-CLAT). The models refer to binary classification for a two-level strategy: the first level (analysis of all compounds) is used in the format "sensitizer or non-sensitizer", and the second level (only sensitizers) is a further classification in the format "strong or weak sensitizer". The ranges of statistical characteristics of the models depend on the endpoint, LLNA or DPRA/h-CLAT: for the first level, sensitivity: 0.69-0.88, specificity: 0.75-0.89, accuracy: 0.77-0.87, Matthew's correlation coefficient (MCC): 0.54-0.57 and for the second level, sensitivity: 0.70-1.0, specificity: 0.78-0.83, accuracy: 0.77-0.87, MCC: 0.54-0.76. Thus, the described approach can be applied to building up models of the skin sensitization potency | ||
| 650 | 4 | |a Journal Article | |
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| 650 | 4 | |a Direct peptide reactivity assay (DPRA) | |
| 650 | 4 | |a Human cell line activation test (h-CLAT) | |
| 650 | 4 | |a Local lymph node assay (LLNA) | |
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| 700 | 1 | |a Benfenati, Emilio |e verfasserin |4 aut | |
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