Cargando…

To Set Up a Logistic Regression Prediction Model for Hepatotoxicity of Chinese Herbal Medicines Based on Traditional Chinese Medicine Theory

Aims. To establish a logistic regression (LR) prediction model for hepatotoxicity of Chinese herbal medicines (HMs) based on traditional Chinese medicine (TCM) theory and to provide a statistical basis for predicting hepatotoxicity of HMs. Methods. The correlations of hepatotoxic and nonhepatotoxic...

Descripción completa

Detalles Bibliográficos
Autores principales: Liu, Hongjie, Li, Tianhao, Chen, Lingxiu, Zhan, Sha, Pan, Meilan, Ma, Zhiguo, Li, Chenghua, Zhang, Zhe
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5021893/
https://www.ncbi.nlm.nih.gov/pubmed/27656240
http://dx.doi.org/10.1155/2016/7273940
_version_ 1782453415699283968
author Liu, Hongjie
Li, Tianhao
Chen, Lingxiu
Zhan, Sha
Pan, Meilan
Ma, Zhiguo
Li, Chenghua
Zhang, Zhe
author_facet Liu, Hongjie
Li, Tianhao
Chen, Lingxiu
Zhan, Sha
Pan, Meilan
Ma, Zhiguo
Li, Chenghua
Zhang, Zhe
author_sort Liu, Hongjie
collection PubMed
description Aims. To establish a logistic regression (LR) prediction model for hepatotoxicity of Chinese herbal medicines (HMs) based on traditional Chinese medicine (TCM) theory and to provide a statistical basis for predicting hepatotoxicity of HMs. Methods. The correlations of hepatotoxic and nonhepatotoxic Chinese HMs with four properties, five flavors, and channel tropism were analyzed with chi-square test for two-way unordered categorical data. LR prediction model was established and the accuracy of the prediction by this model was evaluated. Results. The hepatotoxic and nonhepatotoxic Chinese HMs were related with four properties (p < 0.05), and the coefficient was 0.178 (p < 0.05); also they were related with five flavors (p < 0.05), and the coefficient was 0.145 (p < 0.05); they were not related with channel tropism (p > 0.05). There were totally 12 variables from four properties and five flavors for the LR. Four variables, warm and neutral of the four properties and pungent and salty of five flavors, were selected to establish the LR prediction model, with the cutoff value being 0.204. Conclusions. Warm and neutral of the four properties and pungent and salty of five flavors were the variables to affect the hepatotoxicity. Based on such results, the established LR prediction model had some predictive power for hepatotoxicity of Chinese HMs.
format Online
Article
Text
id pubmed-5021893
institution National Center for Biotechnology Information
language English
publishDate 2016
publisher Hindawi Publishing Corporation
record_format MEDLINE/PubMed
spelling pubmed-50218932016-09-21 To Set Up a Logistic Regression Prediction Model for Hepatotoxicity of Chinese Herbal Medicines Based on Traditional Chinese Medicine Theory Liu, Hongjie Li, Tianhao Chen, Lingxiu Zhan, Sha Pan, Meilan Ma, Zhiguo Li, Chenghua Zhang, Zhe Evid Based Complement Alternat Med Research Article Aims. To establish a logistic regression (LR) prediction model for hepatotoxicity of Chinese herbal medicines (HMs) based on traditional Chinese medicine (TCM) theory and to provide a statistical basis for predicting hepatotoxicity of HMs. Methods. The correlations of hepatotoxic and nonhepatotoxic Chinese HMs with four properties, five flavors, and channel tropism were analyzed with chi-square test for two-way unordered categorical data. LR prediction model was established and the accuracy of the prediction by this model was evaluated. Results. The hepatotoxic and nonhepatotoxic Chinese HMs were related with four properties (p < 0.05), and the coefficient was 0.178 (p < 0.05); also they were related with five flavors (p < 0.05), and the coefficient was 0.145 (p < 0.05); they were not related with channel tropism (p > 0.05). There were totally 12 variables from four properties and five flavors for the LR. Four variables, warm and neutral of the four properties and pungent and salty of five flavors, were selected to establish the LR prediction model, with the cutoff value being 0.204. Conclusions. Warm and neutral of the four properties and pungent and salty of five flavors were the variables to affect the hepatotoxicity. Based on such results, the established LR prediction model had some predictive power for hepatotoxicity of Chinese HMs. Hindawi Publishing Corporation 2016 2016-08-29 /pmc/articles/PMC5021893/ /pubmed/27656240 http://dx.doi.org/10.1155/2016/7273940 Text en Copyright © 2016 Hongjie Liu et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Liu, Hongjie
Li, Tianhao
Chen, Lingxiu
Zhan, Sha
Pan, Meilan
Ma, Zhiguo
Li, Chenghua
Zhang, Zhe
To Set Up a Logistic Regression Prediction Model for Hepatotoxicity of Chinese Herbal Medicines Based on Traditional Chinese Medicine Theory
title To Set Up a Logistic Regression Prediction Model for Hepatotoxicity of Chinese Herbal Medicines Based on Traditional Chinese Medicine Theory
title_full To Set Up a Logistic Regression Prediction Model for Hepatotoxicity of Chinese Herbal Medicines Based on Traditional Chinese Medicine Theory
title_fullStr To Set Up a Logistic Regression Prediction Model for Hepatotoxicity of Chinese Herbal Medicines Based on Traditional Chinese Medicine Theory
title_full_unstemmed To Set Up a Logistic Regression Prediction Model for Hepatotoxicity of Chinese Herbal Medicines Based on Traditional Chinese Medicine Theory
title_short To Set Up a Logistic Regression Prediction Model for Hepatotoxicity of Chinese Herbal Medicines Based on Traditional Chinese Medicine Theory
title_sort to set up a logistic regression prediction model for hepatotoxicity of chinese herbal medicines based on traditional chinese medicine theory
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5021893/
https://www.ncbi.nlm.nih.gov/pubmed/27656240
http://dx.doi.org/10.1155/2016/7273940
work_keys_str_mv AT liuhongjie tosetupalogisticregressionpredictionmodelforhepatotoxicityofchineseherbalmedicinesbasedontraditionalchinesemedicinetheory
AT litianhao tosetupalogisticregressionpredictionmodelforhepatotoxicityofchineseherbalmedicinesbasedontraditionalchinesemedicinetheory
AT chenlingxiu tosetupalogisticregressionpredictionmodelforhepatotoxicityofchineseherbalmedicinesbasedontraditionalchinesemedicinetheory
AT zhansha tosetupalogisticregressionpredictionmodelforhepatotoxicityofchineseherbalmedicinesbasedontraditionalchinesemedicinetheory
AT panmeilan tosetupalogisticregressionpredictionmodelforhepatotoxicityofchineseherbalmedicinesbasedontraditionalchinesemedicinetheory
AT mazhiguo tosetupalogisticregressionpredictionmodelforhepatotoxicityofchineseherbalmedicinesbasedontraditionalchinesemedicinetheory
AT lichenghua tosetupalogisticregressionpredictionmodelforhepatotoxicityofchineseherbalmedicinesbasedontraditionalchinesemedicinetheory
AT zhangzhe tosetupalogisticregressionpredictionmodelforhepatotoxicityofchineseherbalmedicinesbasedontraditionalchinesemedicinetheory