Evidence map›Paper›PMID 27656240›Full record

ArticleEvidence-based complementary and alternative medicine : eCAM2016

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

Hongjie Liu, Tianhao Li, Lingxiu Chen, Sha Zhan, Meilan Pan, Zhiguo Ma, Chenghua Li, Zhe Zhang

Open access · hybridAbstract read
In one paragraph

Article in Evidence-based complementary and alternative medicine : eCAM, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.6field-weighted citation impact, top 19% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 9 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 2 institutions in 1 country.

Hongjie LiuDepartment of Traditional Chinese Medicine, Medical College, Jinan University, Guangzhou 510632, China.
Tianhao LiDepartment of Traditional Chinese Medicine, Medical College, Jinan University, Guangzhou 510632, China.
Lingxiu ChenDepartment of Traditional Chinese Medicine, Medical College, Jinan University, Guangzhou 510632, China.ORCID 0000-0002-3971-4495
Sha ZhanDepartment of Traditional Chinese Medicine, Medical College, Jinan University, Guangzhou 510632, China.
Meilan PanDepartment of Traditional Chinese Medicine, Medical College, Jinan University, Guangzhou 510632, China.
Zhiguo MaDepartment of Chinese Herbal Medicines, Pharmacy College, Jinan University, Guangzhou 510632, China.
Chenghua LiBiomaterial Laboratory of Guangdong Higher Education and Department of Biomedical Engineering, Jinan University, Guangzhou 510632, China.
Zhe ZhangShandong University of Traditional Chinese Medicine, Jinan 250355, China.ORCID 0000-0001-5541-222X
Jinan University · CNShandong University of Traditional Chinese Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Identifiers

PMID27656240
PMCPMC5021893
OpenAlexW2513203987

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.