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| Title |
Serum liver enzymes serve as prognostic factors in patients with intrahepatic cholangiocarcinoma
|
|---|---|
| Published in |
OncoTargets and therapy, March 2017
|
| DOI | 10.2147/ott.s124161 |
| Pubmed ID | |
| Authors |
Chenyue Zhang, Haiyong Wang, Zhouyu Ning, Litao Xu, Liping Zhuang, Peng Wang, Zhiqiang Meng |
| Abstract |
Liver functions, reflective of the overall status of the host, have been reported to be important factors affecting the prognosis in many types of cancers. In this study, we explored the influences of liver enzymes albumin (ALB), globulin (GELO), total protein (TP), alkaline phosphatase (ALP), alanine aminotransferase (ALT), aspartate aminotransferase (AST), total bilirubin (TBIL), direct bilirubin (DBIL), gamma glutamyltranspeptidase (GGT), and lactate dehydrogenase (LDH) on the overall survival (OS) in a number of 173 patients with intrahepatic cholangiocarcinoma (ICC). Between 2011 and 2015, we enrolled patients with pathologically proven locally advanced or metastatic ICC. The impact of ALB, GELO, TP, ALP, ALT, AST, TBIL, DBIL, GGT, and LDH on OS were analyzed using Kaplan-Meier analysis. Next, the associations between these liver enzymes and OS were evaluated by univariate and multivariate analyses. Finally, the role of these enzymes in OS was evaluated in the subgroups. Elevated liver enzymes were linked with OS. We revealed that independent prognostic factors of poor outcome were ALP, TBIL, DBIL, and GGT, whereas ALB is a protective factor in ICC patients. Our results demonstrate that these liver enzymes may serve as valuable predictive markers in ICC patients. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 20 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 4 | 20% |
| Student > Postgraduate | 3 | 15% |
| Unspecified | 2 | 10% |
| Student > Ph. D. Student | 2 | 10% |
| Student > Master | 1 | 5% |
| Other | 3 | 15% |
| Unknown | 5 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 4 | 20% |
| Medicine and Dentistry | 4 | 20% |
| Unspecified | 2 | 10% |
| Nursing and Health Professions | 1 | 5% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 5% |
| Other | 2 | 10% |
| Unknown | 6 | 30% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 08 March 2017.
All research outputs
#22,764,772
of 25,382,440 outputs
Outputs from OncoTargets and therapy
#2,078
of 3,016 outputs
Outputs of similar age
#285,015
of 324,443 outputs
Outputs of similar age from OncoTargets and therapy
#72
of 91 outputs
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We're also able to compare this research output to 91 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.