Evidence map›Paper›PMID 27178043›Full record

ArticleThe AAPS journal2016

Therapeutic Application of Pharmacogenomics in Oncology.

Yingqi Zhang, Seumsack Dennis Somtakoune, Christina Cheung, Mario Listiawan, Xiaodong Feng

Abstract readComment
PubMed Publisher
In one paragraph

Article in The AAPS journal, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.5field-weighted citation impact, top 33% 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

7 citing papers in PubMed, 12 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors at 3 institutions in 1 country.

Yingqi ZhangCalifornia Northstate University College of Phamracy, Elk Grove, CA, USA.
Seumsack Dennis SomtakouneCalifornia Northstate University College of Phamracy, Elk Grove, CA, USA.
Christina CheungCalifornia Northstate University College of Medicine, Elk Grove, CA, USA.
Mario ListiawanRonald Reagan Medical Center, University of California Los Angeles, Los Angeles, CA, USA.
Xiaodong FengCalifornia Northstate University College of Medicine, Elk Grove, CA, USA. XFeng@cnsu.edu.
California Northstate University · USDignity Health · USUniversity of California, Los Angeles · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Personalizing cancer treatment has been proved to be difficult for healthcare providers due to the nature of chemotherapies which includes narrow therapeutic indices, severe and potential life-threatening toxicities, and variable response rates and efficacies. Studies in pharmacogenomics (PGx) may help guide clinicians to personalize treatment for cancer patients. Implementing PGx in cancer treatment may offer choices to anticipate differences in drug response, resistance, efficacy, and toxicity within chemotherapeutic agents and targeted immune biologic agents. This can be used to achieve optimization of treatment regimens based on patients' variability. Many of the cancer treatment agents are biologics targeting specific antigens expressed on cancer cells, or blocking stimulators and signal transduction pathways of tumor growth, or enhance anticancer immune responses. It is now crucial for clinicians to understand the important association of clinically important biomarker polymorphisms with the clinical benefits of cancer therapies. By identifying specific PGx biomarker polymorphisms present in cancer cells, physicians can select and tailor a patient's treatment based on his or her genetic profile. PGx-guided cancer treatment may have the ability to improve the survival of patients while avoiding the unnecessary cost due to unresponsive treatment and toxicities of that patients experience.

Indexed as

PharmacogeneticsAntineoplastic AgentsHumansNeoplasmsPolymorphism, GeneticAntineoplastic Agentsefficacyoncologypharmacogenomicsresistancetoxicity

Identifiers

PMID27178043
OpenAlexW2347297735

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.