Evidence map›Paper›PMID 40607495›Full record

ReviewThe application of clinical genetics2025

A Systematic Review of SNPs Screening for Platinum-Related Pharmacodynamics and Pharmacokinetics Genes in Non-Small Cell Lung Cancer for Precision Medicine.

Nadiya Nurul Afifah, Annisa Lazuardi Larasati, Indra Wijaya, Neily Zakiyah, Ruri Intania, Hideru Obinata, Melisa Intan Barliana

Abstract readReview
In one paragraph

Review in The application of clinical genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Nadiya Nurul AfifahDepartment of Biological Pharmacy, Faculty of Pharmacy, Universitas Padjadjaran, Sumedang, Indonesia.ORCID 0000-0003-1817-436X
Annisa Lazuardi LarasatiFaculty of Pharmacy, Universitas Indonesia, Depok, Indonesia.ORCID 0009-0005-5973-5946
Indra WijayaDepartment of Internal Medicine, Hasan Sadikin General Hospital, Bandung, Indonesia.ORCID 0000-0002-9446-2307
Neily ZakiyahDepartment of Pharmacology and Clinical Pharmacy, Faculty of Pharmacy, Universitas Padjadjaran, Sumedang, Indonesia.ORCID 0000-0002-9630-5567
Ruri IntaniaRotinsulu Lung Hospital, Bandung, Indonesia.
Hideru ObinataDepartment of Biochemistry, Gunma University School of Medicine, Maebashi, Japan.
Melisa Intan BarlianaDepartment of Biological Pharmacy, Faculty of Pharmacy, Universitas Padjadjaran, Sumedang, Indonesia.ORCID 0000-0003-0015-9604

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Traditional treatments for non-small cell lung cancer (NSCLC), such as chemotherapy, especially platinum-based regimens, often lack efficacy due to the disease's inherent heterogeneity. Precision medicine in NSCLC recognizes each tumor's unique genetic profile. Alterations in the pharmacokinetics and pharmacodynamics of platinum-based therapies significantly influence their clinical outcomes. Previous research has predominantly focused on genetic polymorphisms in genes like Methods: The analysis followed the PRISMA and STROPS Guidelines, using specific search terms including NSCLC, Chemotherapy, Polymorphisms, Single Nucleotide Polymorphisms (SNPs), Results: Initial screening of 370 studies, comprising 275 from PubMed and 95 from EBSCO, identified 53 relevant ones, excluding those such as reviews, non-English studies, and meta-analyses. Among the genetic variants studied (ERCC1 rs11615, ERCC2 rs13181, ABCC2 rs717620, GSTP1 rs1695), GSTP1 rs1695 emerged as particularly promising, with 11 studies indicating a significant association with improved survival outcomes. Conclusion: The integration of SNP profiling into clinical decision-making processes holds substantial potential for enhancing the personalization of NSCLC treatment strategies, thereby improving patient outcomes.

Indexed as

ABCC2chemotherapyERCC1ERCC2GSTP1NSCLCpolymorphismsSNPs

Identifiers

PMID40607495
PMCPMC12214474

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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.