SynthesisAsian Pacific journal of cancer prevention : APJCP2021
Association of PON1, LEP and LEPR Polymorphisms with Susceptibility to Breast Cancer: A Meta-Analysis.
Synthesis in Asian Pacific journal of cancer prevention : APJCP, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 3 of them syntheses that pooled 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.
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.
Who cites it
8 citing papers in PubMed, 3 syntheses or guidelines pooled it, 20 citations in OpenAlex.
- Association of the CXCL12 rs1801157 Polymorphism with Breast Cancer Risk: A Meta-Analysis.Asian Pacific journal of cancer prevention : APJCP · 2024Pooled it
- Correlation of Q223R and K109R polymorphisms in leptin receptor gene with susceptibility of breast cancer: A systematic review and meta-analysis.Journal of the Chinese Medical Association : JCMA · 2023Pooled it
- Genetic alterations inFrontiers in oncology · 2023Pooled it
- Insights into the molecular and genetic role of obesity in breast cancer pathogenesis.Cancer biology & therapy · 2025Review
- The Paraoxonase (International journal of molecular sciences · 2025Review
- Leptin and leptin receptor expression as biomarkers for breast cancer: a retrospective study.BMC cancer · 2023Article
- Review
- Using machine learning to identify gene interaction networks associated with breast cancer.BMC cancer · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveBreast cancer is the most common cancer in American women, except for skin cancers. In this meta-analysis, the associations of polymorphisms within paraoxonase 1 (PON1), leptin (LEP) and leptin receptor (LEPR) genes with susceptibility to breast cancer were comprehensively evaluated.
methodsA universal search in PubMed, Scopus, CNKI, SID, Web of Knowledge and Google Scholar was performed to identify relevant studies up to 01 May, 2021. The strength of the associations was estimated by Odds ratios (ORs) with 95% confidence intervals (95% CIs).
resultsA total of 39 case-control studies including 7 studies with 2005 cases and 2748 controls were on PON1 rs662, 6 studies with 2,031 cases and 1,973 controls on PON1 rs854560, 12 studies with 3,444 cases and 3,583 controls on LEP rs7799039, and 14 studies with 5,330 cases and 6,188 controls on LEPR rs1137101 were selected. Pooled data showed that PON1 rs662 and rs854560 polymorphisms were associated with risk of breast cancer in overall population, but not LEP rs7799039 and LEPR rs1137101.
conclusionsOur pooled data revealed that the PON1 rs662 and rs854560 polymorphisms were significantly associated with an increased risk of breast cancer in the overall population. However, LEP rs7799039 and LEPR rs1137101 polymorphisms were not associated.
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Registered trials
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 Socratic graph.