ArticleInternational journal of medical sciences2011
Translational medicine and reliability of single-nucleotide polymorphism studies: can we believe in SNP reports or not?
Article in International journal of medical sciences, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled 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.
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, 1 synthesis or guideline pooled it.
- Genetic variations related to inflammation in suicidal ideation and behavior: A systematic review.Frontiers in psychiatry · 2022Pooled it
- TheCells · 2021Article
- Selective citation in scientific literature on the human health effects of bisphenol A.Research integrity and peer review · 2019Article
- Replication and exploratory analysis of 24 candidate risk polymorphisms for neural tube defects.BMC medical genetics · 2014Article
- Associations of GSTM1*0 and GSTA1*A genotypes with the risk of cardiovascular death among hemodialyses patients.BMC nephrology · 2014Article
- Glutathione S-transferase T1, O1 and O2 polymorphisms are associated with survival in muscle invasive bladder cancer patients.PloS one · 2013Article
- Gastric cancer: Classification, histology and application of molecular pathology.Journal of gastrointestinal oncology · 2012Article
- Single nucleotide polymorphisms as susceptibility, prognostic, and therapeutic markers of nonsmall cell lung cancer.Lung Cancer (Auckland, N.Z.) · 2012Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe number of genetic association studies is increasing exponentially. Nonetheless, genetic association reports are prone to potential biases which may influence the reported outcome.
aimWe hypothesized that positive outcome for a determined polymorphism might be over-reported across genetic association studies analysing a small number of polymorphisms, when compared to studies analysing the same polymorphism together with a high number of other polymorphisms.
methodsWe systematically reviewed published reports on the association of glutathione s-transferase (GST) single-nucleotide polymorphisms (SNPs) and cancer outcome.
resultWe identified 79 eligible trials. Most of the studies examined the GSTM1, theGSTP1 Ile105Val mutation, and GSTT1polymorphisms (n = 54, 57 and 46, respectively). Studies analysing one to three polymorphisms (n = 39) were significantly more likely to present positive outcomes, compared to studies examining more than 3 polymorphisms (n=40) p = 0.004; this was particularly evident for studies analysing the GSTM1polymorphism (p =0.001). We found no significant associations between journal impact factor, number of citations, and probability of publishing positive studies or studies with 1-3 polymorphisms examined.
conclusionsWe propose a new subtype of publication bias in genetic association studies. Positive results for genetic association studies analysing a small number of polymorphisms (n = 1-3) should be evaluated extremely cautiously, because a very large number of such studies are inconclusive and statistically under-powered. Indeed, publication of misleading reports may affect harmfully medical decision-making and use of resources, both in clinical and pharmacological development setting.
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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 OpenQuestion graph.