ArticleDiscover oncology2025
The application of mendelian randomization in cancer research: a bibliometric analysis.
Article in Discover oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cancer is a major public health and economic issue faced globally today, significantly affecting human health and life. Due to various constraints, exploring the causal relationship between risk factors and cancer is challenging and not exactly accurate. The advent of Mendelian randomization (MR) effectively addresses these issues, providing new avenues for exploring causal relationships. We downloaded literature related to the application of MR in cancer from the Web of Science Core Collection (WoSCC) from 2005 to October 21, 2024, limiting the document type to articles and the language to English, resulting in a total of 2058 articles. We downloaded them in plain text format and extracted information on countries, authors, institutions, keywords, journals, citation counts, and publication dates, utilizing VOSviewer, CiteSpace, and R language for bibliometric analysis. From 2005 to 2024, the number of publications on the application of MR in cancer has shown a growth trend. China was the most productive country (1305); the University of Bristol was the most prolific institution (213); Smith, George Davey published the most articles in this field (59) with a total citation count of 5344; the most prolific journal in this field is Scientific Reports (71). Chronic diseases and cancer, inflammation and cancer, and sex hormones and cancer are three hot topics in the current research on the application of MR in cancer. In the future, optimizing statistical methods, standardizing research processes, collecting data from a broader range of populations, expanding data scale, and integrating other research methods to enhance research quality will be the development trends of MR in cancer research. In summary, this study employed bibliometric methods to comprehensively analyze the literature on the application of MR in cancer over the past 20 years, evaluating the historical development, current applications, research hotspots, and future trends of MR in the field of cancer.
Identifiers
What OpenQuestion holds
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.