ReviewCureus2023
Research Landscape of Lymphovascular Invasion in Oral Squamous Cell Carcinoma: A Bibliometric Analysis From 1994 to 2023.
Review in Cureus, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The primary factor affecting tumor biology is neo-lymphangiogenesis in solid epithelial malignancies like oral squamous cell carcinoma (OSCC). Determining the impact of lymphovascular invasion is critical in order to determine OSCC's locoregional and global dissemination. Bibliometric landscapes are vital to learning about the most recent advancements in the aforementioned topic because the ongoing research in OSCC is multifaceted. This analysis can reveal the progressions that might modernize OSCC diagnosis and treatment. The present analysis has been therefore undertaken to study the relevance and effects of lymphovascular invasion in OSCC utilizing co-occurrence of keywords analysis and co-authorship analysis in the PubMed database. The keywords included "lymphovascular invasion in oral squamous cell carcinoma" using the Boolean operator (AND). A cross-sectional bibliometric analysis of full-text articles from 1994 to 2023 using VOSviewer (Version 1.6.19; Centre for Science and Technology Studies, Leiden University, The Netherlands) was performed. The data obtained was analyzed for co-occurrence and co-authorship analysis using the VOSviewer standard protocol. The query revealed 296 searches in the PubMed database. Seven clusters were found with default colors in the representation of the entire term co-occurrence network, which also displayed a total link strength of 22,262. The items were categorized into clusters based on their commonalities. The labels' weights, as determined by links and occurrences, did not depend on one another, and the co-occurrence of keywords does not imply a causal association. In the item density visualization, item labels represented individual things. The number of items from a cluster that was close to the point was represented by the weight given to its color, which was formed by combining the colors of other clusters. A network of 57 authors who matched the search parameters was discovered by the co-authorship analysis. The network visualization map displayed three clusters with a total link strength of 184. The quantity of co-authorship relationships and the number of publications did not appear to be significantly correlated. In conclusion, this investigation uncovered a sizable body of bibliometric data that emphasizes key trends and advancements in the aforementioned theme. The observed variances may be a result of the various objectives of the researchers and journals, who collaborate to provide the best possible literature dissemination.
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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.