Global Research Trends and Future Perspectives in Salivary Gland Oncology: A Scientometric Evaluation.

Authors

Bruno Špiljak, Monal Yuwanati, Gowri Sivaramkrishnan, Rachael Jahander Khodabux, Anand Ramanathan, Doaa S R Khafaga, Asmaa Abou-Bakr, Tamer Badawy, Akhilanand Chaurasia

Published in

Journal of stomatology, oral and maxillofacial surgery. Pages 102934. Aug 12, 2026. Epub Aug 12, 2026.

Abstract

Salivary gland tumors (SGTs) comprise a heterogeneous group of neoplasms with diverse histopathological and molecular features.
This study aims to provide a comprehensive bibliometric overview of global research trends, key contributors, and thematic developments in salivary gland oncology.
A total of 2,932 relevant publications were retrieved from the Scopus database and analyzed using Bibliometrix (R package) and VOSviewer. The analysis examined publication trends, citation metrics, collaborative networks, keyword co-occurrence, and thematic evolution. Bibliographic coupling and co-citation analyses were conducted to identify influential research topics and author collaborations.
Research output steadily increased over the past two decades, with a marked rise after 2010. The United States, Japan, and Germany were the leading contributors, supported by strong international collaborations. Memorial Sloan Kettering Cancer Centre and MD Anderson Cancer Center emerged as the most productive institutions. Influential authors included Seifert G, Bishop JA, and Nagao T. Highly cited journals were Head and Neck Pathology, Histopathology, and the American Journal of Surgical Pathology. Major thematic clusters included salivary duct carcinoma, immunohistochemistry, pleomorphic adenoma, and adenoid cystic carcinoma. Notably, recent trends showed a growing focus on artificial intelligence (AI) applications and molecular profiling of SGTs.
This bibliometric analysis maps the evolving landscape of salivary gland oncology research. Emphasis should be placed on strengthening global collaborations, advancing molecular diagnostics, and leveraging AI technologies.

PMID:
42586503
Bibliographic data and abstract were imported from PubMed on 13 Aug 2026.

Read full publication at:
Please sign in to see all details.

Stats

1-terrible, 9-excellent. How would you rate this publication? Sign in in to submit your rating.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.