BACKGROUND: Uterine leiomyosarcoma(uLMS) is a rare malignant tumor with low clinical specificity and poor prognosis.There are many studies related to uLMS, however, there is still a lack of metrological analyses with generalization. This study provides a bibliometric study of uLMS. METHODS AND MATERIALS: We chose the Web of Science (WoS) as our main database due to its extensive interdisciplinary coverage. We specifically focused on the literature from the last 20 years to ensure relevance and practicality. By utilizing the WOS core dataset and leveraging the R package "bibliometric version 4.1.0" and Citespace, we performed a comprehensive bibliometric analysis. This allowed us to pinpoint research hotspots and create visual representations, resulting in the retrieval of 2489 pertinent articles. RESULTS: This literature review covers 2489 articles on uterine leiomyosarcoma (uLMS) from the past 20 years. Key findings include an average annual publication rate of 8.75, with a 6.07% yearly growth rate and an average citation count of 17.22. Core+Zone 2 sources contributed 1079 articles and 207 reviews, displaying a 4.98% annual growth rate. The analysis identified top journals, influential authors, and core sources, such as the prevalence of publications from the United States and the dominance of and . Bradford's Law and Lotka's Law highlighted core sources and author productivity, respectively. Thematic mapping and factorial analysis revealed research clusters, including etiology, diagnosis, treatment advancements, and surgical approaches, with prominent themes such as gemcitabine and docetaxel. Overall, this comprehensive analysis provides insights into uLMS literature trends and influential factors. CONCLUSION: This thorough bibliometric analysis, in its whole, illuminates the field's guiding principles while also revealing the subtle patterns within the uLMS literature. The knowledge gained here contributes to the current discussion in uLMS and related scientific fields and provides a solid basis for future research paths.