Bibliometric analysis of research trends on the combination of radiotherapy and PARP inhibitors in solid tumors - Chen, Yuxin; Zhang, Zhengkun; Yin, Rutie; Li, Qingli; Zhang, Wenhao (Frontiers in Pharmacology, 2025)
IntroductionRadiotherapy has served as a cornerstone in cancer treatment for over a century. However, the efficacy of radiotherapy is often compromised by the intrinsic and acquired radioresistance of tumors, which can lead to treatment failure and disease recurrence. Recent advancements in preclinical and clinical research have highlighted the potential synergistic efficacy of combining radiotherapy with poly-ADP-ribose polymerase inhibitors (PARPi), offering promising therapeutic avenues for solid tumors. This study employs bibliometric analysis to systematically evaluate the evolution, trends, and intellectual landscape of research on the combination of radiotherapy and PARPi in solid tumors.MethodsPublications addressing the combination of radiotherapy and PARPi for solid tumors between 2005 and 2024 were retrieved from the Web of Science Core Collection (WOSCC) database. Bibliometric assessments were conducted using VOSviewer and CiteSpace to analyze publication trends, collaborative networks, and research foci.ResultsA total of 901 articles were included. The United States dominated research output, with the University of Texas MD Anderson Cancer Center identified as the most productive institution. Hannah Farmer emerged as the most frequently cited author. Keywords co-occurrence analysis revealed a thematic shift from foundational studies on molecular mechanisms, such as DNA damage response and mechanism of action of PARPi, toward clinical investigations evaluating combination therapy efficacy and safety in trials.ConclusionThis bibliometric analysis underscores the rapid growth of research on radiotherapy and PARPi combination therapy, with the United States maintaining a leading role due to its extensive scientific infrastructure and collaborative networks. The field has transitioned from mechanistic explorations to translational and clinical applications, reflecting progress toward therapeutic optimization. These findings provide a comprehensive overview of the knowledge structure within this domain and serve as a strategic reference for guiding future research priorities and clinical implementations.