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<p>Pancreatic cancer remains one of the most lethal malignancies globally, with its surgical management undergoing profound transformation driven by minimally invasive approaches, particularly robot-assisted systems. This study employs bibliometric analysis combined with thematic synthesis to delineate the research evolution, knowledge structure, and emerging trends in robot-assisted pancreatic surgery from 1999 to 2025. Using CiteSpace software, we analyzed 202 publications from the Web of Science database. Our analysis revealed a distinct three-phase evolutionary trajectory: an emergence phase (1999–2010) focused on technical feasibility, a rapid development phase (2011–2021) emphasizing procedural standardization, and a recent maturation phase (2022–2025) shifting toward outcome evaluation and collaborative research. The knowledge structure has evolved from a singular surgical focus to a multidimensional network encompassing tumor biology, precision imaging, and patient-centered outcomes. “Robotic surgery” serves as a key bridging node connecting these domains. Burst keyword analysis highlights the recent emergence of “international study group,” “cohort studies,” and “surgical outcomes” as predominant research fronts. Collaborative network analysis reveals the United States as the leading contributor, while Italy and Germany serve as crucial international hubs. China demonstrates substantial research output but limited integration into global collaborative networks. While bibliometric trends reflect significant research momentum and technological convergence, this analysis underscores the persistent gap between technical innovation and robust clinical evidence. Future advancement requires prioritized investment in international multicenter trials, standardized training protocols, and deeper integration of artificial intelligence and molecular navigation technologies to substantiate clinical value and improve patient outcomes in this challenging surgical domain.</p>

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Bridging the innovation-evidence chasm: a critical appraisal and roadmap for robotic pancreatic cancer surgery

  • 期刊论文

  • 发表日期：

    2026年3月7日

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  • Jinxin Zhu,
  • Jiarui Jiang,
  • Muyue Liu,
  • Weikang Hu,
  • Jianzhen Lin,
  • Kuirong Jiang

摘要

Pancreatic cancer remains one of the most lethal malignancies globally, with its surgical management undergoing profound transformation driven by minimally invasive approaches, particularly robot-assisted systems. This study employs bibliometric analysis combined with thematic synthesis to delineate the research evolution, knowledge structure, and emerging trends in robot-assisted pancreatic surgery from 1999 to 2025. Using CiteSpace software, we analyzed 202 publications from the Web of Science database. Our analysis revealed a distinct three-phase evolutionary trajectory: an emergence phase (1999–2010) focused on technical feasibility, a rapid development phase (2011–2021) emphasizing procedural standardization, and a recent maturation phase (2022–2025) shifting toward outcome evaluation and collaborative research. The knowledge structure has evolved from a singular surgical focus to a multidimensional network encompassing tumor biology, precision imaging, and patient-centered outcomes. “Robotic surgery” serves as a key bridging node connecting these domains. Burst keyword analysis highlights the recent emergence of “international study group,” “cohort studies,” and “surgical outcomes” as predominant research fronts. Collaborative network analysis reveals the United States as the leading contributor, while Italy and Germany serve as crucial international hubs. China demonstrates substantial research output but limited integration into global collaborative networks. While bibliometric trends reflect significant research momentum and technological convergence, this analysis underscores the persistent gap between technical innovation and robust clinical evidence. Future advancement requires prioritized investment in international multicenter trials, standardized training protocols, and deeper integration of artificial intelligence and molecular navigation technologies to substantiate clinical value and improve patient outcomes in this challenging surgical domain.