Document Type : Systematic Review and Meta-analysis
Authors
1
Breast Health & Cancer Research Center, Iran University of Medical Sciences, Tehran, Iran.
2
Department of General Surgery, School of Medicine, Iran University of Medical Sciences, Tehran, Iran.
3
Afshar Hospital Cardiovascular Research Center, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
4
Urology Research Center, Razi Hospital, School of Medicine, Guilan University of Medical Sciences, Rasht, Iran.
5
Department of Colorectal Surgery, Imam Reza Hospital, AJA University of Medical Sciences, Tehran, Iran.
6
Department of Obstetrics and Gynecology, School of Medicine, Iran University of Medical Sciences, Tehran, Iran.
7
Student Research Committee, School of Medicine, Ilam University of Medical Sciences, Ilam, Iran.
8
Department of Plastic Surgery, School of Medicine, Iranshahr University of Medical Sciences, Iranshahr, Iran.
9
Hematology and Oncology Research Center, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
Abstract
Background: Cancer surgery is undergoing transformative integration of precision medicine, artificial intelligence (AI), robotics, advanced imaging, and molecular technologies. These innovations promise enhanced surgical precision, improved patient outcomes, and personalized treatment approaches through data-driven decision-making. Methods: A comprehensive systematic literature review was conducted across PubMed, Embase, Cochrane Library, and Web of Science databases from January 2020 to November 2025. Studies were analyzed for clinical applications, therapeutic outcomes, cost-effectiveness, and implementation challenges. Primary endpoints included surgical accuracy, margin status, survival outcomes, complication rates, and technology adoption metrics. Results: Precision medicine utilizing genomic profiling and circulating tumor DNA demonstrated 94.9% sensitivity and 88.8% specificity in multi-cancer detection. The CIRCULATE-Japan GALAXY study showed ctDNA positivity during the molecular residual disease window predicted significantly inferior disease-free survival (HR 11.99; P < 0.0001) and overall survival (HR 9.68; P < 0.0001). AI-assisted surgical systems achieved area under the curve values of 0.76–0.85 in outcome prediction and reduced surgical complications by 25–30%. The da Vinci 5 robotic system demonstrated 43% reduction in tissue damage through force feedback technology. Meta-analysis of 15,137 patients showed robotic pancreatoduodenectomy reduced hospital stays and conversion rates compared to laparoscopy. Fluorescence-guided surgery achieved improved 5-year overall survival (80.6% vs. 66.7%, P = 0.018) in gastric cancer. Mass spectrometry techniques achieved 93.4–97.1% diagnostic accuracy. Perioperative immunotherapy in non-small cell lung cancer reduced recurrence risk by 43% (HR 0.57) and improved pathological complete response rates over 5-fold (RR 5.58). Nanotechnology-based delivery systems reduced cardiac toxicity (6% vs. 21%) while maintaining therapeutic efficacy. Conclusions: The convergence of precision medicine, AI, robotics, and molecular technologies is revolutionizing cancer surgery toward personalized, data-driven interventions with substantial clinical outcome improvements. Implementation challenges including cost, standardization, and healthcare disparities require systematic addressing for widespread adoption.
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