{
  "abstract": "Research on neoadjuvant immunotherapy (NAI) is increasingly focusing on immunotherapy-related adverse events (AEs). However, many unknowns remain in this field. Hence, through the machine learning (ML)-driven informatics analysis, this study aimed to profile the global decade-long scientific landscape of AEs of NAI and further reveal its critical issues and directions that deserve deeper exploration. During the past decade, the amount of research in the field of NAI safety has displayed a positive trend (annual growth rate: 30.2%), and it has achieved good global collaboration (international coauthorship: 17.43%). Using an unsupervised clustering algorithm, we identified six dominant research clusters, among which Cluster 1 (standardizing response assessment criteria for NAI to minimize its adverse reactions; average citation=34.86±95.48) had the highest impact and Cluster 6 (efficacy and safety of multiple therapy patterns combination) was an emerging research cluster (temporal central tendency=2022.43, research effort dispersion=0.52), with “irAEs” (s=0.4242 (95% CI: 0.01142 to 0.8371), R2=0.4125, p=0.0453), “ICIs” (immune checkpoint inhibitors) (s=1.127 (95% CI: 0.5403 to 1.714), R2=0.7103, p=0.0022), and “efficacy and safety” (s=0.5455 (95% CI: 0.1145 to 0.9764), R2=0.5157, p=0.0193) showing significant overall growth. More importantly, further hotspot burst analysis indicated “ICI” and “efficacy and safety” as the emerging research focuses, demonstrating that scholars in the field are increasingly aware of the importance of balancing NAI efficacy and safety. In conclusion, this study presents ML-derived evidence that outlines the safety challenges of NAI and highlights the importance of balancing its efficacy and safety for its application in patients with perioperative cancer.",
  "authors": [
    {
      "affiliations": [
        "Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China",
        "State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, China"
      ],
      "name": "Song-Bin Guo"
    },
    {
      "affiliations": [
        "Department of Interventional Radiology, Xinjiang Key Laboratory of Translational Biomedical Engineering Research, Tumor Hospital Affiliated to Xinjiang Medical University, The Third Clinical Medical College of Xinjiang Medical University, Urumqi, China",
        "Department of Minimally Invasive Intervention, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, China"
      ],
      "name": "Deng-Yao Liu"
    },
    {
      "affiliations": [
        "Department of Hematology/Oncology, Fujian Children's Hospital (Fujian Branch of Shanghai Children’s Medical Center), College of Clinical Medicine for Obstetrics and Gynecology and Pediatrics, Fujian Medical University, Fuzhou, China"
      ],
      "name": "Rong Hu"
    },
    {
      "affiliations": [
        "Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China",
        "State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, China"
      ],
      "name": "Zhen-Zhong Zhou"
    },
    {
      "affiliations": [
        "State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, China"
      ],
      "name": "Yuan Meng"
    },
    {
      "affiliations": [
        "Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China",
        "State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, China"
      ],
      "name": "Hai-Long Li"
    },
    {
      "affiliations": [
        "Department of Pharmacology, College of Pharmacy, Jinan University, Guangzhou, China"
      ],
      "name": "Wei-Juan Huang"
    },
    {
      "affiliations": [
        "Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China",
        "State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, China"
      ],
      "name": "Xiao-Peng Tian"
    }
  ],
  "title": "Immune-related adverse events of neoadjuvant immunotherapy in patients with perioperative cancer: a machine-learning-driven, decade-long informatics investigation",
  "uid": "7514e15a-4416-5453-913d-f359e90ebd25"
}