Abstract 1060P
Background
For cancer neoadjuvant and adjuvant immunotherapy, after several decades of evolution, the field currently possesses an enormous volume of underutilized data. Informatics analysis to thoroughly excavate the similarities and differences between the two is desperately necessary.
Methods
Extensive relevant studies (n=1373) on neoadjuvant and adjuvant immunotherapy from 2014-2023 were collected for quantitative, hierarchical clustering, and comparative analyses after vigorous quality control.
Results
Over the last decade, neoadjuvant and adjuvant immunotherapy enjoyed promising development status (Annual Growth Rate: 25.18% vs 6.52%) and global collaboration (International Co-authorships: 19.93% vs 19.84%). Unsupervised hierarchical clustering identified their dominant research clusters, in which Cluster 4: Balance of neoadjuvant immunotherapy efficacy and safety and Cluster 2: Adjuvant immunotherapy clinical trials are emerging research populations. Burst and regression curve analyses uncovered domain pivotal research signatures, including biomarkers (R2=0.6505, p=0.0086) in neoadjuvant scenarios, and tumor microenvironment (R2=0.5571, p=0.0209) in adjuvant scenarios. The Walktrap algorithm further revealed that "non-small cell lung cancer, immune checkpoint inhibitors, melanoma" and "melanoma, hepatocellular carcinoma, dendritic cells" (Relevance Percentage: 100% vs 100%, Development Percentage: 37.5% vs 17.1%) are extensively relevant to this field, but remain underdeveloped. Furthermore, comprehensive quantitative comparisons revealed that this field's spotlight on neoadjuvant immunotherapy overtook adjuvant immunotherapy entirely after 2020; such a qualitative finding will facilitate proper decision-making for subsequent research and avoid significant wastage of healthcare resources.
Conclusions
This cross-sectional study comparatively analyzed the fundamental metrological information in cancer neoadjuvant and adjuvant immunotherapy, identified their pivotal research signatures, and provided some substantial predictions for their subsequent preclinical and clinical research.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
Has not received any funding.
Disclosure
All authors have declared no conflicts of interest.
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