SynthesisOncology research2025
Current status, hotspots, and trends in cancer prevention, screening, diagnosis, treatment, and rehabilitation: A bibliometric analysis.
Synthesis in Oncology research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Beyond the primary site: Molecular insights and clinical implications of cancer metastatic overlap between lung and urological organ cancers (Review).Molecular medicine reports · 2026Review
- A bibliometric analysis of research trends and future directions in early detection of pancreatic cancer.Discover oncology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objectives: Decades of clinical and fundamental research advancements in oncology have led to significant breakthroughs such as early screening, targeted therapies, and immunotherapy, contributing to reduced mortality rates in cancer patients. Despite these achievements, cancer continues to be a major public health challenge. This study employs bibliometric techniques to visually analyze the English literature on cancer prevention, screening, diagnosis, treatment, and rehabilitation. Methods: We systematically reviewed publications from 01 March 2014, to 01 March 2024, indexed in the Web of Science core collection. Tools such as VOSviewer Version 1.6.20 is characterized by its core idea of co-occurrence clustering. CiteSpace 6.3.R3 is distinguished by its powerful capabilities in bibliometric analysis, including co-citation analysis, co-occurrence analysis of keywords, author collaboration network analysis, and journal co-citation analysis, providing effective insights into research hotspots and detecting emerging trends. Bibliometrix version 3.0.3 offers rich visualization features, including collaboration network diagrams, citation distribution graphs, and keyword clouds. facilitated the analysis of the literature, helping to map out the current research landscape, identify pressing issues, and discern emerging trends, thus offering insights for future research directions. Results: The analysis revealed that major research hotspots include lung and breast cancer. Attention is predominantly concentrated on cancer treatment, subdivided into targeted therapy, immunotherapy, traditional Chinese medicine, and the development of new anticancer drugs. Significant terms identified in the study include immune checkpoint inhibitors, tumor microenvironment, and cancer stem cells. Conclusion: This bibliometric analysis highlights the evolving directions in oncology research, pinpointing nanotherapy, resistance to targeted therapies, and the integration of artificial intelligence as pivotal future research avenues in the prevention, screening, diagnosis, treatment, and rehabilitation of cancer.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.