Breast cancer's global burden requires not only standardized care but also the ability to adapt treatment based on regional and clinical differences. In high-income countries, advanced diagnostics and treatments are available, while low- and middle-income countries (LMICs) face resource constraints. These disparities necessitate region-specific adaptations of global guidelines, ensuring that all patients receive optimal care despite varying access to healthcare resources. As precision medicine and artificial intelligence (AI) transform breast cancer care, the challenge remains to integrate these advancements into diverse healthcare settings. Based on these challenges, deeper research into accessible and scalable treatment models is essential.
A recent editorial by Michael Gnant from Medical University of Vienna, published (DOI: 10.20892/j.issn.2095-3941.2025.0674)in Cancer Biology & Medicine in March 2026, explores how international guidelines shape breast cancer management worldwide. The study discusses how global frameworks, such as those by the National Comprehensive Cancer Network (NCCN), European Society for Medical Oncology (ESMO), and the St. Gallen International Breast Cancer Conference, help standardize care but must be adapted to regional healthcare infrastructures. With the rise of precision medicine and AI, these guidelines are evolving to incorporate personalized treatments, enhancing patient outcomes across diverse global settings.
Breast cancer care is evolving rapidly due to advancements in precision medicine and AI. International guidelines have long served as the foundation of breast cancer treatment, ensuring evidence-based, standardized care. However, as breast cancer is not a single disease but a spectrum of subtypes, these guidelines must be flexible enough to address the diverse biological behaviors of tumors. For example, molecular subtyping has led to targeted therapies, such as endocrine therapies for luminal A tumors and HER2-targeted treatments for HER2-enriched cancers. Furthermore, AI is enhancing diagnostic accuracy by analyzing imaging, genomic data, and patient records to assist clinicians in making more informed treatment decisions. While these advances have made precision medicine the future of breast cancer care, challenges remain, especially in LMICs where access to these technologies is limited. AI’s integration into clinical decision-making tools and its potential to improve patient stratification is also discussed, demonstrating how intelligent standardization can be achieved by harmonizing global guidelines with the capabilities of AI and molecular diagnostics.
"AI and precision medicine are not only transforming breast cancer care but also offering a way to tailor treatment to individual patients' needs, regardless of where they live," says Michael Gnant, an expert in breast cancer treatment. "While international guidelines provide the foundation, the future lies in integrating these cutting-edge technologies to ensure optimal care for every patient, everywhere."
The integration of AI into breast cancer treatment offers the potential to drastically improve diagnostic accuracy and patient outcomes. By incorporating molecular diagnostics and biomarker-driven therapies, clinicians can offer personalized treatments that target the specific biology of a patient's tumor. In LMICs, AI can help bridge the gap in resources by providing remote diagnostic support and guiding treatment decisions based on available capabilities. As the field continues to evolve, it is crucial to ensure equitable access to these innovations, ensuring that all breast cancer patients benefit from the latest advancements in care.
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References
DOI
10.20892/j.issn.2095-3941.2025.0674
Original Source URL
https://doi.org/10.20892/j.issn.2095-3941.2025.0674
About Cancer Biology & Medicine
Cancer Biology & Medicine (CBM) is a peer-reviewed open-access journal sponsored by China Anti-cancer Association (CACA) and Tianjin Medical University Cancer Institute & Hospital. The journal monthly provides innovative and significant information on biological basis of cancer, cancer microenvironment, translational cancer research, and all aspects of clinical cancer research. The journal also publishes significant perspectives on indigenous cancer types in China. The journal is indexed in SCOPUS, MEDLINE and SCI (IF 8.4, 5-year IF 6.7), with all full texts freely visible to clinicians and researchers all over the world (http://www.ncbi.nlm.nih.gov/pmc/journals/2000/).