3. Conclusion
Individualized anticoagulation therapy for cancer-associated thrombosis (CAT) has become a critical component in improving patient outcomes and quality of life. Through the analysis presented in this review, it is evident that precise risk assessment forms the foundation of individualized treatment. The integration of multidimensional biomarkers, coupled with the continuous development of dynamic monitoring techniques, enables clinicians to scientifically identify high-risk patients and rationally develop anticoagulation strategies, thereby minimizing the incidence of recurrent thrombosis and bleeding complications.
In terms of selecting and adjusting anticoagulant medications, research indicates that relying solely on traditional clinical characteristics is no longer sufficient to meet individualized needs. Incorporating genetic background into assessments provides more accurate predictions for pharmacokinetics and pharmacodynamics. Different studies have shown varying degrees of safety and efficacy for anticoagulant drugs, reflecting the complexity of individual heterogeneity. As medical experts, we must adopt a balanced perspective on these studies, recognizing that the design of individualized treatment plans must seek the optimal intersection between clinical experience, molecular genetic information, and the specific conditions of the patient, rather than following a single standardized pathway.
Furthermore, multidisciplinary collaboration has demonstrated irreplaceable value in CAT management. Close cooperation among experts in oncology, hematology, genetics, and clinical pharmacology can optimize treatment plans from multiple dimensions. The introduction of emerging technologies such as artificial intelligence and big data analytics has further advanced the precision of CAT treatment. These technologies not only enhance the accuracy of risk prediction but also accelerate the dynamic adjustment of treatment plans, achieving true individualized healthcare.
Future research should focus more on integrating multi-omics data, including genomics, transcriptomics, proteomics, and other multi-level information, combined with intelligent tools like machine learning and deep learning, to construct more comprehensive and dynamic risk assessment models. Through these technological means, we aim to achieve maximum therapeutic efficacy while ensuring safety, making the management of CAT patients more scientific, precise, and personalized.
In summary, individualized anticoagulation therapy for cancer-associated thrombosis is in a phase of rapid development. In the face of differing viewpoints and findings from various studies, a scientifically cautious attitude is essential. It is crucial to fully consider patient heterogeneity and treatment risks, leveraging multidisciplinary collaboration and technological innovation to advance clinical practice continuously. This not only helps improve patient survival rates and quality of life but also sets important precedents for the future development of precision medicine.
