AI-based big data analysis of user-generated content to understand adherence in oral hormone receptor-positive advanced breast cancer treatment: A literature review and patient-centered approach using natural language procession
- Background: Understanding patients' adherence needs is crucial for the success of therapies, particularly for chronic illnesses and cancer. The shift from intravenous to oral anticancer medication enhances patient independence but may threaten adherence. This study aims to identify patients' concerns and needs for treatment of oral hormone receptor-positive for advanced breast cancer (CDK4/6 inhibitors).
Methodology: A comprehensive literature review on factors influencing patient adherence was conducted, followed by AI-based big data analyses of user-generated content. Techniques such as natural language processing and machine learning-based word embeddings were applied to achieve a patient-centered understanding of adherence.
Results: The literature review shows that adherence is often overlooked in clinical research due to the impracticality of long-term monitoring in most trial designs. This highlights the need for alternative methods such as real-world data and AI-based analyses to understand patients' long-term adherenceBackground: Understanding patients' adherence needs is crucial for the success of therapies, particularly for chronic illnesses and cancer. The shift from intravenous to oral anticancer medication enhances patient independence but may threaten adherence. This study aims to identify patients' concerns and needs for treatment of oral hormone receptor-positive for advanced breast cancer (CDK4/6 inhibitors).
Methodology: A comprehensive literature review on factors influencing patient adherence was conducted, followed by AI-based big data analyses of user-generated content. Techniques such as natural language processing and machine learning-based word embeddings were applied to achieve a patient-centered understanding of adherence.
Results: The literature review shows that adherence is often overlooked in clinical research due to the impracticality of long-term monitoring in most trial designs. This highlights the need for alternative methods such as real-world data and AI-based analyses to understand patients' long-term adherence to treatment. Key factors influencing adherence to oral breast cancer treatment include the cost-benefit ratio in terms of survival and quality of life, realistic expectations regarding side effects, social support and personalized care. AI analysis of user-generated content supports these findings and reveals more frequent discussions on non-adherence in early breast cancer stages. Semantic graphs and topic modeling also identified additional patient concerns and informational needs for better patient communication.
Conclusions: Enhancing patient-centeredness is crucial for improving adherence and persistence to oral treatment for breast cancer. The increased autonomy provided by oral medications offers a significant opportunity for healthcare providers to empower patients in managing their treatment. Comprehensive support, including addressing emotional and psychological issues, is essential, especially in advanced breast cancer stages.…

