The Significance of Living Evidence in Crafting Future Oncology Decision-Making Support by Artificial Intelligence
In the world of oncology, making the right treatment choice can be a matter of life and death. Traditionally, oncologists have had to sift through hundreds of studies manually to make informed decisions, a process that is not only time-consuming but also prone to errors. However, a new paradigm is emerging that aims to address this bottleneck - Living Evidence.
Living Evidence is a concept that seeks to provide real-time, up-to-date evidence to healthcare professionals, improving treatment decisions and patient outcomes. It is not intended to replace systematic reviews, but rather to augment them. AI algorithms filter through the sheer volume of new publications, screen for relevance, raise quality issues, and update evidence maps in real time.
Systematic reviews are the gold standard for evaluating medical evidence, preventing risks of cherry-picking studies, overvaluing anecdotes, or relying on unverified opinions. In oncology, they play a crucial role in ensuring the right treatment choice is made. However, keeping up with the constant stream of new research and evidence published in oncology journals can be challenging.
Anna Forsythe, the Founder & President of Oncoscope-AI, a real-time oncology evidence platform, is at the forefront of this revolution. The future of oncology decision support must be built on living evidence, combining the speed of algorithms with the rigor of systematic reviews. This creates a system where updates flow seamlessly into practice but are always filtered through an evidence-based lens.
The stakes are high in oncology treatment decisions. Accepting unverified chatbot outputs at face value could lead to dangerous shortcuts, especially in oncology where decisions can never be undone. Therefore, it is essential that systems like Oncoscope-AI earn the trust of healthcare professionals by proving they are comprehensive, transparent, and continually refreshed.
The human-AI partnership leverages each party's strength. Machines are better at speed and repetition, while humans are better at judgment and context. AI should not replace the hierarchy of evidence. It should strengthen it, ensuring oncologists are equipped with tools that deliver both speed and rigor, empowering them to make decisions that are fast, safe, and truly evidence-based.
Organizations involved in developing live, real-time evidence systems in oncology include the Institute for Biometry and Registry Research at MHB Fontane, the German Cancer Society (Deutsche Krebsgesellschaft), German Cancer Aid (Deutsche Krebshilfe), and the Association of the Scientific Medical Societies in Germany (AWMF). These organizations collaborate on oncology guideline programs that support evidence-based treatment decisions.
The lesson of evidence hierarchies extends beyond oncology to other fields such as cardiology, infectious disease, finance, and aviation safety, where systematic, comprehensive evidence is crucial. As the deluge of new medical information continues, the role of AI in healthcare is undeniable. However, caution is necessary to avoid abandoning the safeguards that make modern medicine safe. Trust is the currency of oncology, and systems must earn that trust by proving they are comprehensive, transparent, and continually refreshed.
