KEY TAKEAWAYS
- The REVERT Interventional trial aimed to enhance clinical decision-making using ML algorithms.
- AI and ML can optimize mCRC treatment through tailored strategies, enhancing precision and efficacy.
Metastatic colorectal cancer (mCRC) presents complex challenges in treatment decision-making due to its diverse genetic and molecular profiles and variable treatment responses. Traditional methods often lack the specificity required for personalized care.
Eliza Froicu and colleagues aimed to evaluate the utility of machine learning (ML) algorithms in enhancing clinical decision-making for mCRC treatment, aiming to advance precision medicine through data-driven insights and tailored therapeutic approaches.
Researchers analyzed 29 patients with mCRC, collecting comprehensive data on demographics, genetic profiles, treatment responses, and outcomes. They used ML algorithms, specifically Multiple Kernel Learning, to determine the best treatment plans tailored to each patient’s unique profile.
The results showed that the patients had a mean progression-free survival (mPFS) of 8.87 months, with those having lung metastases experiencing shorter durations at 6.25 months. The CAPOX regimen showed the best outcomes, with an mPFS of 9.25 months.
Objective response rates (ORR) were seen in 65.5% of cases, and 82.8% experienced clinical benefits. These results suggest that AI algorithms could significantly impact PFS and ORR in treating metastatic colorectal cancer.
The study concluded that AI and ML algorithms can advance precision medicine in mCRC by providing tailored treatment strategies, optimizing therapeutic approaches, and maximizing treatment effectiveness. However, further validation is crucial to enhance personalized care.
The trial was sponsored by University of Rome Tor Vergata.
Source: https://cslide.ctimeetingtech.com/esmogi24hybrid/attendee/confcal/show/session/3
Clinical Trial: https://www.clinicaltrials.gov/study/NCT05396807
Froicu E, Afrasanie VA, Alexa-Stratulat T, et al. (2024). “Exploring the potential of Artificial intelligence: Revolutionizing treatment decision-making in metastatic colorectal cancer.” Presented at ESMO GI 2024. (36P)
