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Researchers at the University of Leeds have developed an AI algorithm that could significantly improve the assessment of early-stage bowel cancer recurrence risk.
This algorithm measures the levels of CD3, a type of immune cell, in tumour tissue samples. By analysing samples from 868 patients in the Quasar trial, the researchers created a "CD3 Score" that quantifies CD3 cell counts in different tumour areas.
The study found that patients with higher CD3 Scores, indicating lower levels of CD3 cells, had a greater risk of cancer recurrence. Specifically, the data showed an 8.5% overall chance of bowel cancer returning within two years after surgery and chemotherapy.
The AI effectively identified low-risk patients, with a 3.8% chance of recurrence with chemotherapy, compared to 6.6% without it. High-risk patients had a 23.5% chance of recurrence without chemotherapy, reduced to 14.3% with the treatment.
Current methods for determining which early-stage bowel cancer patients need chemotherapy are unreliable, often leading to unnecessary treatments or missed cases where cancer recurs.
The CD3 Score provides a more accurate indication of recurrence risk, particularly for stage II colon cancer patients, who generally have a lower risk of recurrence. This new method can significantly aid doctors and patients in making informed decisions about post-surgery chemotherapy.
The study's findings highlight the potential of the CD3 Score test to become an essential tool in clinical settings. It is fast, accurate, and straightforward, making conversations about chemotherapy much easier for patients and their doctors.
The research team collaborated with clinical research leaders who have patented the CD3 Score, emphasising its importance in guiding chemotherapy options. Bowel cancer advocacy groups have also praised the study, seeing it as a positive step for improving treatment guidance and patient outcomes.
