A needed (r)evolution to improve colorectal cancer screening: binding patient-centered/shared decision-making medicine with large language models in an emerging knowledge society

Performing procedures in healthy but high risk population is a major challenge for traditional cancer screening methods [1]. One of the most difficult procedures to accept is colonoscopy, which is nevertheless the best way of identifying and eventually removing early colorectal cancer (CRC) lesions. The lack of clarity about why it should be performed is however very worrying, as even first-degree relatives of patients with CRC have reservations about giving their consent (only 15.4% have had a colonoscopy in the previous 5 years) [2]. These types of reservations, which would be greater in patients with no family history of CRC, could result in an inadequate procedure that should be rescheduled or even cancelled with all the associated underlying costs [3]. In addition, the increase in CRC among younger patients requires new, more effective communication strategies. Although phone calls, text messages, and social networks, have been used successfully, the use of large language models (LLMs) has not been adequately evaluated in CRC screening in open populations and health professionals.