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Medscape
16-05-2025
- Health
- Medscape
Colorectal Cancer Screening Choices: Is Compliance Key?
SAN DIEGO — In the ever-expanding options for colorectal cancer (CRC) screening, blood tests using precision medicine are becoming more advanced and convenient than ever; however, caveats abound, and when it comes to potentially life-saving screening measures, picking the optimal screening tool is critical. Regarding tests, 'perfect is not possible,' said William M. Grady, MD, of the Fred Hutchinson Cancer Center, University of Washington School of Medicine, in Seattle, who took part in a debate on the pros and cons of key screening options at Digestive Disease Week (DDW) 2025. 'We have to remember that that's the reality of colorectal cancer screening, and we need to meet our patients where they live,' said Grady, who argued on behalf of blood-based tests, including cell-free (cf) DNA (Shield, Guardant Health) and cfDNA plus protein biomarkers (Freenome). A big point in their favor is their convenience and higher patient compliance — better tests that don't get done do not work, he stressed. He cited data that showed suboptimal compliance rates with standard colonoscopy: Rates range from about 70% among non-Hispanic White individuals to 67% among Black individuals, 51% among Hispanic individuals, and the low rate of just 26% among patients aged between 45 and 50 years. With troubling increases in CRC incidence among younger patients, 'that's a group we're particularly concerned about,' Grady said. Meanwhile, studies show compliance rates with blood-based tests are ≥ 80%, with similar rates seen among those racial and ethnic groups, with lower rates for conventional colonoscopy, he noted. Importantly, in terms of performance in detecting CRC, blood-based tests stand up to other modalities, as demonstrated in a real-world study conducted by Grady and his colleagues showing a sensitivity of 83% for the cfDNA test, 74% for the fecal immunochemical test (FIT) stool test, and 92% for a multitarget stool DNA test compared with 95% for colonoscopy. 'What we can see is that the sensitivity of blood-based tests looks favorable and comparable to other tests,' he said. Among the four options, cfDNA had a highest patient adherence rate (85%-86%) compared with colonoscopy (28%-42%), FIT (43%-65%), and multitarget stool DNA (48%-60%). 'The bottom line is that these tests decrease CRC mortality and incidence, and we know there's a potential to improve compliance with colorectal cancer screening if we offer blood-based tests for average-risk people who refuse colonoscopy,' Grady said. Blood-Based Tests: Caveats, Harms? Arguing against blood-based tests in the debate, Robert E. Schoen, MD, MPH, professor of medicine and epidemiology, Division of Gastroenterology, Hepatology and Nutrition, at the University of Pittsburgh, Pittsburgh, checked off some of the key caveats. While the overall sensitivity of blood-based tests may look favorable, these tests don't detect early CRC well,' said Schoen. The sensitivity rates for stage 1 CRC are 64.7% with Guardant Health and 57.1% with Freenome. Furthermore, their rates of detecting advanced adenomas are very low; the rate with Guardant Health is only about 13%, and with Freenome is even lower at 12.5%, he reported. These rates are 'similar to the false positive rate, with poor discrimination and accuracy for advanced adenomas,' Schoen said. 'Without substantial detection of advanced adenomas, blood-based testing is inferior [to other options].' Importantly, the low advanced adenoma rate translates to a lack of CRC prevention, which is key to reducing CRC mortality, he noted. Essential to success with blood-based biopsies, as well as with stool tests, is the need for a follow-up colonoscopy if results are positive, but Schoen pointed out that this may or may not happen. He cited research from FIT data showing that among 33,000 patients with abnormal stool tests, the rate of follow-up colonoscopy within a year, despite the concerning results, was a dismal 56%. 'We have a long way to go to make sure that people who get positive noninvasive tests get followed up,' he said. In terms of the argument that blood-based screening is better than no screening at all, Schoen cited recent research that projected reductions in the risk for CRC incidence and mortality among 100,000 patients with each of the screening modalities. Starting with standard colonoscopy performed every 10 years, the reductions in incidence and mortality would be 79% and 81%, respectively, followed by annual FIT, at 72% and 76%; multitarget DNA every 3 years, at 68% and 73%; and cfDNA (Shield), at 45% and 55%. Based on those rates, if patients originally opting for FIT were to shift to blood-based tests, 'the rate of CRC deaths would increase,' Schoen noted. The findings underscore that 'blood testing is unfavorable as a 'substitution test,'' he added. 'In fact, widespread adoption of blood testing could increase CRC morbidity.' 'Is it better than nothing?' he asked. 'Yes, but only if performance of a colonoscopy after a positive test is accomplished.' What About FIT? Arguing that stool-based testing, or FIT, is the ideal choice as a first-line CRC test Jill Tinmouth, MD, PhD, a professor at the University of Toronto, Ontario, Canada, pointed to its prominent role in organized screening programs, including regions where resources may limit the widespread utilization of routine first-line colonoscopy screening. In addition, it narrows colonoscopies to those that are already prescreened as being at risk. Data from one such program, reported by Kaiser Permanente of Northern California, showed that participation in CRC screening doubled from 40% to 80% over 10 years after initiating FIT screening. CRC mortality over the same period decreased by 50% from baseline, and incidence fell by as much as 75%. In follow-up colonoscopies, Tinmouth noted that collective research from studies reflecting real-world participation and adherence to FIT in populations in the United Kingdom, the Netherlands, Taiwan, and California show follow-up colonoscopy rates of 88%, 85%, 70%, and 78%, respectively. Meanwhile, a recent large comparison of biennial FIT (n = 26,719) vs one-time colonoscopy (n = 26,332) screening, the first study to directly compare the two, showed noninferiority, with nearly identical rates of CRC mortality at 10 years (0.22% colonoscopy vs 0.24% FIT) as well as CRC incidence (1.13% vs 1.22%, respectively). 'This study shows that in the context of organized screening, the benefits of FIT are the same as colonoscopy in the most important outcome of CRC — mortality,' Tinmouth said. Furthermore, as noted with blood-based screening, the higher participation with FIT shows a much more even racial/ethnic participation than that observed with colonoscopy. 'FIT has clear and compelling advantages over colonoscopy,' she said. As well as better compliance among all groups, 'it is less costly and also better for the environment [by using fewer resources],' she added. Colonoscopy: 'Best for First-Line Screening' Making the case that standard colonoscopy should in fact be the first-line test, Swati G. Patel, MD, director of the Gastrointestinal Cancer Risk and Prevention Center at the University of Colorado Anschutz Medical Center, Aurora, Colorado, emphasized the robust, large population studies showing its benefits. Among them is a landmark national policy study showing a significant reduction in CRC incidence and mortality associated with first-line colonoscopy and adenoma removal. A multitude of other studies in different settings have also shown similar benefits across large populations, Patel added. In terms of its key advantages over FIT, the once-a-decade screening requirement for average-risk patients is seen as highly favorable by many, as evidenced in clinical trial data showing that individuals highly value tests that are accurate and do not need to be completed frequently, she said. Research from various other trials of organized screening programs further showed patients crossing over from FIT to colonoscopy, including one study of more than 3500 patients comparing colonoscopy and FIT, which had approximately 40% adherence with FIT vs nearly 90% with colonoscopy. Notably, as many as 25% of the patients in the FIT arm in that study crossed over to colonoscopy, presumably due to preference for the once-a-decade regimen, Patel said. 'Colonoscopy had a substantial and impressive long-term protective benefit both in terms of developing colon cancer and dying from colon cancer,' she said. Regarding the head-to-head FIT and colonoscopy comparison that Tinmouth described, Patel noted that a supplemental table in the study's appendix of patients who completed screening does reveal increasing separation between the two approaches, favoring colonoscopy, in terms of longer-term CRC incidence and mortality. The collective findings underscore that 'colonoscopy as a standalone test is uniquely cost-effective,' in the face of costs related to colon cancer treatment. Instead of relying on biennial tests with FIT, colonoscopy allows clinicians to immediately risk-stratify those individuals who can benefit from closer surveillance and really relax surveillance for those who are determined to be low risk, she said.
Medscape
15-05-2025
- Health
- Medscape
AI in Ulcerative Colitis: Enhancing Clinical Workflow
Ryan W. Stidham, MD, MS Artificial intelligence (AI) is used in ulcerative colitis to assist in the assessment, monitoring, and management of disease. To explain how this technology is being applied in the clinical setting, Janelle McSwiggin, MSN, RN, spoke with Ryan W. Stidham, MD, MS, associate professor in the Division of Gastroenterology at University of Michigan Health System. Read on to learn more. In terms of real-time clinical applications, how can AI-based systems assist healthcare providers during an endoscopy? There are several ways in which AI is improving endoscopy for IBD using computer vision technologies. For instance, can our existing disease scoring be standardized and perfectly replicated as if it were performed by an expert? Can machines be used to detect, measure, and count all the disease features, like ulcers, erythema, or polyps, for new scores and evaluation tools that would be informative but too impractical and tedious for clinicians to perform? AI can do all of these things during endoscopy and may reshape how we diagnose and monitor IBD by powering new ways to describe mucosal injury. AI during endoscopy is also proving to help in deciding when and where to biopsy. Commercial systems are already helping detect polyps in real time during the procedure. Experimental systems are also showing promise in predicting whether a polyp is a precancerous adenoma or a benign lesion. In the near future, AI will determine whether the lesion is an adenoma, and rather than sending it to a pathologist for confirmation, it can simply be discarded. Alternatively, suspect polyps that are confidently determined to be benign may simply be left in place potentially, without resection. Similarly, in IBD, there is hope that AI will help detect high risk precancerous tissue that historically has been difficult to see. How is AI improving endoscopic evaluation in ulcerative colitis, and what are the benefits of using AI over traditional scoring methods? During a colonoscopy, the clinician is looking at the mucosa to assess the degree of ulceration, erythema, scarring, and even polyps to determine disease severity and quality. Established scores like the Mayo endoscopic score summarize severity with a 0-3 score, although there have been challenges in standardizing scoring, as even experts may disagree on exact grade. AI is already helping automate and standardized the familiar endoscopic scoring systems. Multiple groups have shown the ability to replicate the Mayo endoscopic score and other scores, including the Ulcerative Colitis Endoscopic Index of Severity (UCEIS). These scoring systems form the core of not only standardized endoscopic assessment but also a key endpoint in therapeutic clinical trials. New commercially available technology is digitally recording endoscopic video and providing automated IBD scoring in the background, which helps in objective disease grading, understanding UC population health, and helping to identify patients for clinical trials. However, there is so much more detail and nuance in disease descriptions than a 0, 1, 2, 3 can capture. The appearance of ulceration, the distribution of features, the changes over time are all factored in a seasoned clinician's perspective for describing disease. Quantifying the detail and interacting features considered by experts is difficult to convert into a simple score. Our group has used AI to develop the Cumulative Disease Score (CDS), where IBD features are detected and quantified every 1-2 centimeters. CDS and similar approaches will help better quantify disease to separate the patient with a small patch of severe disease from someone with extensive or severe disease. Other groups look at the same issues differently and are using AI to develop new severity rating definitions. One study in Japan had gastroenterologists look at thousands of colonoscopy videos and asked them to rate the videos on a 0-10 scale to determine severity. The AI determined the components that led to most experts determining that a patient has severe disease, is completely normal, or is somewhere in between. Natural language processing (NLP) is a new segment of AI designed to analyze human text and automate clinical health records. How is NLP being used to support patients with ulcerative colitis? Comprehending the meaning of text requires more than knowing the definitions of words; it's also about understanding grammar, temporal reference, co-reference, negation, assertion — it's an amazing human skill. Today, AI has the same ability and it's starting to understand medical text. The natural language component also includes the ability for machines to generate natural conversational language. The large language models (LLMs) have exploded on the scene as chatbots that provide lifelike responses that are meaningful. Direct NLP applications that are being used in IBD and the UC space currently focus on helping with administrative tasks. Ambient documentation systems are now able to listen to a clinician-patient conversation, understand the meaning of the conversation, and then generate good- to very good-quality documentation. Office notes, telephone encounters, letters to insurers, even letters to patients and their families can be automated using LLM technology. We are in the early days of exploring what LLMs can and cannot do, but the possibilities are exciting. Some electronic medical record vendors and other companies are now providing tools that read patient portal messages and then generate a draft reply. This can address major issues for providers, such as of lack of time and burnout resulting from increased communication responsibilities. However, the reliability of these automated 'patient reply' systems has not been rigorously studied, and at the moment they are far from ready to operate without close supervision from healthcare experts. Soon, AI will interpret emails, charts, and phone call records to order medication refills and interpret disease status. What do you foresee as the next steps in the near future of AI in IBD? We should expect that all image analysis, whether endoscopy, MRI and CT, or pathology, will soon be primarily assessed by AI. Image analysis systems are maturing quickly, and these systems approach or exceed human reliability, reproducibility, and objectivity. The gastroenterologist role will no longer be assessing images but instead interpreting the clinical meaning of images. I don't really want to measure the bowel wall thickness of the entire colon; let the machine do it and I will tell you what it means for the patient. Increasingly, such AI analytics will be built into imaging equipment (eg, the colonoscopy processor). This will enable a new degree of standardization in endoscopy and UC treatment decisions. In addition, we should expect that administrative tasks increasingly will be replaced by AI. Documentation will soon be almost fully automated. LLMs will scan notes and patient records to determine appropriate billing and diagnosis codes. Scheduling will be managed by an interactive chatbot that can not only triage patients but also reach out to patients who are waiting for appointments when they become available. Over the next decade, we will experience major transitions in IBD care as AI ability increasingly comes to understand disease management. We are already seeing examples of LLMs and chatbots acing standard tests, such as the United States Medical Licensing Examination for general medicine. While a few years ago ChatGPT-3 and ChatGPT-4 failed the American College of Gastroenterology self-assessment test, it's only a matter of time before LLMs prove able to understand specialty IBD care questions. This will probably mean that diagnosis and even management plans will be provided by AI tools that have access to patient records, medical literature, guidelines, and some training from experts. Is there anything else you'd like to discuss related to AI and IBD? AI capabilities are truly astounding, but we need to be thinking about what we want them to do and the consequences of deploying these tools in care. How does the structure of healthcare delivery change in the post-AI world? Will IBD patients still need return visits with a clinician or can the AI chatbot and LLMs provide all monitoring? What is the role of the clinician in that scenario? If LLMs are managing routine, low-complexity, stable patients, human gastroenterologists could become overwhelmed with a schedule full of maximum-severity patients. I would speculate that over the next decade, medicine will move toward population-level care, with expert clinicians managing many more patients with the help of armies of AI agents to assist. Regulatory aspects of AI also remain unclear. The FDA and other regulators are thinking hard on balancing safety and innovation in regard to AI in medicine, but we are all learning as we go. What happens if two different FDA-approved AI decision-support systems disagree? What are the consequences of not using AI for decision support, particularly when there is a poor outcome? Who is paying for these AI tools to be developed and maintained? Which will be more valuable to patients: unlimited access to knowledgeable AI IBD care agents, or the seasoned human gastroenterologist? AI is an exciting revolution in specialty medical care like IBD. While we are still separating the hope, help, and hype of AI, rest assured that changes are coming. We should all be directly involved in this evolution of care to best ensure that the future is one designed to benefit both patients and clinicians in IBD.
