Opinion statement: Colorectal cancer (CRC) imposes significant morbidity and mortality, yet it is also largely preventable with evidence-based screening strategies. In May 2021, the US Preventive Services Task Force updated guidance, recommending screening begin at age 45 for average-risk individuals to reduce CRC incidence and mortality in the United States (US). The Task Force recommends screening with one of several screening strategies: high-sensitivity guaiac fecal occult blood test (HSgFOBT), fecal immunochemical test (FIT), multi-target stool DNA (mt-sDNA) test, computed tomographic (CT) colonography (virtual colonoscopy), flexible sigmoidoscopy, flexible sigmoidoscopy with FIT, or traditional colonoscopy. In addition to these recommended options, there are several emerging and novel CRC screening modalities that are not yet approved for first-line screening in average-risk individuals. These include blood-based screening or “liquid biopsy,” colon capsule endoscopy, urinary metabolomics, and stool-based microbiome testing for the detection of colorectal polyps and/or CRC. In order to maximize CRC screening uptake in the US, patients and providers should engage in informed decision-making about the benefits and limitations of recommended screening options to determine the most appropriate screening test. Factors to consider include the invasiveness of the test, test performance, screening interval, accessibility, and cost. In addition, health systems should have a programmatic approach to CRC screening, which may include evidence-based strategies such as patient education, provider education, mailed screening outreach, and/or patient navigation, to maximize screening participation.

Artificial intelligence (AI) and machine learning (ML) systems are increasingly used in medicine to improve clinical decision-making and healthcare delivery. In gastroenterology and hepatology, studies have explored a myriad of opportunities for AI/ML applications which are already making the transition to bedside. Despite these advances, there is a risk that biases and health inequities can be introduced or exacerbated by these technologies. If unrecognised, these technologies could generate or worsen systematic racial, ethnic and sex disparities when deployed on a large scale. There are several mechanisms through which AI/ML could contribute to health inequities in gastroenterology and hepatology, including diagnosis of oesophageal cancer, management of inflammatory bowel disease (IBD), liver transplantation, colorectal cancer screening and many others. This review adapts a framework for ethical AI/ML development and application to gastroenterology and hepatology such that clinical practice is advanced while minimising bias and optimising health equity.

Background: Liver cancer is one of the most rapidly increasing cancers in the United States, and hepatocellular carcinoma (HCC) is its most common form. Disease burden and risk factors differ by sex and race/ethnicity, but a comprehensive analysis of disparities by socioeconomic status (SES) is lacking. We examined the relative impact of race/ethnicity, sex, and SES on HCC incidence, stage, and survival. Methods: We used Surveillance, Epidemiology, and End Results (SEER) 18 data to identify histologically confirmed cases of HCC diagnosed between January 1, 2000 and December 31, 2015. We calculated age-adjusted HCC incidence, stage at diagnosis (local, regional, distant, unstaged), and 5-year survival, by race/ethnicity, SES and sex, using SEER*Stat version 8.3.5. Results: We identified 45,789 cases of HCC. Incidence was highest among low-SES Asian/Pacific Islanders (API; 12.1) and lowest in high-SES Whites (3.2). Incidence was significantly higher among those with low-SES compared with high-SES for each racial/ethnic group (P < 0.001), except American Indian/Alaska Natives (AI/AN). High-SES API had the highest percentage of HCC diagnosed at the local stage. Of all race/ethnicities, Blacks had the highest proportion of distant stage disease in the low- and high-SES groups. Survival was greater in all high-SES racial/ethnic groups compared with low-SES (P < 0.001), except among AI/ANs. Black, low-SES males had the lowest 5-year survival. Conclusions: With few exceptions, HCC incidence, distant stage at diagnosis, and poor survival were highest among the low-SES groups for all race/ethnicities in this national sample. Impact: HCC prevention and control efforts should target low SES populations, in addition to specific racial/ethnic groups.

The optimal time interval for diagnostic colonoscopy completion after an abnormal stool-based colorectal cancer (CRC) screening test is uncertain. We examined the association between time to colonoscopy and CRC outcomes among individuals who underwent diagnostic colonoscopy after abnormal stool-based screening. We performed a retrospective cohort study of veterans age 50 to 75 years with an abnormal fecal occult blood test (FOBT) or fecal immunochemical test (FIT) between 1999 and 2010. We used multivariable Cox proportional hazards to generate CRC-specific incidence and mortality hazard ratios (HRs) and 95% confidence intervals (CI) for 3-month colonoscopy intervals, with 1 to 3 months as the reference group. Association of time to colonoscopy with late-stage CRC diagnosis was also examined. Our cohort included 204,733 patients. Mean age was 61 years (SD 6.9). Compared with patients who received a colonoscopy at 1 to 3 months, there was an increased CRC risk for patients who received a colonoscopy at 13 to 15 months (HR 1.13; 95% CI 1.00-1.27), 16 to 18 months (HR 1.25; 95% CI 1.10-1.43), 19 to 21 months (HR 1.28; 95% CI: 1.11-1.48), and 22 to 24 months (HR 1.26; 95% CI 1.07-1.47). Compared with patients who received a colonoscopy at 1 to 3 months, mortality risk was higher in groups who received a colonoscopy at 19 to 21 months (HR 1.52; 95% CI 1.51-1.99) and 22 to 24 months (HR 1.39; 95% CI 1.03-1.88). Odds for late-stage CRC increased at 16 months. Increased time to colonoscopy is associated with higher risk of CRC incidence, death, and late-stage CRC after abnormal FIT/FOBT. Interventions to improve CRC outcomes should emphasize diagnostic follow-up within 1 year of an abnormal FIT/FOBT result.