Background & Aims: Multi-target stool DNA (mt-sDNA) is an established stool-based colorectal cancer screening test, yet long-term performance is not well-described. We evaluated follow-up colonoscopy rates & quality, neoplasia yield, and repeat-testing adherence over 10 years with an integrated screening program. Methods: We assembled a retrospective cohort of mt-sDNA tests (September 2014–July 2025) within a multi-site health system. A validated large-language-model pipeline extracted colonoscopy, pathology, and quality endpoints from free-text reports. Detection outcomes (adenoma detection rate, advanced neoplasia, modified advanced adenoma, sessile serrated lesion (SSL), and negative exams) were calculated among high-quality exams; adenocarcinoma, bowel preparation adequacy, and cecal intubation rate (CIR) used all screening exams. We assessed colonoscopy completion ≤1 year after positive mt-sDNA, follow-up colonoscopy findings, findings by time-to-colonoscopy, and adherence to repeat mt-sDNA after negative result. Results: Among 148,624 tests in 110,410 individuals, positivity was 13.6%. Of 19,506 positives, 65.1% completed colonoscopy within 12 months (median 82 days). Colonoscopy after a positive mt-sDNA had high yield: advanced adenoma diagnosis was 30.7%; adenocarcinoma was 1.3%. Of patients who had colonoscopy within 3 years of a negative mt-sDNA test, 45.2% had adenoma/serrated lesion, 9.3% had advanced adenoma and 0.5% had colon cancer. Adenoma detection rate after positive mt-sDNA (>50%) exceeded specialty society quality benchmarks and increased over time; Longer intervals (>6 months) to colonoscopy after a positive test were associated with higher advanced adenoma (trend P=0.001).After an initial negative mt-sDNA, only 35.3% were screened again by mt-sDNA testing within 3 years. Conclusions: Over a decade,mt-sDNA screening achieved high colonoscopy qualitybut revealed critical gaps in the care cascade. One-third of positive tests lacked timely follow-up and nearly two-thirds of negative tests were not repeated on schedule, suggesting opportunities for system-level interventions.
Most of moderate to severe ulcerative colitis patients in academic clinical practice still do not qualify for randomized controlled trials
Abstract Background While biologic and small molecule therapies have expanded treatment options for moderate to severe ulcerative colitis (UC), prior research revealed that only 26% of patients in routine practice would have qualified for pivotal randomized controlled trials (RCTs) due to stringent eligibility criteria. This study aimed to evaluate contemporary clinical trial eligibility for UC patients in a tertiary care setting based on more recently approved therapies. Methods We performed a retrospective cohort study of adult patients with moderate to severe UC (total Mayo score ≥6) seen between January 2022 and February 2023. Inclusion and exclusion criteria from seven phase III RCTs conducted between 2012 and 2022 (eg, VARSITY, UNIFI, OCTAVE, LUCENT) were applied to determine patient eligibility and identify reasons for ineligibility. Results Of 150 patients (mean age 44.9 years; 55.7% male), only 42.7% were eligible for at least one RCT. The most common exclusion factor was current or prior medication use, followed by anemia, dysplasia, and disease extent. Trial eligibility did not significantly differ by age, gender, or disease duration. Conclusions Despite modest improvements since 2012, over half of real-world UC patients remain ineligible for current RCTs. Expanding inclusion criteria, especially regarding prior medication exposure, and adopting more inclusive trial designs may enhance external validity. Addressing disparities in trial access and participation remains essential to ensuring equitable representation and improving clinical applicability of RCT findings.
Accurate and Scalable Classification of Colonoscopy Neoplasia Using Machine Learning and Natural Language Processing
INTRODUCTION: Colorectal cancer remains a leading cause of cancer associated death in the United States and colonoscopy the primary screening strategy for prevention. Rates of adenomatous and serrated neoplasia detection are inversely associated with postcolonoscopy colorectal cancer. This crucial quality metric depends on accurate ascertainment of colorectal neoplasia findings from both endoscopy and histopathology records. We aimed to assess the feasibility of a random forest machine learning model to rapidly and accurately categorize colorectal neoplasia from electronic health record data. METHODS: A retrospective cohort study compared neoplasia detection rates among individuals undergoing colonoscopy at a large academic institution to develop a rule-based algorithm to categorize colorectal neoplasia from endoscopy reports and pathology systematized nomenclature of medicine – clinical terms. This cohort provided a large training set to develop a natural language processing system using a random forest approach to automatically classify unstructured pathology findings into adenoma, serrated, or advanced neoplasms. This system was manually validated through an independent holdout set. RESULTS: The training set comprised 35,953 unstructured pathology reports with matched systematized nomenclature of medicine – clinical terms from 95,188 unstructured colonoscopy reports. The final model was assessed on an independent holdout set of 337 manually annotated procedures obtaining an area under the receiver operating characteristic curve of 0.997 (confidence interval [CI] 0.994–1), 0.99 (CI 0.98–1), and 0.99 (CI 0.98–0.99) for prediction of adenoma, serrated, and advanced lesions, respectively. DISCUSSION: The random forest-based hybrid natural language processing system for classification of colonoscopy results was both accurate and explainable. NLP combined with effective machine learning algorithms can provide a scalable strategy for colonoscopy quality monitoring.
Detection of Postcolonoscopy Colorectal Neoplasia by Multi-target Stool DNA
INTRODUCTION: Significant variability between colonoscopy operators contributes to postcolonoscopy colorectal cancers (CRCs). We aimed to estimate postcolonoscopy colorectal neoplasia (CRN) detection by multi-target stool DNA (mt-sDNA), which has not previously been studied for this purpose. METHODS: In a retrospective cohort of patients with +mt-sDNA and completed follow-up colonoscopy, positive predictive value (PPV) for endpoints of any CRN, advanced adenoma, right-sided neoplasia, sessile serrated polyps (SSP), and CRC were stratified by the time since previous colonoscopy (0–9, 10, and ≥11 years). mt-sDNA PPV at ≤9 years from previous average-risk screening colonoscopy was used to estimate CRN missed at previous screening colonoscopy. RESULTS: Among the 850 studied patients with +mt-sDNA after a previous negative screening colonoscopy, any CRN was found in 535 (PPV 63%). Among 107 average-risk patients having +mt-sDNA ≤9 years after last negative colonoscopy, any CRN was found in 67 (PPV 63%), advanced neoplasia in 16 (PPV 15%), right-sided CRN in 48 (PPV 46%), and SSP in 20 (PPV 19%). These rates were similar to those in 47 additional average risk persons with previous incomplete colonoscopy and in an additional 68 persons at increased CRC risk. One CRC (stage I) was found in an average risk patient who was mt-sDNA positive 6 years after negative screening colonoscopy. DISCUSSION: The high PPV of mt-sDNA 0–9 years after a negative screening colonoscopy suggests that lesions were likely missed on previous examination or may have arisen de novo . mt-sDNA as an interval test after negative screening colonoscopy warrants further study.
Establishing key research questions for the implementation of artificial intelligence in colonoscopy: a modified Delphi method
Abstract Background Artificial intelligence (AI) research in colonoscopy is progressing rapidly but widespread clinical implementation is not yet a reality. We aimed to identify the top implementation research priorities. Methods An established modified Delphi approach for research priority setting was used. Fifteen international experts, including endoscopists and translational computer scientists/engineers, from nine countries participated in an online survey over 9 months. Questions related to AI implementation in colonoscopy were generated as a long-list in the first round, and then scored in two subsequent rounds to identify the top 10 research questions. Results The top 10 ranked questions were categorized into five themes. Theme 1: clinical trial design/end points (4 questions), related to optimum trial designs for polyp detection and characterization, determining the optimal end points for evaluation of AI, and demonstrating impact on interval cancer rates. Theme 2: technological developments (3 questions), including improving detection of more challenging and advanced lesions, reduction of false-positive rates, and minimizing latency. Theme 3: clinical adoption/integration (1 question), concerning the effective combination of detection and characterization into one workflow. Theme 4: data access/annotation (1 question), concerning more efficient or automated data annotation methods to reduce the burden on human experts. Theme 5: regulatory approval (1 question), related to making regulatory approval processes more efficient. Conclusions This is the first reported international research priority setting exercise for AI in colonoscopy. The study findings should be used as a framework to guide future research with key stakeholders to accelerate the clinical implementation of AI in endoscopy.
Breast Cancer Metastasis Presenting as Colonic Polyps
ABSTRACT Breast cancer is the most common malignancy among women and is the second leading cause of cancer-related death among women in the United States. Rarely, breast cancer can metastasize to the gastrointestinal tract. We present a case of metastatic breast cancer diagnosed after finding metastatic lesions appearing as polyps during a colonoscopy.
Multitarget Stool DNA Screening in Clinical Practice: High Positive Predictive Value for Colorectal Neoplasia Regardless of Exposure to Previous Colonoscopy
OBJECTIVES: Multitarget stool DNA (MT-sDNA) testing has grown as a noninvasive screening modality for colorectal cancer (CRC), but real-world clinical data are limited in the post-FDA approval setting. The effect of previous colonoscopy on MT-sDNA performance is not known. We aimed to evaluate findings of colorectal neoplasia (CRN) at diagnostic colonoscopy in patients with positive MT-sDNA testing, stratified by patient exposure to previous colonoscopy. METHODS: We identified consecutive patients completing MT-sDNA testing over a 39-month period and reviewed the records of those with positive tests for neoplastic findings at diagnostic colonoscopy. MT-sDNA test positivity rate, adherence to diagnostic colonoscopy, and the positive predictive value (PPV) of MT-sDNA for any CRN and neoplastic subtypes were calculated. RESULTS: Of 16,469 MT-sDNA tests completed, testing returned positive in 2,326 (14.1%) patients. After exclusion of patients at increased risk for CRC, 1,801 patients remained, 1,558 (87%) of whom underwent diagnostic colonoscopy; 918 of 1,558 (59%) of these patients had undergone previous colonoscopy, whereas 640 (41%) had not. Any CRN was found in 1,046 of 1,558 patients (PPV = 67%). More neoplastic lesions were found in patients without previous colonoscopy (73%); however, the rates remained high among those who had undergone previous colonoscopy (63%, P < 0.0001). The large majority (79%) of patients had right-sided neoplasia. DISCUSSION: MT-sDNA has a high PPV for any CRN regardless of exposure to previous colonoscopy. Right-sided CRN was found at colonoscopy in most patients with positive MT-sDNA testing, representing a potential advantage over other currently available screening modalities for CRC.
Impact of feedback on adenoma detection rates: Outcomes of quality improvement program
AbstractBackground and AimFeedback has been shown to improve performance in colonoscopy including adenoma detection rate (ADR). The frequency at which feedback should be given is unknown. As part of a quality improvement program, we sought to measure the outcome of providing quarterly and monthly feedback on colonoscopy quality measures.MethodsAll screening colonoscopies performed at endoscopy unit at Mayo Clinic Arizona by gastroenterologists between October 2010 and December 2012 were reviewed. Quality indicators, including ADR, were extracted for each individual endoscopist, and feedback was provided. The study period was divided into four distinct groups: pre‐intervention that served as baseline, quarterly feedback, monthly feedback, and post‐intervention. Based on ADR, endoscopists were grouped into “low detectors” (≤ 25%), “average detectors” (26–35%), and “high detectors” (> 35%).ResultsA total of 3420 screening colonoscopies were performed during the study period (555 patients during pre‐intervention, 1209 patients during quarterly feedback, 599 during monthly feedback, and 1057 during the post‐intervention period) by 16 gastroenterologists. The overall ADR for the group improved from 30.5% to 37.7% (P = 0.003). Compared with the pre‐interventional period, all quality indicators measured significantly improved during the monthly feedback and post‐intervention periods but not in the quarterly feedback period.ConclusionsIn our quality improvement program, monthly feedback significantly improved colonoscopy quality measures, including ADR, while quarterly feedback did not. The impact of the intervention was most prominent in the “low detectors” group. Results were durable up to 6 months following the intervention.
Postcolonoscopy Followup Recommendations: Comparison with and without Use of Polyp Pathology
Background. Appropriate recommendations for a followup exam after an index colonoscopy are an important quality indicator. Lack of knowledge of polyp pathology at the time of colonoscopy may be one reason that followup recommendations are not made. Aim. To describe and compare the accuracy of followup recommendations made at colonoscopy based on the size and number of polyps with recommendations made at a later date based on actual polyp pathology. Methods. All patients who underwent screening and surveillance colonoscopy from March, 2012, to August, 2012, were included. Surveillance recommendations from the endoscopy reports were graded as “accurate” or “not accurate” based on the postpolypectomy surveillance guidelines established by US Multisociety Task Force on Colon Cancer. Polyp pathology was then used to regrade the surveillance recommendations. Results. Followup recommendations were accurate in 759/884 (86%) of the study colonoscopies, based upon size and number of polyps with the assumption that all polyps were adenomatous. After incorporating actual polyp pathology, 717/884 (81%) colonoscopies had accurate recommendations. Conclusion. In our practice, the knowledge of actual polyp pathology does not change the surveillance recommendations made at the time of colonoscopy in the majority of patients.