Colorectal cancer screening uptake and adherence by modality at a large tertiary care center in the United States: a retrospective analysis.

OBJECTIVE: Real-world data is crucial to inform existing opportunistic colorectal cancer (CRC) prevention programs. This study aimed to assess CRC screening adherence and utilization of various screening modalities within a Primary Care network over a three-year period (2017-2019). METHODS: A retrospective review of individuals aged 50-75 years at average CRC risk, with at least one clinic visit in the previous 24 months. The primary outcome, CRC screening adherence (overall and by modality) was examined among the entire eligible population and newly adherent individuals each calendar year. The final sample included 107,366 patients and 218,878 records. RESULTS: Overall CRC screening adherence increased from 71% in 2017 to 78% in 2019. For "up-to-date" individuals, colonoscopy was the predominant modality (accounting for approximately 74%, versus 4% of adherence for non-invasive options). However, modality utilization trends changed over time in these individuals: mt-sDNA increased 10.2-fold, followed by FIT (1.6-fold) and colonoscopy (1.1-fold). Among newly adherent individuals, the proportion screened by colonoscopy and FOBT decreased over time (89% to 80% and 2.4% to 1.2%, respectively), while uptake of FIT and mt-sDNA increased (7.7% to 11.5% and 0.9% to 6.8%, respectively). Notably, FIT and mt-sDNA increases were most evident in age and race-ethnicity groups with the lowest screening rates. CONCLUSIONS: In an opportunistic CRC screening program, adherence increased but remained below the national 80% goal. While colonoscopy remained the most utilized modality, new colonoscopy uptake declined, compared with rising mt-sDNA and FIT utilization. Among minority populations, new uptake increased most with mt-sDNA and FIT.

Speedometer for withdrawal time monitoring during colonoscopy: a clinical implementation trial.

OBJECTIVES: Meticulous inspection of the mucosa during colonoscopy, represents a lengthier withdrawal time, but has been shown to increase adenoma detection rate (ADR). We investigated if artificial intelligence-aided speed monitoring can improve suboptimal withdrawal time. METHODS: We evaluated the implementation of a computer-aided speed monitoring device during colonoscopy at a large academic endoscopy center. After informed consent, patients ≥18 years undergoing colonoscopy between 5 March and 29 April 2021 were examined without the use of the speedometer, and with the speedometer between 29 April and 30 June 2021. All colonoscopies were recorded, and withdrawal time was assessed based on the recordings in a blinded fashion. We compared mean withdrawal time, percentage of withdrawal time ≥6 min, and ADR with and without the speedometer. RESULTS: One hundred sixty-six patients in each group were eligible for analyses. Mean withdrawal time was 9 min and 6.6 s (95% CI: 8 min and 34.8 s to 9 min and 39 s) without the use of the speedometer, and 9 min and 9 s (95% CI: 8 min and 45 s to 9 min and 33.6 s) with the speedometer; difference 2.3 s (95% CI: -42.3-37.7, p = 0.91). The ADRs were 45.2% (95% CI: 37.6-52.8) without the speedometer as compared to 45.8% (95% CI: 38.2-53.4) with the speedometer (p = 0.91). The proportion of colonoscopies with withdrawal time ≥6 min without the speedometer was 85.5% (95% CI: 80.2-90.9) versus 86.7% (95% CI: 81.6-91.9) with the speedometer (p = 0.75). CONCLUSIONS: Use of speed monitoring during withdrawal did not increase withdrawal time or ADR in colonoscopy. CLINICALTRIALS.GOV IDENTIFIER: NCT04710251.

Artificial intelligence in colonoscopy.

Colorectal cancer remains a leading cause of morbidity and mortality in the United States. Advances in artificial intelligence (AI), specifically computer aided detection and computer-aided diagnosis offer promising methods of increasing adenoma detection rates with the goal of removing more pre-cancerous polyps. Conversely, these methods also may allow for smaller non-cancerous lesions to be diagnosed in vivo and left in place, decreasing the risks that come with unnecessary polypectomies. This review will provide an overview of current advances in the use of AI in colonoscopy to aid in polyp detection and characterization as well as areas of developing research.

[Risk Prediction Using Routine Data: Development and Validation of Multivariable Models Predicting 30- and 90-day Mortality after Surgical Treatment of Colorectal Cancer]. / Risikoberechnung mit Routinedaten? Entwicklung und Validierung multivariabler Modelle zur Prädiktion der 30- und 90-Tage-Mortalität nach chirurgischer Behandlung kolorektaler Karzinome.

AIMS: Quality control, benchmarking, and pay for performance (P4P) require valid indicators and statistical models allowing adjustment for differences in risk profiles of the patient populations of the respective institutions. Using hospital remuneration data for measuring quality and modelling patient risks has been criticized by clinicians. Here we explore the potential of prediction models for 30- and 90-day mortality after colorectal cancer surgery based on routine data. STUDY DESIGN: Full census of a major statutory health insurer. SETTING: Surgical departments throughout the Federal Republic of Germany. PATIENTS: 4283 and 4124 insurants with major surgery for treatment of colorectal cancer during 2013 and 2014, respectively. PREDICTORS: Age, sex, primary and secondary diagnoses as well as tumor locations as recorded in the hospital remuneration data according to §301 SGB V. OUTCOMES: 30- and 90-day mortality. STATISTICAL ANALYSIS: Elixhauser comorbidities, Charlson conditions, and Charlson scores were generated from the ICD-10 diagnoses. Multivariable prediction models were developed using a penalized logistic regression approach (logistic ridge regression) in a derivation set (patients treated in 2013). Calibration and discrimination of the models were assessed in an internal validation sample (patients treated in 2014) using calibration curves, Brier scores, receiver operating characteristic curves (ROC curves) and the areas under the ROC curves (AUC). RESULTS: 30- and 90-day mortality rates in the learning-sample were 5.7 and 8.4%, respectively. The corresponding values in the validation sample were 5.9% and once more 8.4%. Models based on Elixhauser comorbidities exhibited the highest discriminatory power with AUC values of 0.804 (95% CI: 0.776 -0.832) and 0.805 (95% CI: 0.782-0.828) for 30- and 90-day mortality. The Brier scores for these models were 0.050 (95% CI: 0.044-0.056) and 0.067 (95% CI: 0.060-0.074) and similar to the models based on Charlson conditions. Regardless of the model, low predicted probabilities were well calibrated, while higher predicted values tended to be overestimates. CONCLUSION: The reasonable results regarding discrimination and calibration notwithstanding, models based on hospital remuneration data may not be helpful for P4P. Routine data do not offer information regarding a wide range of quality indicators more useful than mortality. As an alternative, models based on clinical registries may allow a wider, more valid perspective.

The Association between Serum 25-Hydroxyvitamin D and Cancer Risk: Results from the Prospective KORA F4 Study.

BACKGROUND: Many studies have examined the relationship between vitamin D and specific types of cancer with inconsistent results. Furthermore, to date, no observational studies have demonstrated a clear relationship between vitamin D and total cancer risk. METHODS: We analyzed data from a population-based prospective cohort study including 2,003 initially cancer-free participants from the KORA F4 study with baseline serum 25-hydroxyvitamin D (25(OH)D) measurements (surveyed between 2006 and 2008). We used Cox proportional hazard models to assess the association between 25(OH)D levels and incident cancer risk. RESULTS: Within a follow-up period of 7 years, 69 of the participants developed cancer. Overall, we observed no significant relationship between serum 25(OH)D levels and cancer risk. The hazard ratio (HR) per 1 ng/ml increase in 25 (OH)D for this relationship was 1.00 (95% confidence interval (CI) 0.97-1.04) adjusting for age, sex, body mass index, and season of blood draw. This was also true in subgroup analysis for prostate cancer (HR 0.95, 95% CI 0.88-1.03), breast cancer (HR 1.03, 95% CI 0.97-1.09), and colorectal cancer (HR 0.97, 95% CI 0.88-1.07). CONCLUSION: Our study found no protective effect of 25(OH)D against developing cancer. However, studies with more participants and additional measurements of 25(OH)D are still needed to accurately clarify the relationship between 25(OH)D and total cancer risk.

Cutting edge: Compartmentalization of Th1-like noninvariant CD1d-reactive T cells in hepatitis C virus-infected liver.

Murine intrahepatic lymphocytes (IHL) are dominated by invariant TCR alpha-chain expressing CD1d-reactive NKT cells, which can cause model hepatitis. Invariant NKT (CD56(+/-)CD161(+)) and recently identified noninvariant CD1d-reactive T cells rapidly produce large amounts of IL-4 and/or IFN-gamma and can regulate Th1/Th2 responses. Human liver contains large numbers of CD56(+) NKT cells but few invariant NKT. Compared with matched peripheral blood T cell lines, primary IHL lines from patients with chronic hepatitis C had high levels of CD161 and CD1d reactivity, but the invariant TCR was rare. CD1d-reactive IHL were strikingly Th1 biased. IHL also demonstrated CD1d-specific cytotoxic activity. Hepatocytes and other liver cells express CD1d. These results identify a novel population of human T cells that could contribute to destructive as well as protective immune responses in the liver. CD1d-reactive T cells may have distinct roles in different tissues.