Colorectal cancer (CRC) is the third most commonly diagnosed cancer in the world. The incidence and mortality show wide geographical variations. Screening is recommended to reduce both incidence and mortality. However, there are significant differences among studies in implementation strategies and detection. This review aimed to present the results and strategies of different screening programs worldwide. We reviewed the literature on national and international screening programs published in PubMed, on web pages, and in clinical guidelines. CRC Screening programs are currently underway in most European countries, Canada, specific regions in North and South America, Asia, and Oceania. The most extensive screening strategies were based on fecal occult blood testing, and more recently, the fecal immunochemical test (FIT). Participation in screening has varied greatly among different programs. The Netherlands showed the highest participation rate (68.2%) and some areas of Canada showed the lowest (16%). Participation rates were highest among women and in programs that used the FIT test. Men exhibited the greatest number of positive results. The FIT test has been the most widely used screening program worldwide. The advent of this test has increased participation rates and the detection of positive results. Core tip: Colorectal cancer is the third most commonly diagnosed cancer worldwide. The incidence and mortality show wide geographical variations across the world. Screening is recommended to reduce both, however, there are significant differences among studies in implementation strategies and detection. This review aimed to present the results and strategies of different screening programs worldwide.

IIM is the PL with highest risk to progress to GC. Sub-typing of IM is a valid procedure for the identification of high risk patients that require more intensive surveillance.

No abstract

BackgroundRisk prediction models for colorectal cancer (CRC) detection in symptomatic patients based on available biomarkers may improve CRC diagnosis. Our aim was to develop, compare with the NICE referral criteria and externally validate a CRC prediction model, COLONPREDICT, based on clinical and laboratory variables.MethodsThis prospective cross-sectional study included consecutive patients with gastrointestinal symptoms referred for colonoscopy between March 2012 and September 2013 in a derivation cohort and between March 2014 and March 2015 in a validation cohort. In the derivation cohort, we assessed symptoms and the NICE referral criteria, and determined levels of faecal haemoglobin and calprotectin, blood haemoglobin, and serum carcinoembryonic antigen before performing an anorectal examination and a colonoscopy. A multivariate logistic regression analysis was used to develop the model with diagnostic accuracy with CRC detection as the main outcome.ResultsWe included 1572 patients in the derivation cohort and 1481 in the validation cohorts, with a 13.6 % and 9.1 % CRC prevalence respectively. The final prediction model included 11 variables: age (years) (odds ratio [OR] 1.04, 95 % confidence interval [CI] 1.02–1.06), male gender (OR 2.2, 95 % CI 1.5–3.4), faecal haemoglobin ≥20 μg/g (OR 17.0, 95 % CI 10.0–28.6), blood haemoglobin <10 g/dL (OR 4.8, 95 % CI 2.2–10.3), blood haemoglobin 10–12 g/dL (OR 1.8, 95 % CI 1.1–3.0), carcinoembryonic antigen ≥3 ng/mL (OR 4.5, 95 % CI 3.0–6.8), acetylsalicylic acid treatment (OR 0.4, 95 % CI 0.2–0.7), previous colonoscopy (OR 0.1, 95 % CI 0.06–0.2), rectal mass (OR 14.8, 95 % CI 5.3–41.0), benign anorectal lesion (OR 0.3, 95 % CI 0.2–0.4), rectal bleeding (OR 2.2, 95 % CI 1.4–3.4) and change in bowel habit (OR 1.7, 95 % CI 1.1–2.5). The area under the curve (AUC) was 0.92 (95 % CI 0.91–0.94), higher than the NICE referral criteria (AUC 0.59, 95 % CI 0.55–0.63; p < 0.001). On the basis of the thresholds with 90 % (5.6) and 99 % (3.5) sensitivity, we divided the derivation cohort into three risk groups for CRC detection: high (30.9 % of the cohort, positive predictive value [PPV] 40.7 %, 95 % CI 36.7–45.9 %), intermediate (29.5 %, PPV 4.4 %, 95 % CI 2.8–6.8 %) and low (39.5 %, PPV 0.2 %, 95 % CI 0.0–1.1 %). The discriminatory ability was equivalent in the validation cohort (AUC 0.92, 95 % CI 0.90–0.94; p = 0.7).ConclusionsCOLONPREDICT is a highly accurate prediction model for CRC detection.Electronic supplementary materialThe online version of this article (doi:10.1186/s12916-016-0668-5) contains supplementary material, which is available to authorized users.