BackgroundColorectal cancer (CRC) is a very common tumor worldwide. Its mortality can be limited by early diagnosis through screening programs. These programs are based on fecal occult blood testing and colonoscopy. Our objective was to find a model based on the determination of blood biomarkers that was efficacious enough to become part of the early diagnosis of CRC. MethodsIn a total of 221 patients who underwent a colonoscopy, two types of markers were identified (I) classic: carcinoembryonic antigen (CEA), CA19.9, α-fetoprotein, CA125, CA72.4, and ferritin; and (II) experimental: neutrophil gelatinase-associated lipocalin (NGAL), estimated glomerular filtration rate (EGFR), 8-hydroxydeoxyguanosine (8OHdG), calprotectin, and cysteine-rich 61 (Cyr61). We divided the patients into four groups according to colonoscopy results: a control group (n=83) with normal colonoscopy, a polyp group (n=56), a CRC group (n=45), and an inflammatory disease group (n=37). We built an algorithm based on multivariate logistic regression analysis. ResultsA total of 51.6% were males, and the median age was 63 years. We designed an algorithm based on the combination of several markers that discriminated CRC patients from the rest of the patients with a performance of 94%, a sensitivity of 95.6%, and a specificity of 80.6%. Discriminating by sex also resulted in two powerful algorithms, although it performed better in males (97% vs. 91%). ConclusionsOur study has devised a predictive model with high efficacy based on the determination of several biomarkers. We think that it could be incorporated into the set of methods used in CRC screening.