OBJECTIVES: Most screening options for colorectal cancer (CRC) are invasive and patient compliance in population wide screening programs is low. Recently, potential candidates for blood-based biomarker tests for early cancer detection have been described. Here we perform an extensive cost-effectiveness analysis of integrated diagnostic screening workflows to determine the anticipated impact of incorporating two candidate in vitro biomarkers, CCSA-3 immunoassay and SEPT9 epigenetics testing, on both patient mortality and medical costs. METHODS: Markov Cycle Tree models were constructed to simulate disease progression and screening for 4 million people, representative of the U.S. population, aging from 50 to 80. Eight workflows were constructed from combinations of Optical Colonoscopy (OC), CT Colonography (CTC), Fecal Occult Blood Test (FOBT), Immunoassay (CCSA-3), and Epigenetics (SEPT9). Kernel density estimation was performed on raw biomarker data to generate disease-state probability distributions of biomarker levels for sensitivity and specificity calculations. Finally, we perform sensitivity analysis on the sensitivity and specificity of a generic in vitro diagnostic test. RESULTS: CRC screening workflows that include initial screening with inexpensive in vitro diagnostic tests given every 3 years outperform others in both cost and effectiveness. Incremental costs compared with No Screening are as follows: OC $1.4B increase, SEPT9 $582M increase, CCSA-3 $2.8B decrease. Life-years saved: OC 78,535, SEPT9 185,839, CCSA-3 216,434. Despite having lower sensitivity and specificity, the low-cost and minimally-invasive nature of these tests allow more frequent screening, resulting in better detection of early stage disease than with OC alone. CONCLUSIONS: Though currently there are no blood-based biomarkers approved for early colorectal cancer screening, we can assess the expected impact of these tests once developed on colorectal cancer in the U.S. population. A complete sensitivity analysis of the sensitivity and specificity of a hypothetical biomarker provides a map of cost-effectiveness within which any test developed will fall.