Background: Colorectal cancer (CRC) is one of the most common and deadliest cancers worldwide, and incidence rates are rising. However, early detection and intervention can improve the survival rates and quality of life of affected patients. The Dxcover Liquid Biopsy Platform is a rapid multi-omic liquid biopsy that interrogates a blood sample with infrared radiation and produces a distinctive signature that represents the whole biomolecular profile of the sample. The liquid biopsy has been reported previously as a standalone test, but also has potential to be employed in combination with other information sources, such as biomarker data, and clinical risk factors. Methods: In this study, samples from 1377 patients were collected across sites in the USA (n=989) and UK (n=388). Blood was obtained from patients either prior to scheduled colonoscopy or before surgical resection and any anti-cancer therapies. Streck plasma samples were analyzed by the Dxcover Liquid Biopsy Platform. Carcinoembryonic Antigen (CEA) values were determined for all samples. Fecal hemoglobin levels from fecal immunochemical testing (FIT) were also obtained for the UK samples. Machine learning algorithms were developed to compare test performance and assess combinations. Results: Initially, machine learning models were developed for the spectral dataset alone. The area under the curve (AUC) was 0.95 and the model reported consistent detection rates across CRC stages. There was limited diagnostic utility reported for CEA alone (37% sensitivity with 80% specificity). There was no improvement to the spectral model with the inclusion of CEA. For the UK cohort with FIT results, the FIT only model (AUC=0.83) was enhanced by the addition of spectral data, with the combined model (spectra+FIT) reporting an AUC of 0.90. Conclusions: There is potential for combining this liquid biopsy with orthogonal tests, such as FIT testing or other blood-based biomarkers. A rapid liquid biopsy that is sensitive to early-stage CRC could substantially improve patient outcomes. Current screening programs have addressable limitations and the emergence of new alternative technologies is vital to support earlier CRC detection.