Optimizing Screening for Colorectal Cancer: An Algorithm Combining Fecal Immunochemical Test, Blood-Based Cancer-Associated Proteins and Demographics to Reduce Colonoscopy Burden

• Published in: Clinical colorectal cancer 2023-06, Vol.22 (2), p.199-210
• Main Authors: Petersen, Mathias M., Kleif, Jakob, Jørgensen, Lars N., Hendel, Jakob W., Seidelin, Jakob B., Madsen, Mogens R., Vilandt, Jesper, Brandsborg, Søren, Rasmussen, Jørn S., Andersen, Lars M., Khalid, Ali, Ferm, Linnea, Gawel, Susan H., Martens, Frans, Andersen, Berit, Rasmussen, Morten, Davis, Gerard J., Christensen, Ib J., Therkildsen, Christina
• Format: Article
• Language: English
• Subjects: Biomarkers; Biomarkers, Tumor; Colonoscopy; Colorectal neoplasia; Colorectal Neoplasms - diagnosis; Demography; Early detection; Early Detection of Cancer - methods; Feces - chemistry; Hematologic Tests; Hemoglobins - analysis; Humans; Logistic regression modeling; Mass Screening - methods; Minimal invasive liquid biopsy; Occult Blood
• ISSN: 1533-0028; 1938-0674
• DOI: 10.1016/j.clcc.2023.02.001

•Colorectal cancer screening using Fecal Immunochemical Test (FIT) reduces both morbidity and mortality.•However, FIT screening is linked to high demand of colonoscopy capacity mainly due to a high false positive rate.•In here, we tested whether our proposed algorithm using FIT, blood-based biomarker analysis and demographics of the subject could improve screening.•The algorithm reduced the amount of needed colonoscopies by 4%-11%. Fecal Immunochemical Test (FIT) is widely used in population-based screening for colorectal cancer (CRC). This had led to major challenges regarding colonoscopy capacity. Methods to maintain high sensitivity without compromising the colonoscopy capacity are needed. This study investigates an algorithm that combines FIT result, blood-based biomarkers associated with CRC, and individual demographics, to triage subjects sent for colonoscopy among a FIT positive (FIT+) screening population and thereby reduce the colonoscopy burden. From the Danish National Colorectal Cancer Screening Program, 4048 FIT+ (≥100 ng/mL Hemoglobin) subjects were included and analyzed for a panel of 9 cancer-associated biomarkers using the ARCHITECT i2000. Two algorithms were developed: 1) a predefined algorithm based on clinically available biomarkers: FIT, age, CEA, hsCRP and Ferritin; and 2) an exploratory algorithm adding additional biomarkers: TIMP-1, Pepsinogen-2, HE4, CyFra21-1, Galectin-3, B2M and sex to the predefined algorithm. The diagnostic performances for discriminating subjects with or without CRC in the 2 models were benchmarked against the FIT alone using logistic regression modeling. The discrimination of CRC showed an area under the curve (AUC) of 73.7 (70.5-76.9) for the predefined model, 75.3 (72.1-78.4) for the exploratory model, and 68.9 (65.5-72.2) for FIT alone. Both models performed significantly better (P < .001) than the FIT model. The models were benchmarked vs. FIT at cutoffs of 100, 200, 300, 400, and 500 ng/mL Hemoglobin using corresponding numbers of true positives and false positives. All performance metrics were improved at all cutoffs. A screening algorithm including a combination of FIT result, blood-based biomarkers and demographics outperforms FIT in discriminating subjects with or without CRC in a screening population with FIT results above 100 ng/mL Hemoglobin. This study aimed to investigate if a 2-step algorithm using fecal immunochemical test, blood-based biomarkers and demographics of a subject could enhance scr