TY - JOUR
T1 - Optimizing Screening for Colorectal Cancer
T2 - An Algorithm Combining Fecal Immunochemical Test, Blood-Based Cancer-Associated Proteins and Demographics to Reduce Colonoscopy Burden
AU - Petersen, Mathias M
AU - Kleif, Jakob
AU - Jørgensen, Lars N
AU - Hendel, Jakob W
AU - Seidelin, Jakob B
AU - Madsen, Mogens R
AU - Vilandt, Jesper
AU - Brandsborg, Søren
AU - Rasmussen, Jørn S
AU - Andersen, Lars M
AU - Khalid, Ali
AU - Ferm, Linnea
AU - Gawel, Susan H
AU - Martens, Frans
AU - Andersen, Berit
AU - Rasmussen, Morten
AU - Davis, Gerard J
AU - Christensen, Ib J
AU - Therkildsen, Christina
N1 - Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.
PY - 2023/6
Y1 - 2023/6
N2 - BACKGROUND: 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.MATERIALS AND METHODS: 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.RESULTS: 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.CONCLUSION: 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.
AB - BACKGROUND: 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.MATERIALS AND METHODS: 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.RESULTS: 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.CONCLUSION: 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.
KW - Biomarkers, Tumor
KW - Colonoscopy
KW - Colorectal Neoplasms/diagnosis
KW - Demography
KW - Early Detection of Cancer/methods
KW - Feces/chemistry
KW - Hematologic Tests
KW - Hemoglobins/analysis
KW - Humans
KW - Mass Screening/methods
KW - Occult Blood
UR - http://www.scopus.com/inward/record.url?scp=85149675107&partnerID=8YFLogxK
U2 - 10.1016/j.clcc.2023.02.001
DO - 10.1016/j.clcc.2023.02.001
M3 - Journal article
C2 - 36878807
SN - 1533-0028
VL - 22
SP - 199
EP - 210
JO - Clinical Colorectal Cancer
JF - Clinical Colorectal Cancer
IS - 2
ER -