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Development of an algorithm combining blood-based biomarkers, fecal immunochemical test, and age for population-based colorectal cancer screening - 04/12/24

Doi : 10.1016/j.gie.2024.06.015 
Mathias M. Petersen, PhD 1, 2, Jakob Kleif, PhD 1, 2, 3, Jason Liggett, PhD 4, Morten Rasmussen, PhD 2, 5, Lars N. Jørgensen, PhD 2, 5, Jesper Vilandt, MD 3, Jakob B. Seidelin, PhD 6, Carla M.T. Beertsen, MSc 7, Annemieke C. Heijboer, PhD 7, Claudia Jaensch, PhD 8, 9, Peter Bondeven, PhD 10, Kåre A. Gotschalck, PhD 11, Uffe S. Løve, PhD 12, Susan H. Gawel, PhD 13, Berit Andersen, PhD 14, 15, Ib J. Christensen, PhD 1, Eric Mayer, MSc 4, Gerard J. Davis, PhD 13, Christina Therkildsen, PhD 1,
1 Gastro Unit, Copenhagen University Hospital–Amager and Hvidovre, Hvidovre, Denmark 
2 Institute for Clinical Medicine, University of Copenhagen, Copenhagen, Denmark 
3 Department of Surgery, Regional Hospital Nordsjælland, Hillerød, Denmark 
4 New Day Diagnostics, Knoxville, Tennessee, USA 
5 Digestive Disease Center, Copenhagen University Hospital–Rigshospitalet and Bispebjerg, Bispebjerg, Denmark 
6 Gastro Unit, Section for Gastroenterology, Copenhagen University Hospital–Herlev and Gentofte, Herlev, Denmark 
7 Endocrine Laboratory, Department of Clinical Chemistry, Amsterdam University Medical Center, Academic Medical Center, and Vrije University Medical Center, Amsterdam, the Netherlands 
8 Department of Surgery, Regional Hospital Gødstrup, Herning, Denmark 
9 NIDO, Center for Research and Education, Regional Hospital Gødstrup, Herning, Denmark 
10 Department of Surgery, Regional Hospital Randers, Randers, Denmark 
11 Department of Surgery, Regional Hospital Horsens, Horsens, Denmark 
12 Department of Surgery, Regional Hospital Viborg, Viborg, Denmark 
13 Abbott Laboratories, Abbott Diagnostics Division, Abbott Park, Illinois, USA 
14 Department of Public Health Programmes and University Research Clinic for Cancer Screening, Regional Hospital Randers, Randers, Denmark 
15 Department of Clinical Medicine, Aarhus University, Aarhus, Denmark 

Reprint requests: Christina Therkildsen, PhD, Gastro Unit Department 360, Hvidovre Hospital, Kettegårds Allé 30, 2650 Hvidovre, Denmark.Gastro Unit Department 360Hvidovre HospitalKettegårds Allé 30Hvidovre2650Denmark

Abstract

Background and Aims

Implementation of screening modalities has reduced the burden of colorectal cancer (CRC), but high false positive rates pose a major problem for colonoscopy capacity. We aimed to create a tailored screening algorithm that expands the fecal immunochemical test (FIT) with a blood specimen and current age to improve selection of individuals for diagnostic colonoscopy.

Methods

In this prospective multicenter study, 8 blood-based biomarkers (carcinoembryonic antigen, ferritin, high-sensitivity C-reactive protein, human epididymis protein 4, Cyfra21-1, hepsin, interleukin 8, and osteoprotegerin) were investigated in 1977 FIT-positive individuals from the Danish national CRC screening program undergoing follow-up colonoscopy. Specimens were analyzed on Architect i2000, Architect c8000 (both from Abbott, Chicago, Ill, USA), or Luminex xMAP machines (MilliporeSigma, St. Louis, Mo, USA). FIT analyses and blood-based biomarker data were combined with clinical data (ie, age and colonoscopy findings) in a cross-validated logistic regression model (algorithm) benchmarked against a model solely using the FIT result (FIT model) applying different cutoffs for FIT positivity.

Results

The cohort included individuals with CRC (n = 240), adenomas (n = 938), or no neoplastic lesions (n = 799). The cross-validated algorithm combining the 8 biomarkers, quantitative FIT result, and age performed superior to the FIT model in discriminating CRC versus non-CRC individuals (area under the receiver operating characteristic curve, 0.77 vs 0.67, respectively; P < .001). When discriminating individuals with either CRC or high- or medium-risk adenomas versus low-risk adenomas or clean colorectum, the areas under the receiver operating characteristic curve were 0.68 versus 0.64 for the algorithm and FIT model, respectively.

Conclusions

The algorithm presented here can improve patient allocation to colonoscopy, reducing colonoscopy burden without compromising cancer and adenoma detection rates or vice versa.

Il testo completo di questo articolo è disponibile in PDF.

Graphical abstract




Il testo completo di questo articolo è disponibile in PDF.

Abbreviations : AUC, CRC, EDTA, FIT, Hb, HRA, LRA, MRA


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© 2024  American Society for Gastrointestinal Endoscopy. Tutti i diritti riservati.
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