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Optimizing Screening for Colorectal Cancer: An Algorithm Combining Fecal Immunochemical Test, Blood-Based Cancer-Associated Proteins and Demographics to Reduce Colonoscopy Burden.
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.
Afiliação
  • Petersen MM; Gastro Unit, Hvidovre Hospital, Hvidovre, Denmark; Institute for Clinical Medicine, University of Copenhagen, Copenhagen, Denmark. Electronic address: mathias.mertz.petersen@regionh.dk.
  • Kleif J; Gastro Unit, Hvidovre Hospital, Hvidovre, Denmark; Institute for Clinical Medicine, University of Copenhagen, Copenhagen, Denmark; Department of Surgery, Nordsjællands Hospital, Hillerød, Denmark.
  • Jørgensen LN; Institute for Clinical Medicine, University of Copenhagen, Copenhagen, Denmark; Digestive Disease Center, Bispebjerg Hospital, Copenhagen, Denmark.
  • Hendel JW; Gastro Unit, Section for Gastroenterology, Herlev Hospital, Herlev, Denmark.
  • Seidelin JB; Gastro Unit, Section for Gastroenterology, Herlev Hospital, Herlev, Denmark.
  • Madsen MR; Department of Surgery, Herning Hospital, Herning, Denmark.
  • Vilandt J; Department of Surgery, Nordsjællands Hospital, Hillerød, Denmark.
  • Brandsborg S; Department of Surgery, Horsens Hospital, Horsens, Denmark.
  • Rasmussen JS; Department of Surgery, Horsens Hospital, Horsens, Denmark.
  • Andersen LM; Department of Public Health Programmes and University Research Clinic for Cancer Screening, Randers Regional Hospital, Randers, Denmark.
  • Khalid A; Department of Surgery, Viborg Hospital, Viborg, Denmark.
  • Ferm L; Gastro Unit, Hvidovre Hospital, Hvidovre, Denmark.
  • Gawel SH; Abbott Laboratories, Abbott Diagnostics Division, Abbott Park, IL.
  • Martens F; Endocrine Laboratory, Department of Clinical Chemistry, Amsterdam UMC, AMC & VUMC, Amsterdam, The Netherlands.
  • Andersen B; Department of Public Health Programmes and University Research Clinic for Cancer Screening, Randers Regional Hospital, Randers, Denmark; Department of Clinical Medicine, Aarhus University, Aarhus, Denmark.
  • Rasmussen M; Institute for Clinical Medicine, University of Copenhagen, Copenhagen, Denmark.
  • Davis GJ; Abbott Laboratories, Abbott Diagnostics Division, Abbott Park, IL.
  • Christensen IJ; Gastro Unit, Hvidovre Hospital, Hvidovre, Denmark.
  • Therkildsen C; Gastro Unit, Hvidovre Hospital, Hvidovre, Denmark.
Clin Colorectal Cancer ; 22(2): 199-210, 2023 06.
Article em En | MEDLINE | ID: mdl-36878807
ABSTRACT

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.
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Texto completo: 1 Coleções: 01-internacional Contexto em Saúde: 1_ASSA2030 / 2_ODS3 Base de dados: MEDLINE Assunto principal: Neoplasias Colorretais / Detecção Precoce de Câncer Tipo de estudo: Diagnostic_studies / Prognostic_studies / Risk_factors_studies / Screening_studies Limite: Humans Idioma: En Revista: Clin Colorectal Cancer Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Contexto em Saúde: 1_ASSA2030 / 2_ODS3 Base de dados: MEDLINE Assunto principal: Neoplasias Colorretais / Detecção Precoce de Câncer Tipo de estudo: Diagnostic_studies / Prognostic_studies / Risk_factors_studies / Screening_studies Limite: Humans Idioma: En Revista: Clin Colorectal Cancer Ano de publicação: 2023 Tipo de documento: Article