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The Automatically Analyzed (AA) ColonView (CV) Quick Test for Fecal Occult Blood Shows Higher Diagnostic Accuracy in Detection of Colorectal Adenoma than Visually Analyzed Tests

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Background/Aim: The present study compared the accuracy of visually analyzed (VA) and automatically analyzed (AA) ColonView (CV) quick test; a new-generation fecal immunochemical test (FIT) for hemoglobin (Hb) and hemoglobin/haptoglobin… Click to show full abstract

Background/Aim: The present study compared the accuracy of visually analyzed (VA) and automatically analyzed (AA) ColonView (CV) quick test; a new-generation fecal immunochemical test (FIT) for hemoglobin (Hb) and hemoglobin/haptoglobin (Hb/Hp) (Biohit Oyj, Helsinki, Finland) in subjects participating in colorectal neoplasia (CRN) detection in Brazil. A traditional guaiac-based fecal occult blood test (gFOBT) test (HemoccultSENSA) was used as a reference. Patients and Methods: A cohort of 509 colonoscopy-referral patients were asked to collect three consecutive fecal samples, to be analyzed by both CV and SENSA. Results: In ROC analysis for the AA reading, the optimal cut-off value for CV Hb was ≥8.0912 and that for CV Hb/Hp was ≥1.8983. With these cut-offs, the sensitivity (Se), specificity (Sp), and efficiency of CV AA in detecting colorectal adenoma (CRA) were: 64.2%/78.6%, 53.4%/35.3%, and 58.6%/56.5%, for Hb and Hb/Hp, respectively. In the HSROC analysis, the AUC values for i) VA and ii) AA modes were as follows: i) AUC=0.551 (95%CI=0.500-0.602), ii) AUC=0.606 (95%CI=0.550-0.662). The difference between these AUC values was statistically significant (p=0.0160). Conclusion: The present study confirms the previous results on the applicability of the ColonView quick test in CRN screening. Of the two optional reading modes, the AA reading showed significantly better diagnostic accuracy as compared to the VA reading (or SENSA), in detecting the CRA endpoint in colonoscopy-referral patients.

Keywords: test; automatically analyzed; accuracy; colonview quick; quick test; visually analyzed

Journal Title: AntiCancer Research
Year Published: 2021

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