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Evaluation of Colorectal Cancer Risk and Prevalence by Stool DNA Integrity Detection
Published on: June 8, 2020
Utility of Quantitative Fecal Immunochemical Test Values for Average Risk Colorectal Cancer Screening Risk
James H-E Kang1,2, Christopher D Jensen1, Sophie Merchant1
1Kaiser Permanente Northern California Division of Research, Pleasanton, California, USA.
Introduction:
Fecal immunochemical test (FIT) for colorectal cancer (CRC) screening is interpreted qualitatively (positive/negative) by a threshold quantitative fecal hemoglobin concentration (qFIT value); patients who test positive are referred for colonoscopy. Given a small percentage of persons with a positive FIT have cancer, we evaluated whether considering qFIT value might facilitate further risk stratification among FIT-positive patients.
Methods:
Among patients aged 50-75 years with a positive FIT (≥20 μg/g) in 2013-2022 who underwent colonoscopy within 12 months, we evaluated qFIT values in 20 μg/g increments in relation with the most advanced finding at colonoscopy.
Results:
Among 78,555 eligible FITs, median qFIT values were higher for CRC (147.8 μg/g) than advanced adenoma (52.8 μg/g), clinically significant serrated polyp (40.9 μg/g), nonadvanced adenoma (40.4 μg/g), and normal findings (43 μg/g). Positive predictive values (PPVs) for advanced adenoma and CRC increased with increasing qFIT values ( P < 0.001). PPV of qFIT values for CRC increased from 0.9% (95% confidence interval [CI]: 0.8%-1.0%) to 6.7% (95% CI: 6.2%-7.2%) with concentrations in the 20-39.9 μg/g to ≥200 μg/g range. Similarly, the PPV of qFIT values for advanced adenoma increased from 13.4% (95% CI: 13.0%-13.7%) to 20.4% (95% CI: 19.5%-21.3%) with values in the 20-39.9 μg/g to ≥200 μg/g range.
Discussion:
Neoplastic findings occurred across the whole spectrum of qFIT values, emphasizing the need for colonoscopy for all positive qFIT tests. However, increasing qFIT values correlated with the PPV for CRC and advanced adenoma and may help to stratify patients at highest risk of detecting serious neoplastic lesions in resource-constrained settings.
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