2020
DOI: 10.2139/ssrn.3576859
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New Fecal Bacterial Signature for Colorectal Cancer Screening Reduces the Fecal Immunochemical Test False-Positive Rate in a Screening Population

Abstract: Guidelines recommend routine screening for colorectal cancer (CRC) in asymptomatic adults starting at age 50. The most extensively used noninvasive test for CRC screening is the fecal immunochemical test (FIT), which has an overall sensitivity for CRC of approximately 61.0%-91.0%, which drops to 27.0%-67.0% for advanced adenomas. These figures contain a high false-positive rate and a low positive predictive value. This work aimed to develop a new, noninvasive CRC screening tool based on fecal bacterial markers… Show more

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Cited by 5 publications
(12 citation statements)
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“…For the CRC endpoint this was achieved while maintaining the same level of sensitivity as that obtained using FIT20 alone, but the sensitivity of detecting advanced adenomas, and hence the overall sensitivity in detecting AN, was signi cantly reduced (from 21.8-17.5%, a reduction of approximately 20%). These results are in line with and con rm previous results obtained in a clinical study which was restricted to participants preselected by a positive FIT in clinical practice [7].…”
Section: Discussionsupporting
confidence: 92%
See 1 more Smart Citation
“…For the CRC endpoint this was achieved while maintaining the same level of sensitivity as that obtained using FIT20 alone, but the sensitivity of detecting advanced adenomas, and hence the overall sensitivity in detecting AN, was signi cantly reduced (from 21.8-17.5%, a reduction of approximately 20%). These results are in line with and con rm previous results obtained in a clinical study which was restricted to participants preselected by a positive FIT in clinical practice [7].…”
Section: Discussionsupporting
confidence: 92%
“…In such a scenario, it is expected that the increased sensitivity provided by FIT and the potential higher speci city achieved when adding RAID-CRC Screen as a triage test would lead to higher detection rates with greater precision, thus requiring fewer colonoscopies than when using FIT alone. Even though the results were highly consistent with those from a preliminary Spanish clinical study [7], further replication in other, larger studies is highly desirable. Further studies should also aim to evaluate the performance of the test in other populations from other countries.…”
Section: Discussionsupporting
confidence: 71%
“…Although it is possible that unrecorded variables other than the test characteristics account for the observed differences, our results indicate that initial screening tests with high specificity or PPV may help to elevate adherence to colonoscopy, which has been observed in the comparison of three gFOBTs 33 and in a real‐world setting 34 . The importance of test specificity for CRC screening programs was also specially addressed in other studies 35,36 . Our findings may have implications for the importance of choosing an initial test very carefully in a given jurisdiction or country to complete the full range of screening.…”
Section: Discussionmentioning
confidence: 65%
“…34 The importance of test specificity for CRC screening programs was also specially addressed in other studies. 35,36 Our findings may have implications for the importance of choosing an initial test very carefully in a given jurisdiction or country to complete the full range of screening. Certainly, this analysis is an important step toward identifying determinants of colonoscopy adherence and bears implications for public health policy-making and practice.…”
Section: Discussionmentioning
confidence: 92%
“…This shows that our algorithm can be fine-tuned to optimize cost-effectiveness (Figure S8). A comparison of our algorithm with the current FIT strategy and other available solutions (GoodGut [47] and ColoGuard [48]) revealed higher sensitivity for both CRC and CR while maintaining a significant reduction of the current false positive rate and, importantly, without the need of collecting a separate sample from the screening (Table S6).…”
Section: Development Of a Two-phase Machine Learning Classifiermentioning
confidence: 98%