ReviewClinical and translational gastroenterology2016
Fecal Immunochemical Tests Combined With Other Stool Tests for Colorectal Cancer and Advanced Adenoma Detection: A Systematic Review.
Review in Clinical and translational gastroenterology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Stage-Specific Sensitivity of Fecal Immunochemical Tests for Detecting Colorectal Cancer: Systematic Review and Meta-Analysis.The American journal of gastroenterology · 2020Pooled it
- Utility of Stool-Based Tests for Colorectal Cancer Detection: A Comprehensive Review.Healthcare (Basel, Switzerland) · 2024Review
- Novel Diagnostic Biomarkers in Colorectal Cancer.International journal of molecular sciences · 2022Review
- Improvements in the Effectiveness of Early Detection in Colorectal Cancer with Open-Label Randomised Study.Journal of clinical medicine · 2021Article
- The Roadmap of Colorectal Cancer Screening.Cancers · 2021Review
- Fecal immunochemical test for hemoglobin in combination with fecal transferrin in colorectal cancer screening.United European gastroenterology journal · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesDespite moderate to high detection rates of fecal immunochemical tests (FITs) of colorectal cancer (CRC), detection of adenomas remains limited. Further stool tests exist, which are not used in routine practice, such as DNA or RNA markers and protein markers. We aimed at systematically investigating and summarizing evidence for diagnostic performance of combinations of FIT with other stool tests compared with FIT alone in early detection of CRC and its precursors.
methodsWe systematically reviewed studies that evaluated FITs in combination with other stool tests and compared measures of diagnostic accuracy with and without additional stool tests. PubMed and Web of Science were searched from inception to May 2015. Reference lists of eligible studies were also screened. Two reviewers extracted data independently.
resultsSome of the reports on DNA, RNA, or tissue tests, including tests based on DNA mutations, methylation, and integrity in selected genes as well as microRNA expression, showed some improvements of diagnostic test accuracy. In contrast, so far assessed stool protein markers did generally not lead to substantial improvements in performance of FIT when added to the latter. Many marker combinations were reported only in one study each, and few studies were conducted in a true screening setting.
conclusionsSeveral stool markers show potential to improve performance of FITs. However, the results require confirmation in further studies, which should also evaluate the costs and cost-effectiveness of combined screening strategies.
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.