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- Title
Risk-adjusted colorectal cancer screening using the FIT and routine screening data: development of a risk prediction model.
- Authors
Cooper, Jennifer Anne; Parsons, Nick; Stinton, Chris; Mathews, Christopher; Smith, Steve; Halloran, Stephen P; Moss, Sue; Taylor-Phillips, Sian
- Abstract
<bold>Background: </bold>The faecal immunochemical test (FIT) is replacing the guaiac faecal occult blood test in colorectal cancer screening. Increased uptake and FIT positivity will challenge colonoscopy services. We developed a risk prediction model combining routine screening data with FIT concentration to improve the accuracy of screening referrals.<bold>Methods: </bold>Multivariate analysis used complete cases of those with a positive FIT (⩾20 μg g-1) and diagnostic outcome (n=1810; 549 cancers and advanced adenomas). Logistic regression was used to develop a risk prediction model using the FIT result and screening data: age, sex and previous screening history. The model was developed further using a feedforward neural network. Model performance was assessed by discrimination and calibration, and test accuracy was investigated using clinical sensitivity, specificity and receiver operating characteristic curves.<bold>Results: </bold>Discrimination improved from 0.628 with just FIT to 0.659 with the risk-adjusted model (P=0.01). Calibration using the Hosmer-Lemeshow test was 0.90 for the risk-adjusted model. The sensitivity improved from 30.78% to 33.15% at similar specificity (FIT threshold of 160 μg g-1). The neural network further improved model performance and test accuracy.<bold>Conclusions: </bold>Combining routinely available risk predictors with the FIT improves the clinical sensitivity of the FIT with an increase in the diagnostic yield of high-risk adenomas.
- Subjects
ENGLAND; COLON tumors; COMPARATIVE studies; FECES; IMMUNOHISTOCHEMISTRY; RESEARCH methodology; MEDICAL cooperation; MULTIVARIATE analysis; RECTUM tumors; RESEARCH; RISK assessment; PILOT projects; EVALUATION research; RECEIVER operating characteristic curves; STATISTICAL models; EARLY detection of cancer; DIAGNOSIS
- Publication
British Journal of Cancer, 2018, Vol 118, Issue 2, p285
- ISSN
0007-0920
- Publication type
journal article
- DOI
10.1038/bjc.2017.375