Development and internal validation of a risk prediction model for high-risk adenomas among average risk colorectal cancer screening participants
Date
2020-09-03
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
Background: High-risk adenomas (HRAs) are precursors to colorectal cancer (CRC), and removing them during colonoscopy can halt progression to CRC. The aim of this study was to develop a risk prediction model for HRAs detected at screening colonoscopy based on readily available patient information. Subsequently, we aimed to understand if biomarkers of glucose metabolism were associated with HRAs, with hopes incorporating them into a baseline risk prediction model to enhance its clinical utility. Methods: The cohort consisted of 3,035 individuals aged 50 to 74 years with no prior history of cancer who underwent a primary screening colonoscopy at a centralized colon cancer screening centre between 2008 and 2016. A multivariable logistic regression model was created using CRC risk factors identified from prior research. Model covariates were collected from a baseline questionnaire and included patient demographics (age and sex), lifestyle parameters (body mass index, alcohol, smoking, and vitamin D supplement use) and medical history (family history of CRC and diabetes). Model calibration was assessed using the c-statistic. Glucose, insulin, glycated hemoglobin A1c, and c-peptide were all measured were assessed using a case control study design from from a subset of the CCSC biorepository.conditional logistic regression was used to understand their associations with HRAs. Results: Mean participant age was 58.8 years, and 54.7% were male. A total of 249 participants with HRAs were identified (8.2%). An optimism adjusted c-statistic of 0.67 was calculated, and a specificity and negative predictive value of 97.0% and 92.4% for the detection of HRAs respectively, were achieved using 20% predicted probability as a high-risk threshold. However, a sensitivity of only 10.8% was achieved. Our model has moderate predictive ability, with strengths in being able to rule those with an absence of HRAs on screening colonoscopy. Finally, after adjustment, no meaningful associations were found between these four biomarkers of glucose metabolism and HRAs. Conclusion: Although these glucose metabolism biomarkers were not found to be associated with HRAs, the production of a simple risk prediction model can still provide benefit to the current screening programs in Alberta. Maximizing screening efficiency through improved risk prediction can enhance resource allocation. Ultimately, this model has the potential to improve patient care by reducing unnecessary colonoscopies, limiting this invasive procedure to those most likely to have significant findings.
Description
Keywords
Colorectal Cancer, Risk prediction, Screening
Citation
Sutherland, R. L. (2020). Development and internal validation of a risk prediction model for high-risk adenomas among average risk colorectal cancer screening participants (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca.