Browsing by Author "Samarakoon, Y.M."

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Prediction of colorectal cancer risk among adults in a lower middle-income country
(AME Publishing Company, 2019) Samarakoon, Y.M.; Gunawardena, N.S.; Pathirana, A.; Perera, M.N.; Hewage, S.A.
BACKGROUND: Globally, colorectal cancer (CRC) is ranked as the third most common cancer in men and the second in women. Use of a simple, validated risk prediction tool will offer a low-cost mechanism to identify the high-risk individuals for CRC. This will increase efficient use of limited resources and early identification of patients. The aim of our study was to develop and validate a risk prediction model for developing CRC for Sri Lankan adults. METHODS: The risk predictors were based on the risk factors identified through a logistic regression model along with expert opinion. A case control design utilizing 65 CRC new cases and 65 hospital controls aged 30 years or more was used to assess the criterion validity and reliability of the model. The information was obtained using an interviewer administered questionnaire based on the risk prediction model. RESULTS: The developed model consisted of eight predictors with an area under the curve (AUC) of 0.849 (95% CI: 0.8 to 0.9, P<0.001). It has a sensitivity of 76.9%, specificity of 83.1%, positive predictive value (PPV) of 82.0%, negative predictive value (NPV) of 79.3%. Positive and negative likelihood ratios are 4.6 and 0.3. Test re-test reliability revealed a Kappa coefficient of 0.88. CONCLUSIONS: The model developed to predict the risk of CRC among adults aged 30 years and above was proven to be valid and reliable and it is an effective tool to be used as the first step to identify the high-risk population who should be referred for colonoscopy examination. © Journal of Gastrointestinal Oncology. All rights reserved.
Risk prediction models for colorectal cancer: A Scoping review
(Postgraduate Institute of Medicine University of Colombo, 2017) Samarakoon, Y.M.; Pathmeswaran, A.; Gunawardena, N.S.
BACKGROUND AND OBJECTIVES: Many risk prediction models have been developed globally to identify specific populations at high risk for colorectal cancer in specific settings. Documentation of available evidence from existing studies will serve as a useful information base. We performed a scoping review, to review and analyse published risk prediction models for colorectal cancer the world over. METHODS: A scoping review was undertaken to address the following question ‘what are the existing risk prediction models to identify the risk of developing colorectal cancer among individuals in different countries and settings?’ using the framework developed by Arksey and O’Malley for scoping reviews. Forty-one articles were included in this review from database searches and from additional searches. The titles and abstracts were reviewed using predetermined screening criteria. We limited our search to existing literature in English language and included both observational and interventional studies. RESULTS: Out of the 58 risk prediction models identified, most were developed for colorectal cancer followed by advanced colorectal cancer. Most of the articles reviewed were cross sectional studies or cohort studies. Statistical methods such as multiple logistic regression was used by a majority, while few have incorporated non-statistical methods such as consensus method and extracting data from published literature. The authors of the 58 risk prediction models have considered 77 different risk factors excluding the genetic variants. CONCLUSIONS: This comprehensive scoping review demonstrates the capacity of the existing risk models to stratify the general population into risk categories, detailing the studies conducted, location, study design, outcome, overview of the methods, data source and the identified risk predictors. While striving to build on existing knowledge, the review also identifies the research gaps and the need for further improvement.