Original Article
Prediction of colorectal cancer risk among adults in a lower middle-income country
Abstract
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.
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.
