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BACKGROUND: Many bodies advise that people with bowel symptoms undergo colonoscopy to detect colorectal cancer. AIM: To determine which bowel symptoms predict cancer on colonoscopy. METHODS: Information was collected on symptoms, demographics and medical history from patients subsequently undergoing colonoscopy. Multiple logistic regression modelling was used to identify predictors of colorectal cancer. An ROC curve was estimated for each model, and the area under the curve (AUC) was computed. RESULTS: Cancer was found in 159 patients and no cancer or adenoma in 7577 patients. Bowel symptoms that predicted cancer were rectal bleeding, change in bowel habit and rectal mucus. Prediction was the strongest in patients who had symptoms at least weekly and commencing within the previous 12 months; abdominal pain was predictive only in such patients. The odds ratios never exceeded 4.27. A model based on age, gender, and medical history was highly predictive (AUC = 0.79). Adding symptoms to this model increased the AUC to 0.85. CONCLUSIONS: This model predicts patients in whom colonoscopy will have the highest yield. Conversely, colonoscopy can be avoided in people at low risk: in our study, 95% of cancers could have been detected by doing only 60% of the colonoscopies.
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Adelstein et al. (2010) studied this question.
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