Paul C Schroy1, John B Wong2, Michael J O'Brien3, Clara A Chen4, John L Griffith5. 1. Department of Medicine, Boston Medical Center, Boston University School of Medicine, Boston, Massachusetts, USA. 2. Department of Medicine, Tufts Medical Center, Boston, Massachusetts, USA. 3. Department of Pathology, Boston University School of Medicine, Boston, Massachusetts, USA. 4. Data Coordinating Center, Boston University School of Public Health, Boston, Massachusetts, USA. 5. Department of Health Sciences, Bouve College of Health Sciences, Northeastern University, Boston, Massachusetts, USA.
Abstract
OBJECTIVES: Eliciting patient preferences within the context of shared decision making has been advocated for colorectal cancer screening. Risk stratification for advanced colorectal neoplasia (ACN) might facilitate more effective shared decision making when selecting an appropriate screening option. Our objective was to develop and validate a clinical index for estimating the probability of ACN at screening colonoscopy. METHODS: We conducted a cross-sectional analysis of 3,543 asymptomatic, mostly average-risk patients 50-79 years of age undergoing screening colonoscopy at two urban safety net hospitals. Predictors of ACN were identified using multiple logistic regression. Model performance was internally validated using bootstrapping methods. RESULTS: The final index consisted of five independent predictors of risk (age, smoking, alcohol intake, height, and a combined sex/race/ethnicity variable). Smoking was the strongest predictor (net reclassification improvement (NRI), 8.4%) and height the weakest (NRI, 1.5%). Using a simplified weighted scoring system based on 0.5 increments of the adjusted odds ratio, the risk of ACN ranged from 3.2% (95% confidence interval (CI), 2.6-3.9) for the low-risk group (score ≤2) to 8.6% (95% CI, 7.4-9.7) for the intermediate/high-risk group (score 3-11). The model had moderate to good overall discrimination (C-statistic, 0.69; 95% CI, 0.66-0.72) and good calibration (P=0.73-0.93). CONCLUSIONS: A simple 5-item risk index based on readily available clinical data accurately stratifies average-risk patients into low- and intermediate/high-risk categories for ACN at screening colonoscopy. Uptake into clinical practice could facilitate more effective shared decision-making for CRC screening, particularly in situations where patient and provider test preferences differ.
OBJECTIVES: Eliciting patient preferences within the context of shared decision making has been advocated for colorectal cancer screening. Risk stratification for advanced colorectal neoplasia (ACN) might facilitate more effective shared decision making when selecting an appropriate screening option. Our objective was to develop and validate a clinical index for estimating the probability of ACN at screening colonoscopy. METHODS: We conducted a cross-sectional analysis of 3,543 asymptomatic, mostly average-risk patients 50-79 years of age undergoing screening colonoscopy at two urban safety net hospitals. Predictors of ACN were identified using multiple logistic regression. Model performance was internally validated using bootstrapping methods. RESULTS: The final index consisted of five independent predictors of risk (age, smoking, alcohol intake, height, and a combined sex/race/ethnicity variable). Smoking was the strongest predictor (net reclassification improvement (NRI), 8.4%) and height the weakest (NRI, 1.5%). Using a simplified weighted scoring system based on 0.5 increments of the adjusted odds ratio, the risk of ACN ranged from 3.2% (95% confidence interval (CI), 2.6-3.9) for the low-risk group (score ≤2) to 8.6% (95% CI, 7.4-9.7) for the intermediate/high-risk group (score 3-11). The model had moderate to good overall discrimination (C-statistic, 0.69; 95% CI, 0.66-0.72) and good calibration (P=0.73-0.93). CONCLUSIONS: A simple 5-item risk index based on readily available clinical data accurately stratifies average-risk patients into low- and intermediate/high-risk categories for ACN at screening colonoscopy. Uptake into clinical practice could facilitate more effective shared decision-making for CRC screening, particularly in situations where patient and provider test preferences differ.
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