Thomas F Imperiale1,2,3, Patrick O Monahan4, Timothy E Stump4, David F Ransohoff5. 1. Division of Gastroenterology and Hepatology, Department of Medicine, Indiana University School of Medicine. 2. The Center for Innovation, Health Services Research and Development, Roudebush Virginia Medical Center. 3. Regenstrief Institute; Indianapolis, Indiana. 4. Department of Biostatistics, Indiana University School of Medicine. 5. Department of Medicine, University of North Carolina at Chapel Hill, North Carolina, USA.
Abstract
BACKGROUND: Models estimating risk for advanced proximal colorectal neoplasia (APN) may be used to select colorectal cancer (CRC) screening test, either prior to knowing distal colorectal findings or afterward. Current models have only fair discrimination and nearly all require knowing distal findings. OBJECTIVE: Derive and test risk prediction models for APN with and without distal findings. SETTING: Selected endoscopy centers within central Indiana, USA. PARTICIPANTS: Average-risk persons undergoing first-time screening colonoscopy. INTERVENTIONS: Demographics, personal and family medical history, lifestyle factors and physical measures were linked to the most advanced finding in proximal and distal colorectal segments. For both models, logistic regression identified factors independently associated with APN on a derivation set. Based on equation coefficients, points were assigned to each factor, and risk for APN was examined for each score. Scores with comparable risks were collapsed into risk categories. Both models and their scoring systems were tested on the validation set. MAIN OUTCOME: APN, defined as any adenoma or sessile serrated lesion ≥1 cm, one with villous histology or high-grade dysplasia, or CRC proximal to the descending colon. RESULTS: Among 3025 subjects in the derivation set (mean age 57.3 ± 6.5 years; 52% women), APN prevalence was 4.5%; 2859 (94.5%) had complete data on risk factors. Independently associated with APN were age, sex, cigarette smoking, cohabitation status, metabolic syndrome, non-steroidal anti-inflammatory drug use and physical activity. This model (without distal findings) was well-calibrated (P = 0.62) and had good discrimination (c-statistic = 0.73). In low-, intermediate- and high-risk groups that comprised 21, 58 and 21% of the sample, respectively, APN risks were 1.47% (95% CI, 0.67-2.77%), 3.09% (CI, 2.31-4.04%) and 11.6% (CI, 9.10-14.4%), respectively (P < 0.0001), with no proximal CRCs in the low-risk group and 2 in the intermediate-risk group. When tested in the validation set of 1455, the model retained good metrics (calibration P = 0.85; c-statistic = 0.83), with APN risks in low- (22%), intermediate- (56%) and high-risk (22%) subgroups of 0.62% (CI, 0.08-2.23%) 2.20% (CI, 1.31-3.46%) and 13.0% (CI, 9.50-17.2%), respectively (P < 0.0001). There were no proximal CRCs in the low-risk group, and two in the intermediate-risk group. The model with distal findings performed comparably, with validation set metrics of 0.18 for calibration, 0.76 for discrimination and APN risk (% sample) in low-, intermediate-, and high-risk groups of 1.1 (69%), 8.3 (22%) and 22.3% (9%). CONCLUSION: These models stratify large proportions of average-risk persons into clinically meaningful risk groups, and could improve screening efficiency, particularly for noncolonoscopy-based programs.
BACKGROUND: Models estimating risk for advanced proximal colorectal neoplasia (APN) may be used to select colorectal cancer (CRC) screening test, either prior to knowing distal colorectal findings or afterward. Current models have only fair discrimination and nearly all require knowing distal findings. OBJECTIVE: Derive and test risk prediction models for APN with and without distal findings. SETTING: Selected endoscopy centers within central Indiana, USA. PARTICIPANTS: Average-risk persons undergoing first-time screening colonoscopy. INTERVENTIONS: Demographics, personal and family medical history, lifestyle factors and physical measures were linked to the most advanced finding in proximal and distal colorectal segments. For both models, logistic regression identified factors independently associated with APN on a derivation set. Based on equation coefficients, points were assigned to each factor, and risk for APN was examined for each score. Scores with comparable risks were collapsed into risk categories. Both models and their scoring systems were tested on the validation set. MAIN OUTCOME: APN, defined as any adenoma or sessile serrated lesion ≥1 cm, one with villous histology or high-grade dysplasia, or CRC proximal to the descending colon. RESULTS: Among 3025 subjects in the derivation set (mean age 57.3 ± 6.5 years; 52% women), APN prevalence was 4.5%; 2859 (94.5%) had complete data on risk factors. Independently associated with APN were age, sex, cigarette smoking, cohabitation status, metabolic syndrome, non-steroidal anti-inflammatory drug use and physical activity. This model (without distal findings) was well-calibrated (P = 0.62) and had good discrimination (c-statistic = 0.73). In low-, intermediate- and high-risk groups that comprised 21, 58 and 21% of the sample, respectively, APN risks were 1.47% (95% CI, 0.67-2.77%), 3.09% (CI, 2.31-4.04%) and 11.6% (CI, 9.10-14.4%), respectively (P < 0.0001), with no proximal CRCs in the low-risk group and 2 in the intermediate-risk group. When tested in the validation set of 1455, the model retained good metrics (calibration P = 0.85; c-statistic = 0.83), with APN risks in low- (22%), intermediate- (56%) and high-risk (22%) subgroups of 0.62% (CI, 0.08-2.23%) 2.20% (CI, 1.31-3.46%) and 13.0% (CI, 9.50-17.2%), respectively (P < 0.0001). There were no proximal CRCs in the low-risk group, and two in the intermediate-risk group. The model with distal findings performed comparably, with validation set metrics of 0.18 for calibration, 0.76 for discrimination and APN risk (% sample) in low-, intermediate-, and high-risk groups of 1.1 (69%), 8.3 (22%) and 22.3% (9%). CONCLUSION: These models stratify large proportions of average-risk persons into clinically meaningful risk groups, and could improve screening efficiency, particularly for noncolonoscopy-based programs.
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