TY - JOUR
T1 - A prognostic model for advanced colorectal neoplasia recurrence
AU - Liu, Lin
AU - Messer, Karen
AU - Baron, John A.
AU - Lieberman, David A.
AU - Jacobs, Elizabeth T.
AU - Cross, Amanda J.
AU - Murphy, Gwen
AU - Martinez, Maria Elena
AU - Gupta, Samir
N1 - Publisher Copyright:
© 2016, Springer International Publishing Switzerland (outside the USA).
PY - 2016/10/1
Y1 - 2016/10/1
N2 - Purpose: Following colonoscopic polypectomy, US Multisociety Task Force (USMSTF) guidelines stratify patients based on risk of subsequent advanced neoplasia (AN) using number, size, and histology of resected polyps, but have only moderate sensitivity and specificity. We hypothesized that a state-of-the-art statistical prediction model might improve identification of patients at high risk of future AN and address these challenges. Methods: Data were pooled from seven prospective studies which had follow-up ascertainment of metachronous AN within 3–5 years of baseline polypectomy (combined n = 8,228). Pooled data were randomly split into training (n = 5,483) and validation (n = 2,745) sets. A prognostic model was developed using best practices. Two risk cut-points were identified in the training data which achieved a 10 percentage point improvement in sensitivity and specificity, respectively, over current USMSTF guidelines. Clinical benefit of USMSTF versus model-based risk stratification was then estimated using validation data. Results: The final model included polyp location, prior polyp history, patient age, and number, size and histology of resected polyps. The first risk cut-point improved sensitivity but with loss of specificity. The second risk cut-point improved specificity without loss of sensitivity (specificity 46.2 % model vs. 42.1 % guidelines, p < 0.001; sensitivity 75.8 % model vs. 74.0 % guidelines, p = 0.64). Estimated AUC was 65 % (95 % CI: 62–69 %). Conclusion: This model-based approach allows flexibility in trading sensitivity and specificity, which can optimize colonoscopy over- versus underuse rates. Only modest improvements in prognostic power are possible using currently available clinical data. Research considering additional factors such as adenoma detection rate for risk prediction appears warranted.
AB - Purpose: Following colonoscopic polypectomy, US Multisociety Task Force (USMSTF) guidelines stratify patients based on risk of subsequent advanced neoplasia (AN) using number, size, and histology of resected polyps, but have only moderate sensitivity and specificity. We hypothesized that a state-of-the-art statistical prediction model might improve identification of patients at high risk of future AN and address these challenges. Methods: Data were pooled from seven prospective studies which had follow-up ascertainment of metachronous AN within 3–5 years of baseline polypectomy (combined n = 8,228). Pooled data were randomly split into training (n = 5,483) and validation (n = 2,745) sets. A prognostic model was developed using best practices. Two risk cut-points were identified in the training data which achieved a 10 percentage point improvement in sensitivity and specificity, respectively, over current USMSTF guidelines. Clinical benefit of USMSTF versus model-based risk stratification was then estimated using validation data. Results: The final model included polyp location, prior polyp history, patient age, and number, size and histology of resected polyps. The first risk cut-point improved sensitivity but with loss of specificity. The second risk cut-point improved specificity without loss of sensitivity (specificity 46.2 % model vs. 42.1 % guidelines, p < 0.001; sensitivity 75.8 % model vs. 74.0 % guidelines, p = 0.64). Estimated AUC was 65 % (95 % CI: 62–69 %). Conclusion: This model-based approach allows flexibility in trading sensitivity and specificity, which can optimize colonoscopy over- versus underuse rates. Only modest improvements in prognostic power are possible using currently available clinical data. Research considering additional factors such as adenoma detection rate for risk prediction appears warranted.
KW - Colorectal cancer
KW - Colorectal polyps
KW - Epidemiology
KW - Polyp surveillance
KW - Risk stratification
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U2 - 10.1007/s10552-016-0795-5
DO - 10.1007/s10552-016-0795-5
M3 - Article
C2 - 27517467
AN - SCOPUS:84982132588
SN - 0957-5243
VL - 27
SP - 1175
EP - 1185
JO - Cancer Causes and Control
JF - Cancer Causes and Control
IS - 10
ER -