Imperial College London
Portrait Picture

Professor Amanda Cross

Faculty of Medicine, School of Public Health

Professor of Cancer Epidemiology
 
 
 
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Contact

 

+44 (0)20 7594 3338amanda.cross

 
 
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Assistant

 

Mr Will Kay +44 (0)20 7594 3350

 
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Location

 

Room 1089Queen Elizabeth the Queen Mother Wing (QEQM)St Mary's Campus

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Summary

 

Publications

Citation

BibTex format

@article{Liu:2016:10.1007/s10552-016-0795-5,
author = {Liu, L and Messer, K and Baron, JA and Lieberman, DA and Jacobs, ET and Cross, AJ and Murphy, G and Martinez, ME and Gupta, S},
doi = {10.1007/s10552-016-0795-5},
journal = {Cancer Causes & Control},
title = {A prognostic model for advanced colorectal neoplasia recurrence.},
url = {http://dx.doi.org/10.1007/s10552-016-0795-5},
year = {2016}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
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.
AU  - Liu,L
AU  - Messer,K
AU  - Baron,JA
AU  - Lieberman,DA
AU  - Jacobs,ET
AU  - Cross,AJ
AU  - Murphy,G
AU  - Martinez,ME
AU  - Gupta,S
DO  - 10.1007/s10552-016-0795-5
PY  - 2016///
SN  - 1573-7225
TI  - A prognostic model for advanced colorectal neoplasia recurrence.
T2  - Cancer Causes & Control
UR  - http://dx.doi.org/10.1007/s10552-016-0795-5
ER  -
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