Cancer Causes & Control

, Volume 27, Issue 10, pp 1175–1185 | Cite as

A prognostic model for advanced colorectal neoplasia recurrence

  • Lin Liu
  • Karen Messer
  • John A. Baron
  • David A. Lieberman
  • Elizabeth T. Jacobs
  • Amanda J. Cross
  • Gwen Murphy
  • Maria Elena Martinez
  • Samir Gupta
Original paper



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.


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.


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 %).


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.


Polyp surveillance Risk stratification Epidemiology Colorectal cancer Colorectal polyps 



Advanced neoplasia


Area under the receiver operating characteristic curve


Body mass index


Confidence intervals


Colorectal cancer


L1-regularized logistic regression model


Net reclassification improvement


Receiver operating characteristic


US Multisociety Task Force



This work was supported in part by Public Health Service Grants, CA-41108, CA-23074, CA95060, CA37287, CA104869, CA23108, CA59005, CA26852, and 5R01CA155293 from the National Cancer Institute. Funding for the Veteran’s Affairs Study was supported by the Cooperative Studies Program, Department of Veterans Affairs. The project described was also supported by a pilot grant from the UCSD Department of Family Medicine and Public Health (Liu, PI), as well as in part by Merit Review Award number 1 I01 HX001574-01A1 (Gupta, PI) from the United States Department of Veterans Affairs Health Services Research and Development Service of the VA Office of Research and Development. The views expressed in this article are those of the author(s) and do not necessarily represent the views of the Department of Veterans Affairs.

Author contributions

L.L., K.M., M.E.M., and S.G. contributed to study concept and design. L.L., K.M., and S.G. drafted the manuscript. L.L. and K.M performed the statistical analysis. L.L., K.M., J.A.B., D.A.L., A.J.C., M.G., M.E.M., and S.G. obtained the funding All authors contributed to acquisition, analysis, and interpretation of data, critically revised the manuscript for important intellectual content, and approved the final version of the article, including the authorship list.

Compliance with ethical standards

Conflict of interest


Supplementary material

10552_2016_795_MOESM1_ESM.docx (13 kb)
Supplementary material 1 (DOCX 13 kb)


  1. 1.
    Siegel RL, Miller KD, Jemal A (2015) Cancer statistics, 2015. CA Cancer J Clin 65:5–29CrossRefPubMedGoogle Scholar
  2. 2.
    Atkin WS, Edwards R, Kralj-Hans I, Wooldrage K, Hart AR et al (2010) Once-only flexible sigmoidoscopy screening in prevention of colorectal cancer: a multicentre randomised controlled trial. Lancet 375:1624–1633CrossRefPubMedGoogle Scholar
  3. 3.
    Lieberman DA, Rex DK, Winawer SJ, Giardiello FM, Johnson DA et al (2012) Guidelines for colonoscopy surveillance after screening and polypectomy: a consensus update by the US Multi-Society Task Force on Colorectal Cancer. Gastroenterology 143:844–857CrossRefPubMedGoogle Scholar
  4. 4.
    Martínez ME, Ahnen D, Greenberg ER (2013) One-year risk for advanced colorectal neoplasia. Ann Intern Med 158:639CrossRefPubMedGoogle Scholar
  5. 5.
    Martínez ME, Baron JA, Lieberman DA, Schatzkin A, Lanza E et al (2009) A pooled analysis of advanced colorectal neoplasia diagnoses after colonoscopic polypectomy. Gastroentereolgy 136:832–841CrossRefGoogle Scholar
  6. 6.
    Laiyemo AO, Murphy G, Albert PS, Sansbury LB, Wang Z et al (2008) Postpolypectomy colonoscopy surveillance guidelines: predictive accuracy for advanced adenoma at 4 years. Ann Intern Med 148:419–426CrossRefPubMedGoogle Scholar
  7. 7.
    Pinsky PF, Schoen RE, Weissfeld JL, Church T, Yokochi LA et al (2009) The yield of surveillance colonoscopy by adenoma history and time to examination. Clin Gastroenterol Hepatol 7:86–92CrossRefPubMedGoogle Scholar
  8. 8.
    Chung SJ, Kim YS, Yang SY, Song JH, Kim D et al (2011) Five-year risk for advanced colorectal neoplasia after initial colonoscopy according to the baseline risk stratification: a prospective study in 2452 asymptomatic Koreans. Gut 60:1537–1543CrossRefPubMedGoogle Scholar
  9. 9.
    Stegeman I, de Wijkerslooth TR, Stoop EM, van Leerdam ME, Dekker E et al (2013) Colorectal cancer risk factors in the detection of advanced adenoma and colorectal cancer. Cancer Epidemiol 37:278–283CrossRefPubMedGoogle Scholar
  10. 10.
    Saini SD, Kim HM, Schoenfeld P (2006) Incidence of advanced adenomas at surveillance colonoscopy in patients with a personal history of colon adenomas: a meta-analysis and systematic review. Gastrointest Endosc 64:614–626CrossRefPubMedGoogle Scholar
  11. 11.
    van Heijningen EM, Lansdorp-Vogelaar I, Kuipers EJ, Dekker E, Lesterhuis W et al (2013) Features of adenoma and colonoscopy associated with recurrent colorectal neoplasia based on a large community-based study. Gastroenterology 144:1410–1418CrossRefPubMedGoogle Scholar
  12. 12.
    Laiyemo AO, Pinsky PF, Marcus PM, Lanza E, Cross AJ et al (2009) Utilization and yield of surveillance colonoscopy in the continued follow-up study of the polyp prevention trial. Clin Gastroenterol Hepatol 7:562–567CrossRefPubMedGoogle Scholar
  13. 13.
    Schatzkin A, Lanza E, Corle D, Lance P, Iber F et al (2000) Lack of effect of a low-fat, high-fiber diet on the recurrence of colorectal adenomas. Polyp Prevention Trial Study Group. N Engl J Med 342:1149–1155CrossRefPubMedGoogle Scholar
  14. 14.
    Baron JA, Cole BF, Sandler RS, Haile RW, Ahnen D et al (2003) A randomized trial of aspirin to prevent colorectal adenomas. N Engl J Med 348:891–899CrossRefPubMedGoogle Scholar
  15. 15.
    Alberts DS, Martínez ME, Roe DJ, Guillen-Rodriguez JM, Marshall JR et al (2000) Lack of effect of a high-fiber cereal supplement on the recurrence of colorectal adenomas. Phoenix Colon Cancer Prevention Physicians’ Network. N Engl J Med 342:1156–1162CrossRefPubMedGoogle Scholar
  16. 16.
    Baron JA, Beach M, Mandel JS, van Stolk RU, Haile RW et al (1999) Calcium supplements for the prevention of colorectal adenomas. Calcium Polyp Prevention Study Group. N Engl J Med 340:101–107CrossRefPubMedGoogle Scholar
  17. 17.
    Greenberg ER, Baron JA, Tosteson TD, Freeman DH Jr, Beck GJ et al (1994) A clinical trial of antioxidant vitamins to prevent colorectal adenoma. Polyp Prevention Study Group. N Engl J Med 331:141–147CrossRefPubMedGoogle Scholar
  18. 18.
    Alberts DS, Martínez ME, Hess LM, Einspahr JG, Green SB et al (2005) Phase III trial of ursodeoxycholic acid to prevent colorectal adenoma recurrence. J Natl Cancer Inst 97:846–853CrossRefPubMedGoogle Scholar
  19. 19.
    Lieberman DA, Weiss DG, Bond JH, Ahnen DJ, Garewal H et al (2000) Use of colonoscopy to screen asymptomatic adults for colorectal cancer. Veterans Affairs Cooperative Study Group 380. N Engl J Med 343:162–168CrossRefPubMedGoogle Scholar
  20. 20.
    Dean CB, Nielsen JD (2007) Generalized linear mixed models: a review and some extensions. Lifetime Data Anal 13:497–512CrossRefPubMedGoogle Scholar
  21. 21.
    Steyerberg EW, Eijkemans MJ, Harrell FE Jr, Habbema JD (2000) Prognostic modelling with logistic regression analysis: a comparison of selection and estimation methods in small data sets. Stat Med 19:1059–1079CrossRefPubMedGoogle Scholar
  22. 22.
    Wang D, Zhang W, Bakhai A (2004) Comparison of Bayesian model averaging and stepwise methods for model selection in logistic regression. Stat Med 23:3451–3467CrossRefPubMedGoogle Scholar
  23. 23.
    Friedman J, Hastie T, Tibshirani R (2010) Regularization paths for generalized linear models via coordinate descent. J Stat Softw 33:1–22CrossRefPubMedPubMedCentralGoogle Scholar
  24. 24.
    Park MY, Hastie T (2007) L1-regularization path algorithm for generalized linear models. J R Stat Soc Ser B Stat Methodol 69:659–677CrossRefGoogle Scholar
  25. 25.
    Volinsky CT, Madigan D, Raftery AE, Kronmal RA (1977) Bayesian model averaging in proportional hazard models: assessing the risk of a stroke. J R Stat Soc Ser C Appl Stat 46:433–448CrossRefGoogle Scholar
  26. 26.
    Hosmer D, Lemeshow S (2000) Applied logistic regression. Wiley, New YorkCrossRefGoogle Scholar
  27. 27.
    Vermont J, Bosson JL, François P, Robert C, Rueff A et al (1991) Strategies for graphical threshold determination. Comput Methods Programs Biomed 35:141–150CrossRefPubMedGoogle Scholar
  28. 28.
    Schäfer H (1989) Constructing a cut-off point for a quantitative diagnostic test. Stat Med 8:1381–1391CrossRefPubMedGoogle Scholar
  29. 29.
    Gallop RJ, Crits-Christoph P, Muenz LR, Tu XM (2003) Determination and interpretation of the optimal operating point for ROC curves derived through generalized linear models. Underst Stat 2:219–242CrossRefGoogle Scholar
  30. 30.
    Pencina MJ, D’Agostino RB Sr, D’Agostino RB Jr, Vasan RS (2008) Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond. Stat Med 27:157–172CrossRefPubMedGoogle Scholar
  31. 31.
    Seo JY, Chun J, Lee C, Hong KS, Im JP et al (2015) Novel risk stratification for recurrence after endoscopic resection of advanced colorectal adenoma. Gastrointest Endosc 81:655–664CrossRefPubMedGoogle Scholar
  32. 32.
    Fairley KJ, Li J, Komar M, Steigerwalt N, Erlich P (2014) Predicting the risk of recurrent adenoma and incident colorectal cancer based on findings of the baseline colonoscopy. Clin Transl Gastroenterol 5:e64CrossRefPubMedPubMedCentralGoogle Scholar
  33. 33.
    van Enckevort CC, de Graaf AP, Hollema H, Sluiter WJ, Kleibeuker JH et al (2014) Predictors of colorectal neoplasia after polypectomy: based on initial and consecutive findings. Neth J Med 72:139–145PubMedGoogle Scholar
  34. 34.
    Jang ES, Kim JW, Jung YJ, Jeong JB, Kim BG et al (2013) Clinical and endoscopic predictors of colorectal adenoma recurrence after colon polypectomy. Turk J Gastroenterol 24:476–482CrossRefPubMedGoogle Scholar
  35. 35.
    Brenner H, Chang-Claude J, Jansen L, Seiler CM, Hoffmeister M (2012) Role of colonoscopy and polyp characteristics in colorectal cancer after colonoscopic polyp detection: a population-based case–control study. Ann Intern Med 157:225–232CrossRefPubMedGoogle Scholar
  36. 36.
    Cottet V, Jooste V, Fournel I, Bouvier AM, Faivre J et al (2012) Long-term risk of colorectal cancer after adenoma removal: a population-based cohort study. Gut 61:1180–1186CrossRefPubMedGoogle Scholar
  37. 37.
    de Jonge V, Sint Nicolaas J, van Leerdam ME, Kuipers EJ, Veldhuyzen van Zanten SJ (2011) Systematic literature review and pooled analyses of risk factors for finding adenomas at surveillance colonoscopy. Endoscopy 43:560–572CrossRefPubMedGoogle Scholar
  38. 38.
    Nusko G, Hahn EG, Mansmann U (2008) Risk of advanced metachronous colorectal adenoma during long-term follow-up. Int J Colorectal Dis 23:1065–1071CrossRefPubMedGoogle Scholar
  39. 39.
    Bonithon-Kopp C, Piard F, Fenger C, Cabeza E, O’Morain C et al (2004) Colorectal adenoma characteristics as predictors of recurrence. Dis Colon Rectum 47:323–333CrossRefPubMedGoogle Scholar
  40. 40.
    Bertario L, Russo A, Sala P, Pizzetti P, Ballardini G et al (2003) Predictors of metachronous colorectal neoplasms in sporadic adenoma patients. Int J Cancer 105:82–87CrossRefPubMedGoogle Scholar
  41. 41.
    Nusko G, Mansmann U, Kirchner T, Hahn EG (2002) Risk related surveillance following colorectal polypectomy. Gut 51:424–428CrossRefPubMedPubMedCentralGoogle Scholar
  42. 42.
    Gschwantler M, Kriwanek S, Langner E, Goritzer B, Schrutka-Kolbl C et al (2002) High-grade dysplasia and invasive carcinoma in colorectal adenomas: a multivariate analysis of the impact of adenoma and patient characteristics. Eur J Gastroenterol Hepatol 14:183–188CrossRefPubMedGoogle Scholar
  43. 43.
    Bertario L, Russo A, Sala P, Pizzetti P, Ballardini G et al (1999) Risk of colorectal cancer following colonoscopic polypectomy. Tumori 85:157–162PubMedGoogle Scholar
  44. 44.
    Yang G, Zheng W, Sun QR, Shu XO, Li WD et al (1998) Pathologic features of initial adenomas as predictors for metachronous adenomas of the rectum. J Natl Cancer Inst 90:1661–1665CrossRefPubMedGoogle Scholar
  45. 45.
    Triantafyllou K, Papatheodoridis GV, Paspatis GA, Vasilakaki TH, Elemenoglou I et al (1997) Predictors of the early development of advanced metachronous colon adenomas. Hepatogastroenterology 44:533–538PubMedGoogle Scholar
  46. 46.
    Corley DA, Jensen CD, Marks AR, Zhao WK, Lee JK et al (2014) Adenoma detection rate and risk of colorectal cancer and death. N Engl J Med 370:1298–1306CrossRefPubMedPubMedCentralGoogle Scholar
  47. 47.
    Kaminski MF, Regula J, Kraszewska E, Polkowski M, Wojciechowska U et al (2010) Quality indicators for colonoscopy and the risk of interval cancer. N Engl J Med 362:1795–1803CrossRefPubMedGoogle Scholar
  48. 48.
    Leggett BA, Hewett DG (2015) Colorectal cancer screening. Intern Med J 45:6–15CrossRefPubMedGoogle Scholar
  49. 49.
    Imperiale TF, Ransohoff DF, Itzkowitz SH, Levin TR, Lavin P et al (2014) Multitarget stool DNA testing for colorectal-cancer screening. N Engl J Med 370:1287–1297CrossRefPubMedGoogle Scholar

Copyright information

© Springer International Publishing Switzerland (outside the USA) 2016

Authors and Affiliations

  • Lin Liu
    • 1
    • 2
  • Karen Messer
    • 1
    • 2
  • John A. Baron
    • 3
  • David A. Lieberman
    • 4
  • Elizabeth T. Jacobs
    • 5
  • Amanda J. Cross
    • 6
    • 7
  • Gwen Murphy
    • 8
  • Maria Elena Martinez
    • 1
    • 2
  • Samir Gupta
    • 9
    • 2
    • 10
  1. 1.Division of Biostatistics and Bioinformatics, Department of Family Medicine and Public HealthUniversity of California San DiegoLa JollaUSA
  2. 2.University of California San Diego Moores Cancer CenterLa JollaUSA
  3. 3.Department of MedicineUniversity of North Carolina School of MedicineChapel HillUSA
  4. 4.Division of Gastroenterology and HepatologyVeterans Affairs Medical Center and Oregon Health and Science UniversityPortlandUSA
  5. 5.University of Arizona Cancer Center, Arizona College of Public HealthUniversity of ArizonaTucsonUSA
  6. 6.Department of Epidemiology and Biostatistics, School of Public HealthImperial College LondonLondonUK
  7. 7.Cancer Screening and Prevention Research Group, Department of Surgery and CancerImperial College LondonLondonUK
  8. 8.Division of Cancer Epidemiology and Genetics, Department of Health and Human ServicesNational Cancer Institute, National Institutes of HealthRockvilleUSA
  9. 9.Veteran Affairs San Diego Healthcare SystemSan DiegoUSA
  10. 10.Division of Gastroenterology, Department of Internal MedicineUniversity of California San DiegoLa JollaUSA

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