Literature DB >> 19114700

Validation of a colorectal cancer risk prediction model among white patients age 50 years and older.

Yikyung Park1, Andrew Nathan Freedman, Mitchell H Gail, David Pee, Albert Hollenbeck, Arthur Schatzkin, Ruth M Pfeiffer.   

Abstract

PURPOSE: Validation of an absolute risk prediction model for colorectal cancer (CRC) by using a large, population-based cohort. PATIENTS AND METHODS: The National Institutes of Health (NIH) -American Association of Retired Persons (AARP) diet and health study, a prospective cohort study, was used to validate the model. Men and women age 50 to 71 years at baseline answered self-administered questionnaires that asked about demographic characteristics, diet, lifestyle, and medical histories. We compared expected numbers of CRC patient cases predicted by the model to the observed numbers of CRC patient cases identified in the NIH-AARP study overall and in subgroups defined by risk factor combinations. The discriminatory power was measured by the area under the receiver-operating characteristic curve (AUC).
RESULTS: During an average of 6.9 years of follow-up, we identified 2,092 and 832 incident CRC patient cases in men and women, respectively. The overall expected/observed ratio was 0.99 (95% CI, 0.95 to 1.04) in men and 1.05 (95% CI, 0.98 to 1.11) in women. Agreement between the expected and the observed number of cases was good in most risk factor categories, except for in subgroups defined by CRC screening and polyp history. This discrepancy may be caused by differences in the question on screening and polyp history between two studies. The AUC was 0.61 (95% CI, 0.60 to 0.62) for men and 0.61 (95% CI, 0.59 to 0.62) for women, which was similar to other risk prediction models.
CONCLUSION: The absolute risk model for CRC was well calibrated in a large prospective cohort study. This prediction model, which estimates an individual's risk of CRC given age and risk factors, may be a useful tool for physicians, researchers, and policy makers.

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Mesh:

Year:  2008        PMID: 19114700      PMCID: PMC2645089          DOI: 10.1200/JCO.2008.17.4813

Source DB:  PubMed          Journal:  J Clin Oncol        ISSN: 0732-183X            Impact factor:   44.544


  11 in total

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Journal:  J Natl Cancer Inst       Date:  2006-09-06       Impact factor: 13.506

2.  Validation of the Gail et al. model of breast cancer risk prediction and implications for chemoprevention.

Authors:  B Rockhill; D Spiegelman; C Byrne; D J Hunter; G A Colditz
Journal:  J Natl Cancer Inst       Date:  2001-03-07       Impact factor: 13.506

3.  Risk factors and individual probabilities of melanoma for whites.

Authors:  Eunyoung Cho; Bernard A Rosner; Diane Feskanich; Graham A Colditz
Journal:  J Clin Oncol       Date:  2005-04-20       Impact factor: 44.544

4.  Design and serendipity in establishing a large cohort with wide dietary intake distributions : the National Institutes of Health-American Association of Retired Persons Diet and Health Study.

Authors:  A Schatzkin; A F Subar; F E Thompson; L C Harlan; J Tangrea; A R Hollenbeck; P E Hurwitz; L Coyle; N Schussler; D S Michaud; L S Freedman; C C Brown; D Midthune; V Kipnis
Journal:  Am J Epidemiol       Date:  2001-12-15       Impact factor: 4.897

5.  Projecting absolute invasive breast cancer risk in white women with a model that includes mammographic density.

Authors:  Jinbo Chen; David Pee; Rajeev Ayyagari; Barry Graubard; Catherine Schairer; Celia Byrne; Jacques Benichou; Mitchell H Gail
Journal:  J Natl Cancer Inst       Date:  2006-09-06       Impact factor: 13.506

6.  Colon cancer screening, lifestyle, and risk of colon cancer.

Authors:  M L Slattery; S L Edwards; K N Ma; G D Friedman
Journal:  Cancer Causes Control       Date:  2000-07       Impact factor: 2.506

7.  Validation of a model of lung cancer risk prediction among smokers.

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Journal:  J Natl Cancer Inst       Date:  2006-05-03       Impact factor: 13.506

8.  Fruit and vegetable intakes and risk of colorectal cancer in the NIH-AARP diet and health study.

Authors:  Yikyung Park; Amy F Subar; Victor Kipnis; Frances E Thompson; Traci Mouw; Albert Hollenbeck; Michael F Leitzmann; Arthur Schatzkin
Journal:  Am J Epidemiol       Date:  2007-05-07       Impact factor: 4.897

9.  Plant foods, fiber, and rectal cancer.

Authors:  Martha L Slattery; Karen P Curtin; Sandra L Edwards; Donna M Schaffer
Journal:  Am J Clin Nutr       Date:  2004-02       Impact factor: 7.045

10.  Colorectal cancer risk prediction tool for white men and women without known susceptibility.

Authors:  Andrew N Freedman; Martha L Slattery; Rachel Ballard-Barbash; Gordon Willis; Bette J Cann; David Pee; Mitchell H Gail; Ruth M Pfeiffer
Journal:  J Clin Oncol       Date:  2008-12-29       Impact factor: 44.544

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  58 in total

1.  Colorectal cancer predicted risk online (CRC-PRO) calculator using data from the multi-ethnic cohort study.

Authors:  Brian J Wells; Michael W Kattan; Gregory S Cooper; Leila Jackson; Siran Koroukian
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2.  Co-occurring risk factors for current cigarette smoking in a U.S. nationally representative sample.

Authors:  Stephen T Higgins; Allison N Kurti; Ryan Redner; Thomas J White; Diana R Keith; Diann E Gaalema; Brian L Sprague; Cassandra A Stanton; Megan E Roberts; Nathan J Doogan; Jeff S Priest
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Review 3.  Do recent epidemiologic observations impact who and how we should screen for CRC?

Authors:  Ethan Bortniker; Joseph C Anderson
Journal:  Dig Dis Sci       Date:  2014-12-10       Impact factor: 3.199

Review 4.  Colonic Polyps: Diagnosis and Surveillance.

Authors:  Michael B Huck; Jaime L Bohl
Journal:  Clin Colon Rectal Surg       Date:  2016-12

5.  Development of a comprehensive health-risk prediction tool for postmenopausal women.

Authors:  Haley Hedlin; Julie Weitlauf; Carolyn J Crandall; Rami Nassir; Jane A Cauley; Lorena Garcia; Robert Brunner; Jennifer Robinson; Marica L Stefanick; John Robbins
Journal:  Menopause       Date:  2019-12       Impact factor: 2.953

6.  Assessing individual risk for high-risk colorectal adenoma at first-time screening colonoscopy.

Authors:  Kana Wu; Edward L Giovannucci; Yin Cao; Bernard A Rosner; Jing Ma; Rulla M Tamimi; Andrew T Chan; Charles S Fuchs
Journal:  Int J Cancer       Date:  2015-04-23       Impact factor: 7.396

7.  A Risk Prediction Model for Sporadic CRC Based on Routine Lab Results.

Authors:  Ben Boursi; Ronac Mamtani; Wei-Ting Hwang; Kevin Haynes; Yu-Xiao Yang
Journal:  Dig Dis Sci       Date:  2016-02-19       Impact factor: 3.199

8.  Risk of Advanced Neoplasia Using the National Cancer Institute's Colorectal Cancer Risk Assessment Tool.

Authors:  Thomas F Imperiale; Menggang Yu; Patrick O Monahan; Timothy E Stump; Rebeka Tabbey; Elizabeth Glowinski; David F Ransohoff
Journal:  J Natl Cancer Inst       Date:  2016-08-31       Impact factor: 13.506

9.  Personalizing colonoscopy screening for elderly individuals based on screening history, cancer risk, and comorbidity status could increase cost effectiveness.

Authors:  Frank van Hees; Sameer D Saini; Iris Lansdorp-Vogelaar; Sandeep Vijan; Reinier G S Meester; Harry J de Koning; Ann G Zauber; Marjolein van Ballegooijen
Journal:  Gastroenterology       Date:  2015-08-04       Impact factor: 22.682

10.  Derivation and Validation of a Scoring System to Stratify Risk for Advanced Colorectal Neoplasia in Asymptomatic Adults: A Cross-sectional Study.

Authors:  Thomas F Imperiale; Patrick O Monahan; Timothy E Stump; Elizabeth A Glowinski; David F Ransohoff
Journal:  Ann Intern Med       Date:  2015-09-01       Impact factor: 25.391

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