Literature DB >> 15734968

A simulation model for colorectal cancer screening: potential of stool tests with various performance characteristics compared with screening colonoscopy.

Ulrike Haug1, Hermann Brenner.   

Abstract

OBJECTIVE: Many new stool tests intended to detect neoplastic cells or cell products are developed at present for colorectal cancer (CRC) screening. The aim of this study was to simulate a population-based screening setting to assess and compare the potential for early detection and prevention of CRC of screening based on stool tests with different sensitivity and specificity and of screening with colonoscopy as a primary screening tool.
METHOD: A Markov model was developed aimed to estimate the proportion of CRC cases which are early detected or prevented due to screening as well as the number of equired stool tests and colonoscopies per early detected or prevented CRC case. Model outcomes were calculated for the offer of annual stool testing from age 55 to 74 in combination with colonoscopic follow-up of positive test results and for the offer of screening colonoscopy as a primary screening tool at ages 55 and 65. The long-lasting risk reduction of colonoscopy allowing the removal of precancerous lesions was taken into account quantitatively.
RESULTS: For a variety of stool tests with different performance characteristics, the proportion of CRC cases early detected or prevented was estimated to be higher for stool testing in combination with colonoscopic follow-up of positive test results compared with screening colonoscopy assuming levels of compliance to be expected for the respective screening scheme. Optimizing performance characteristics of stool tests in terms of detecting precancerous lesions, in addition to those in terms of detecting CRC, seemed to be crucial for maximizing effectiveness of CRC screening with stool tests.
CONCLUSION: Screening based on new stool tests with colonoscopic follow-up of positive test results might offer a high potential for early detection or prevention of CRC.

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Year:  2005        PMID: 15734968     DOI: 10.1158/1055-9965.EPI-04-0411

Source DB:  PubMed          Journal:  Cancer Epidemiol Biomarkers Prev        ISSN: 1055-9965            Impact factor:   4.254


  8 in total

Review 1.  Calibration methods used in cancer simulation models and suggested reporting guidelines.

Authors:  Natasha K Stout; Amy B Knudsen; Chung Yin Kong; Pamela M McMahon; G Scott Gazelle
Journal:  Pharmacoeconomics       Date:  2009       Impact factor: 4.981

2.  Time to fecal immunochemical test completion for colorectal cancer screening.

Authors:  Cameron B Haas; Amanda I Phipps; Anjum Hajat; Jessica Chubak; Karen J Wernli
Journal:  Am J Manag Care       Date:  2019-04       Impact factor: 2.229

3.  Screening: part 19 of a series on evaluation of scientific publications.

Authors:  Claudia Spix; Maria Blettner
Journal:  Dtsch Arztebl Int       Date:  2012-05-25       Impact factor: 5.594

4.  The colorectal cancer screening process in community settings: a conceptual model for the population-based research optimizing screening through personalized regimens consortium.

Authors:  Jasmin A Tiro; Aruna Kamineni; Theodore R Levin; Yingye Zheng; Joanne S Schottinger; Carolyn M Rutter; Douglas A Corley; Celette S Skinner; Jessica Chubak; Chyke A Doubeni; Ethan A Halm; Samir Gupta; Karen J Wernli; Carrie Klabunde
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2014-06-10       Impact factor: 4.254

5.  What is a Reasonable Screening Test for Colorectal Cancer.

Authors:  Young Jin Kim
Journal:  J Korean Soc Coloproctol       Date:  2010-12-31

6.  Tumour M2-PK as a stool marker for colorectal cancer: comparative analysis in a large sample of unselected older adults vs colorectal cancer patients.

Authors:  U Haug; D Rothenbacher; M N Wente; C M Seiler; C Stegmaier; H Brenner
Journal:  Br J Cancer       Date:  2007-04-03       Impact factor: 7.640

7.  Faecal ribosomal protein L19 is a genetic prognostic factor for survival in colorectal cancer.

Authors:  C-J Huang; C-C Chien; S-H Yang; C-C Chang; H-L Sun; Y-C Cheng; C-C Liu; S-C Lin; C-M Lin
Journal:  J Cell Mol Med       Date:  2008-02-04       Impact factor: 5.310

8.  A simulation model of colorectal cancer surveillance and recurrence.

Authors:  Johnie Rose; Knut Magne Augestad; Chung Yin Kong; Neal J Meropol; Michael W Kattan; Qingqing Hong; Xuebei An; Gregory S Cooper
Journal:  BMC Med Inform Decis Mak       Date:  2014-04-08       Impact factor: 2.796

  8 in total

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