Show simple item record

A prediction model for colon cancer surveillance data

dc.contributor.authorGood, Norm M.en_US
dc.contributor.authorSuresh, Krithikaen_US
dc.contributor.authorYoung, Graeme P.en_US
dc.contributor.authorLockett, Trevor J.en_US
dc.contributor.authorMacrae, Finlay A.en_US
dc.contributor.authorTaylor, Jeremy M. G.en_US
dc.date.accessioned2015-08-05T16:47:27Z
dc.date.available2016-09-06T15:43:59Zen
dc.date.issued2015-08-15en_US
dc.identifier.citationGood, Norm M.; Suresh, Krithika; Young, Graeme P.; Lockett, Trevor J.; Macrae, Finlay A.; Taylor, Jeremy M. G. (2015). "A prediction model for colon cancer surveillance data." Statistics in Medicine 34(18): 2662-2675.en_US
dc.identifier.issn0277-6715en_US
dc.identifier.issn1097-0258en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/112258
dc.publisherWiley Periodicals, Inc.en_US
dc.publisherCRC Press, Inc.en_US
dc.subject.othercolonoscopyen_US
dc.subject.othercancer surveillanceen_US
dc.subject.otherinterval censoreden_US
dc.subject.otheradenomaen_US
dc.subject.othercomplementary log‐log linken_US
dc.subject.otherPoisson processen_US
dc.titleA prediction model for colon cancer surveillance dataen_US
dc.typeArticleen_US
dc.rights.robotsIndexNoFollowen_US
dc.subject.hlbsecondlevelStatistics and Numeric Dataen_US
dc.subject.hlbsecondlevelPublic Healthen_US
dc.subject.hlbsecondlevelMedicine (General)en_US
dc.subject.hlbtoplevelScienceen_US
dc.subject.hlbtoplevelSocial Sciencesen_US
dc.subject.hlbtoplevelHealth Sciencesen_US
dc.description.peerreviewedPeer Revieweden_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/112258/1/sim6500-sup-0001-Supplementary1.pdf
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/112258/2/sim6500.pdf
dc.identifier.doi10.1002/sim.6500en_US
dc.identifier.sourceStatistics in Medicineen_US
dc.identifier.citedreferenceTaylor JMG, Park Y, Ankerst DP, Proust‐Lima C, Williams S, Kestin L, Bae K, Pickles T, Sandler H. Real‐time individual predictions of prostate cancer recurrence using joint models. Biometrics 2013; 69 ( 1 ): 206 – 213.en_US
dc.identifier.citedreferenceRutter CM, Yu O, Miglioretti DL. A hierarchical non‐homogenous Poisson model for meta‐analysis of adenoma counts. Statistics in Medicine 2007; 26 ( 1 ): 98 – 109.en_US
dc.identifier.citedreferenceBampton PA, Sandford JJ, Cole SR, Smith A, Morcom J, Cadd B, Young GP. Interval faecal occult blood testing in a colonoscopy based screening programme detects additional pathology. Gut 2005; 54 ( 6 ): 803 – 806.en_US
dc.identifier.citedreferenceBampton PA, Sandford JJ, Young GP. Achieving long‐term compliance with colonoscopic surveillance guidelines for patients at increased risk of colorectal cancer in Australia. International Journal of Clinical Practice 2007; 61 ( 3 ): 510 – 513.en_US
dc.identifier.citedreferenceLane JM, Chow E, Young GP, Good N, Smith A, Bull J, Sandford J, Morcom J, Bampton PA, Cole SR. Interval fecal immunochemical testing in a colonoscopic surveillance program speeds detection of colorectal neoplasia. Gastroenterology 2010; 139 ( 6 ): 1918 – 1926.en_US
dc.identifier.citedreferenceDowling DJ, St John DJB, Macrae FA, Hopper JL. Yield from colonoscopic screening in people with a strong family history of common colorectal cancer. Journal of Gastroenterology and Hepatology 2000; 15 ( 8 ): 939 – 944.en_US
dc.identifier.citedreferenceBrown GJE, St John DJB, Macrae FA, Aittomäki K. Cancer risk in young women at risk of hereditary nonpolyposis colorectal cancer: implications for gynecologic surveillance. Gynecologic Oncology 2001; 80 ( 3 ): 346 – 349.en_US
dc.identifier.citedreferenceGood N, Macrae F, Young G, O'Dywer J, Slattery M, Venables W, Lockett T, O'Dywer M. Ideal colonoscopic surveillance intervals to reduce incidence of advanced adenoma and colorectal cancer. Journal of Gastroenterology and Hepatology 2015. DOI: 10.1111/jgh.12904.en_US
dc.identifier.citedreferenceDay DW, Morson BC. The adenoma‐carcinoma sequence. Major Problems in Pathology 1977; 10: 58 – 71.en_US
dc.identifier.citedreferenceWinawer SJ, Zauber AG. The advanced adenoma as the primary target of screening.. Gastrointestinal Endoscopy Clinics of North America 2002; 12 ( 1 ): 1 – 9.en_US
dc.identifier.citedreferenceZauber AG, Lansdorp‐Vogelaar I, Knudsen AB, Wilschut J, van Ballegooijen M, Kuntz KM. Evaluating test strategies for colorectal cancer screening: a decision analysis for the US Preventive Services Task Force. Annals of Internal Medicine 2008; 149 ( 9 ): 659 – 669.en_US
dc.identifier.citedreferenceFrazier AL, Colditz GA, Fuchs CS, Kuntz KM. Cost‐effectiveness of screening for colorectal cancer in the general population. Journal of the American Medical Association 2000; 284 ( 15 ): 1954 – 1961.en_US
dc.identifier.citedreferenceLieberman DA. Cost‐effectiveness model for colon cancer screening. Gastroenterology 1995; 109 ( 6 ): 1781 – 1790.en_US
dc.identifier.citedreferenceO'Leary BA, Olynyk JK, Neville AM, Platell CF. Cost‐effectiveness of colorectal cancer screening: comparison of community‐based flexible sigmoidoscopy with fecal occult blood testing and colonoscopy. Journal of Gastroenterology and Hepatology 2004; 19 ( 1 ): 38 – 47.en_US
dc.identifier.citedreferenceAllison JE, Tekawa IS, Ransom LJ, Adrain AL. A comparison of fecal occult‐blood tests for colorectal‐cancer screening. New England Journal of Medicine 1996; 334 ( 3 ): 155 – 160.en_US
dc.identifier.citedreferenceLevin B, Lieberman DA, McFarland B, Smith RA, Brooks D, Andrews KS, Dash C, Giardiello FM, Glick S, Levin TR, Pickhardt P, Rex DK, Thorson A, Winawer SJ. Screening and surveillance for the early detection of colorectal cancer and adenomatous polyps, 2008: a joint guideline from the American Cancer Society, the US multi‐society task force on colorectal cancer, and the American College of Radiology. CA: A Cancer Journal for Clinicians 2008; 58 ( 3 ): 130 – 160.en_US
dc.identifier.citedreferenceRizopoulos D. Dynamic predictions and prospective accuracy in joint models for longitudinal and time‐to‐event data. Biometrics 2011; 67 ( 3 ): 819 – 829.en_US
dc.identifier.citedreferenceWang Y, Taylor JMG. Jointly modeling longitudinal and event time data with application to acquired immunodeficiency syndrome. Journal of the American Statistical Association 2001; 96 ( 455 ): 895 – 905.en_US
dc.identifier.citedreferenceYu M, Law NJ, Taylor JMG, Sandler HM. Joint longitudinal‐survival‐cure models and their application to prostate cancer. Statistica Sinica 2004; 14 ( 3 ): 835 – 862.en_US
dc.identifier.citedreferencevan Houwelingen H, Putter H. 2011; Dynamic Prediction in Clinical Survival Analysis. CRC Press, Inc.: Boca Raton, FL.en_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


Files in this item

Show simple item record

Remediation of Harmful Language

The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.

Accessibility

If you are unable to use this file in its current format, please select the Contact Us link and we can modify it to make it more accessible to you.