Development and validation of case-finding algorithms for recurrence of breast cancer using routinely collected administrative data-Reference-Cited by-同舟云学术

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Development and validation of case-finding algorithms for recurrence of breast cancer using routinely collected administrative data

Published:2019-03-08 Issue:1 Volume:19 Page:
ISSN:1471-2407
Container-title:BMC Cancer
language:en
Short-container-title:BMC Cancer

Author:

Xu Yuan,Kong Shiying,Cheung Winson Y.,Bouchard-Fortier Antoine,Dort Joseph C.,Quan Hude,Buie Elizabeth M.,McKinnon Geoff,Quan May Lynn

Funder

CIHR Health System Impact Fellowship

Calgary Center For Clinical Research

Publisher

Springer Science and Business Media LLC

Subject

Cancer Research,Genetics,Oncology

Link

http://link.springer.com/content/pdf/10.1186/s12885-019-5432-8.pdf

Reference22 articles.

1. Carrell DS, Halgrim S, Tran DT, et al. Using natural language processing to improve efficiency of manual chart abstraction in research: the case of breast cancer recurrence. Am J Epidemiol. 2014;179:749–58.

2. Warren JL, Yabroff KR. Challenges and opportunities in measuring cancer recurrence in the United States. J Natl Cancer Inst. 2015;107.

3. Chubak J, Yu O, Pocobelli G, et al. Administrative data algorithms to identify second breast cancer events following early-stage invasive breast cancer. J Natl Cancer Inst. 2012;104:931–40.

4. Hassett MJ, Uno H, Cronin AM, Carroll NM, Hornbrook MC, Ritzwoller D. Detecting lung and colorectal Cancer recurrence using structured clinical/administrative data to enable outcomes research and population health management. Med Care. 2017;55:e88–98.

5. Kroenke CH, Chubak J, Johnson L, Castillo A, Weltzien E, Caan BJ. Enhancing breast cancer recurrence algorithms through selective use of medical record data. J Natl Cancer Inst. 2016;108.

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