@article{c119d2fe55df4fc9bd866255dd0455d1,
title = "Why do epidemiologic studies find an inverse association between intraprostatic inflammation and prostate cancer: A possible role for colliding bias?",
abstract = "Inflammation is an emerging risk factor for prostate cancer based largely on evidence from animal models and histopathologic observations. However, findings from patho-epidemiologic studies of intraprostatic inflammation and prostate cancer have been less supportive, with inverse associations observed in many studies of intraprostatic inflammation and prostate cancer diagnosis. Here, we propose collider stratification bias as a potential methodologic explanation for these inverse findings and provide strategies for conducting future etiologic studies of intraprostatic inflammation and prostate cancer.",
author = "Langston, {Marvin E.} and Sfanos, {Karen S.} and Saira Khan and Nguyen, {Trang Q.} and {de Marzo}, {Angelo M.} and Platz, {Elizabeth A.} and Siobhan Sutcliffe",
note = "Funding Information: Effort for Langston is supported by the NIDDK grant K12DK111028. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. Funding Information: S. Khan reports grants from Department of Defense during the conduct of the study. E.A. Platz reports personal fees from Kaiser Permanente Northern California, Division of Research outside the submitted work. S. Sutcliffe reports grants from NIH during the conduct of the study. The Editor-in-Chief of Cancer Epidemiology, Biomarkers & Prevention is an author on this article. In keeping with AACR editorial policy, a senior member of the Cancer Epidemiology, Biomarkers & Prevention editorial team managed the consideration process for this submission and independently rendered the final decision concerning acceptability. No disclosures were reported by the other authors. Publisher Copyright: {\textcopyright} 2021 American Association for Cancer Research.",
year = "2021",
month = feb,
doi = "10.1158/1055-9965.EPI-20-1009",
language = "English",
volume = "30",
pages = "255--259",
journal = "Cancer Epidemiology Biomarkers and Prevention",
issn = "1055-9965",
number = "2",
}