Dataset Information

Periodontal disease, tooth loss and colorectal cancer risk: Results from the Nurses' Health Study.

ABSTRACT: Periodontal diseases including tooth loss might increase systemic inflammation, lead to immune dysregulation and alter gut microbiota, thereby possibly influencing colorectal carcinogenesis. Few epidemiological studies have examined the association between periodontal diseases and colorectal cancer (CRC) risk. We collected information on the periodontal disease (defined as history of periodontal bone loss) and number of natural teeth in the Nurses' Health Study. A total of 77,443 women were followed since 1992. We used Cox proportional hazard models to calculate multivariable hazard ratios (HRs) and 95% confidence intervals (95% CIs) after adjustment for smoking and other known risk factors for CRC. We documented 1,165 incident CRC through 2010. Compared to women with 25-32 teeth, the multivariable HR (95% CI) for CRC for women with <17 teeth was 1.20 (1.04-1.39). With regard to tumor site, the HRs (95% CIs) for the same comparison were 1.23 (1.01-1.51) for proximal colon cancer, 1.03 (0.76-1.38) for distal colon cancer and 1.48 (1.07-2.05) for rectal cancer. In addition, compared to those without periodontal disease, HRs for CRC were 0.91 (95% CI 0.74-1.12) for periodontal disease, and 1.22 (95% CI 0.91-1.63) when limited to moderate to severe periodontal disease. The results were not modified by smoking status, body mass index or alcohol consumption. Women with fewer teeth, possibly moderate or severe periodontal disease, might be at a modest increased risk of developing CRC, suggesting a potential role of oral health in colorectal carcinogenesis.

SUBMITTER: Momen-Heravi F

PROVIDER: S-EPMC5159274 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Periodontal disease, tooth loss and colorectal cancer risk: Results from the Nurses' Health Study.

Momen-Heravi Fatemeh F Babic Ana A Tworoger Shelley S SS Zhang Libin L Wu Kana K Smith-Warner Stephanie A SA Ogino Shuji S Chan Andrew T AT Meyerhardt Jeffrey J Giovannucci Edward E Fuchs Charles C Cho Eunyoung E Michaud Dominique S DS Stampfer Meir J MJ Yu Yau-Hua YH Kim David D Zhang Xuehong X

International journal of cancer 20161123 3

Periodontal diseases including tooth loss might increase systemic inflammation, lead to immune dysregulation and alter gut microbiota, thereby possibly influencing colorectal carcinogenesis. Few epidemiological studies have examined the association between periodontal diseases and colorectal cancer (CRC) risk. We collected information on the periodontal disease (defined as history of periodontal bone loss) and number of natural teeth in the Nurses' Health Study. A total of 77,443 women were foll ...[more]

PMID: 27778343

Similar Datasets

Project description:BACKGROUND:Current periodontal disease taxonomies have limited utility for predicting disease progression and tooth loss; in fact, tooth loss itself can undermine precise person-level periodontal disease classifications. To overcome this limitation, the current group recently introduced a novel patient stratification system using latent class analyses of clinical parameters, including patterns of missing teeth. This investigation sought to determine the clinical utility of the Periodontal Profile Classes and Tooth Profile Classes (PPC/TPC) taxonomy for risk assessment, specifically for predicting periodontal disease progression and incident tooth loss. METHODS:The analytic sample comprised 4,682 adult participants of two prospective cohort studies (Dental Atherosclerosis Risk in Communities Study and Piedmont Dental Study) with information on periodontal disease progression and incident tooth loss. The PPC/TPC taxonomy includes seven distinct PPCs (person-level disease pattern and severity) and seven TPCs (tooth-level disease). Logistic regression modeling was used to estimate relative risks (RR) and 95% confidence intervals (CI) for the association of these latent classes with disease progression and incident tooth loss, adjusting for examination center, race, sex, age, diabetes, and smoking. To obtain personalized outcome propensities, risk estimates associated with each participant's PPC and TPC were combined into person-level composite risk scores (Index of Periodontal Risk [IPR]). RESULTS:Individuals in two PPCs (PPC-G: Severe Disease and PPC-D: Tooth Loss) had the highest tooth loss risk (RR = 3.6; 95% CI = 2.6 to 5.0 and RR = 3.8; 95% CI = 2.9 to 5.1, respectively). PPC-G also had the highest risk for periodontitis progression (RR = 5.7; 95% CI = 2.2 to 14.7). Personalized IPR scores were positively associated with both periodontitis progression and tooth loss. CONCLUSIONS:These findings, upon additional validation, suggest that the periodontal/tooth profile classes and the derived personalized propensity scores provide clinical periodontal definitions that reflect disease patterns in the population and offer a useful system for patient stratification that is predictive for disease progression and tooth loss.

Dataset Information

Periodontal disease, tooth loss and colorectal cancer risk: Results from the Nurses' Health Study.

Publications

Periodontal disease, tooth loss and colorectal cancer risk: Results from the Nurses' Health Study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets