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Periodontology 2000 Jun 2020Epidemiologic and cancer control studies on the association of periodontal disease and cancer risk mostly suggest a positive association with overall cancer risk and... (Review)
Review
Epidemiologic and cancer control studies on the association of periodontal disease and cancer risk mostly suggest a positive association with overall cancer risk and certain specific types of cancer. These findings are generally consistent among cross-sectional and longitudinal studies. In this paper, we review epidemiologic studies and current knowledge on periodontal disease and cancer, with a focus on those studies conducted in the years following the Joint European Federation of Periodontology/American Academy of Periodontology Workshop on "Periodontitis and Systemic Diseases" in November 2012. This review also explores the role of chronic inflammation as a biologically plausible mechanistic link between periodontal disease and risk of cancer. Furthermore, it highlights studies that have examined the potential importance of certain periodontal pathogens in this association.
Topics: Cross-Sectional Studies; Humans; Neoplasms; Periodontal Diseases; Periodontics; Periodontitis
PubMed: 32385885
DOI: 10.1111/prd.12329 -
Environmental Research Mar 2021The number of studies addressing per- and polyfluoroalkyl substances (PFAS) and cancer is increasing. Many communities have had water contaminated by PFAS, and cancer is... (Review)
Review
BACKGROUND
The number of studies addressing per- and polyfluoroalkyl substances (PFAS) and cancer is increasing. Many communities have had water contaminated by PFAS, and cancer is one of the important community concerns related to PFAS exposure.
OBJECTIVES
We critically reviewed the evidence relating to PFAS and cancer from an epidemiologic standpoint to highlight directions for future research that would be the most likely to meaningfully increase knowledge.
METHODS
We conducted a search in PubMed for studies of cancer and PFAS (through 9/20/2020). We identified epidemiologic studies that provided a quantitative estimate for some measure of the association between PFAS and cancer. Here, we review that literature, including several aspects of epidemiologic study design that impact the usefulness of study results.
RESULTS
We identified 16 cohort (or case-cohort) studies, 10 case-control studies (4 nested within cohorts and 6 non-nested), 1 cross sectional study and 1 ecologic study. The cancer sites with the most evidence of an association with PFAS are testicular and kidney cancer. There are also some suggestions in a few studies of an association with prostate cancer, but the data are inconsistent.
DISCUSSION
Each study's design has strengths and limitations. Weaknesses in study design and methods can, in some cases, lead to questionable associations, but in other cases can make it more difficult to detect true associations, if they are present. Overall, the evidence for an association between cancer and PFAS remains sparse. A variety of studies with different strengths and weaknesses can be helpful to clarify associations between PFAS and cancer. Long term follow-up of large-sized cohorts with large exposure contrasts are most likely to be informative.
Topics: Alkanesulfonic Acids; Case-Control Studies; Cross-Sectional Studies; Environmental Pollutants; Fluorocarbons; Humans; Kidney Neoplasms; Male; Water
PubMed: 33385391
DOI: 10.1016/j.envres.2020.110690 -
Respiratory Care Oct 2004A retrospective study uses existing data that have been recorded for reasons other than research. A retrospective case series is the description of a group of cases with...
A retrospective study uses existing data that have been recorded for reasons other than research. A retrospective case series is the description of a group of cases with a new or unusual disease or treatment. With a case-control study, cases with and without the condition of interest are identified, and the degree of exposure to a possible risk factor is then retrospectively compared between the 2 groups. With a matched case-control study, control subjects are selected such that they resemble (match) the cases with regards to certain characteristics (eg, age, comorbidity, severity of disease). Retrospective study designs are generally considered inferior to prospective study designs. Therefore, a retrospective study design should never be used when a prospective design is feasible.
Topics: Case-Control Studies; Epidemiologic Studies; Humans; Retrospective Studies
PubMed: 15447798
DOI: No ID Found -
International Journal of Epidemiology Feb 2017Interrupted time series (ITS) analysis is a valuable study design for evaluating the effectiveness of population-level health interventions that have been implemented at...
Interrupted time series (ITS) analysis is a valuable study design for evaluating the effectiveness of population-level health interventions that have been implemented at a clearly defined point in time. It is increasingly being used to evaluate the effectiveness of interventions ranging from clinical therapy to national public health legislation. Whereas the design shares many properties of regression-based approaches in other epidemiological studies, there are a range of unique features of time series data that require additional methodological considerations. In this tutorial we use a worked example to demonstrate a robust approach to ITS analysis using segmented regression. We begin by describing the design and considering when ITS is an appropriate design choice. We then discuss the essential, yet often omitted, step of proposing the impact model a priori. Subsequently, we demonstrate the approach to statistical analysis including the main segmented regression model. Finally we describe the main methodological issues associated with ITS analysis: over-dispersion of time series data, autocorrelation, adjusting for seasonal trends and controlling for time-varying confounders, and we also outline some of the more complex design adaptations that can be used to strengthen the basic ITS design.
Topics: Epidemiologic Studies; Humans; Interrupted Time Series Analysis; Public Health; Research Design
PubMed: 27283160
DOI: 10.1093/ije/dyw098 -
BMC Medical Research Methodology Oct 2021Mediation analysis methodology underwent many advancements throughout the years, with the most recent and important advancement being the development of causal mediation... (Review)
Review
BACKGROUND
Mediation analysis methodology underwent many advancements throughout the years, with the most recent and important advancement being the development of causal mediation analysis based on the counterfactual framework. However, a previous review showed that for experimental studies the uptake of causal mediation analysis remains low. The aim of this paper is to review the methodological characteristics of mediation analyses performed in observational epidemiologic studies published between 2015 and 2019 and to provide recommendations for the application of mediation analysis in future studies.
METHODS
We searched the MEDLINE and EMBASE databases for observational epidemiologic studies published between 2015 and 2019 in which mediation analysis was applied as one of the primary analysis methods. Information was extracted on the characteristics of the mediation model and the applied mediation analysis method.
RESULTS
We included 174 studies, most of which applied traditional mediation analysis methods (n = 123, 70.7%). Causal mediation analysis was not often used to analyze more complicated mediation models, such as multiple mediator models. Most studies adjusted their analyses for measured confounders, but did not perform sensitivity analyses for unmeasured confounders and did not assess the presence of an exposure-mediator interaction.
CONCLUSIONS
To ensure a causal interpretation of the effect estimates in the mediation model, we recommend that researchers use causal mediation analysis and assess the plausibility of the causal assumptions. The uptake of causal mediation analysis can be enhanced through tutorial papers that demonstrate the application of causal mediation analysis, and through the development of software packages that facilitate the causal mediation analysis of relatively complicated mediation models.
Topics: Causality; Epidemiologic Studies; Humans; Mediation Analysis; Models, Statistical; Observational Studies as Topic; Research Design
PubMed: 34689754
DOI: 10.1186/s12874-021-01426-3 -
Epidemiology (Cambridge, Mass.) May 2017The author proposes that epidemiologic studies should more often assess the associations of a single exposure with multiple outcomes simultaneously. Such "outcome-wide...
The author proposes that epidemiologic studies should more often assess the associations of a single exposure with multiple outcomes simultaneously. Such "outcome-wide epidemiology" will be especially important for exposures that may be beneficial for some outcomes but harmful for others. Outcome-wide epidemiology may also be helpful in prioritizing public health recommendations. Methodologically, the conduct of outcome-wide epidemiology will generally be more straightforward than recent proposals for exposure-wide epidemiologic studies, in which the associations between a single outcome and many exposures are assessed simultaneously. Such exposure-wide studies are likely to be subject to numerous biases because of the inability to make simultaneous confounding control and because exposures are likely to affect, and mediate the effects of, other exposures. These problems simplify considerably in an outcome-wide approach when a single exposure is being considered. Moreover, outcome-wide approaches will generally be more useful than exposure-wide approaches in shaping public health recommendations.
Topics: Bias; Epidemiologic Methods; Epidemiologic Studies; Humans; Outcome Assessment, Health Care; Public Health
PubMed: 28166102
DOI: 10.1097/EDE.0000000000000641 -
Journal of Epidemiology and Community... Jul 2006In ideal randomised experiments, association is causation: association measures can be interpreted as effect measures because randomisation ensures that the exposed and...
In ideal randomised experiments, association is causation: association measures can be interpreted as effect measures because randomisation ensures that the exposed and the unexposed are exchangeable. On the other hand, in observational studies, association is not generally causation: association measures cannot be interpreted as effect measures because the exposed and the unexposed are not generally exchangeable. However, observational research is often the only alternative for causal inference. This article reviews a condition that permits the estimation of causal effects from observational data, and two methods -- standardisation and inverse probability weighting -- to estimate population causal effects under that condition. For simplicity, the main description is restricted to dichotomous variables and assumes that no random error attributable to sampling variability exists. The appendix provides a generalisation of inverse probability weighting.
Topics: Causality; Confounding Factors, Epidemiologic; Data Interpretation, Statistical; Effect Modifier, Epidemiologic; Epidemiologic Research Design; Epidemiologic Studies; Humans; Probability; Research Design
PubMed: 16790829
DOI: 10.1136/jech.2004.029496 -
Steroids Jul 2015Early epidemiologic studies of estrogen metabolism measured only 2-hydroxyestrone and 16α-hydroxyestrone and relied on direct enzyme immunoassays without purification... (Review)
Review
Early epidemiologic studies of estrogen metabolism measured only 2-hydroxyestrone and 16α-hydroxyestrone and relied on direct enzyme immunoassays without purification steps. Eight breast cancer studies have used these assays with prospectively collected blood or urine samples. Results were inconsistent, and generally not statistically significant; but the assays had limited specificity, especially at the low concentrations characteristic of postmenopausal women. To facilitate continued testing in population-based studies of the multiple laboratory-based hypotheses about the roles of estrogen metabolites, a novel liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay was developed to measure concurrently all 15 estrogens and estrogen metabolites in human serum and urine, as unconjugated and total (glucuronidated+sulfated+unconjugated) concentrations. The assay has high sensitivity (lower limit of quantitation ∼1-2 pmol/L), reproducibility (coefficients of variation generally ⩽5%), and accuracy. Three prospective studies utilizing this comprehensive assay have demonstrated that enhanced 2-hydroxylation of parent estrogens (estrone+estradiol) is associated with reduced risk of postmenopausal breast cancer. In the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO) cohort, the serum ratio of 2-hydroxylation pathway metabolites to parent estrogens was associated with a 28% reduction in breast cancer risk across extreme deciles (p-trend=.05), after adjusting for unconjugated estradiol and breast cancer risk factors. Incorporating this ratio into a risk prediction model already including unconjugated estradiol improved absolute risk estimates substantially (by ⩾14%) in 36% of the women, an encouraging result that needs replication. Additional epidemiologic studies of the role of estrogen metabolism in the etiology of hormone-related diseases and continued improvement of estrogen metabolism assays are justified.
Topics: Breast Neoplasms; Chromatography, Liquid; Epidemiologic Studies; Estrogens; Female; Humans; Hydroxyestrones; Postmenopause; Premenopause; Prospective Studies; Risk Factors; Tandem Mass Spectrometry
PubMed: 25725255
DOI: 10.1016/j.steroids.2015.02.015 -
Annals of Work Exposures and Health Jul 2023Computer-assisted coding of job descriptions to standardized occupational classification codes facilitates evaluating occupational risk factors in epidemiologic studies...
OBJECTIVES
Computer-assisted coding of job descriptions to standardized occupational classification codes facilitates evaluating occupational risk factors in epidemiologic studies by reducing the number of jobs needing expert coding. We evaluated the performance of the 2nd version of SOCcer, a computerized algorithm designed to code free-text job descriptions to US SOC-2010 system based on free-text job titles and work tasks, to evaluate its accuracy.
METHODS
SOCcer v2 was updated by expanding the training data to include jobs from several epidemiologic studies and revising the algorithm to account for nonlinearity and incorporate interactions. We evaluated the agreement between codes assigned by experts and the highest scoring code (a measure of confidence in the algorithm-predicted assignment) from SOCcer v1 and v2 in 14,714 jobs from three epidemiology studies. We also linked exposure estimates for 258 agents in the job-exposure matrix CANJEM to the expert and SOCcer v2-assigned codes and compared those estimates using kappa and intraclass correlation coefficients. Analyses were stratified by SOCcer score, score distance between the top two scoring codes from SOCcer, and features from CANJEM.
RESULTS
SOCcer's v2 agreement at the 6-digit level was 50%, compared to 44% in v1, and was similar for the three studies (38%-45%). Overall agreement for v2 at the 2-, 3-, and 5-digit was 73%, 63%, and 56%, respectively. For v2, median ICCs for the probability and intensity metrics were 0.67 (IQR 0.59-0.74) and 0.56 (IQR 0.50-0.60), respectively. The agreement between the expert and SOCcer assigned codes linearly increased with SOCcer score. The agreement also improved when the top two scoring codes had larger differences in score.
CONCLUSIONS
Overall agreement with SOCcer v2 applied to job descriptions from North American epidemiologic studies was similar to the agreement usually observed between two experts. SOCcer's score predicted agreement with experts and can be used to prioritize jobs for expert review.
Topics: Humans; Job Description; Soccer; Occupational Exposure; Epidemiologic Studies; Algorithms
PubMed: 37071789
DOI: 10.1093/annweh/wxad020 -
Frontiers in Public Health 2020Peak exposures are of concern because they can potentially overwhelm normal defense mechanisms and induce adverse health effects. Metrics of peak exposure have been used... (Review)
Review
Peak exposures are of concern because they can potentially overwhelm normal defense mechanisms and induce adverse health effects. Metrics of peak exposure have been used in epidemiologic and exposure studies, but consensus is lacking on its definition. The relevant characteristics of peak exposure are dependent upon exposure patterns, biokinetics of exposure, and disease mechanisms. The objective of this review was to summarize the use of peak metrics in epidemiologic and exposure studies. A comprehensive search of Medline, Embase, Web of Science, and NIOSHTIC-2 databases was conducted using keywords related to peak exposures. The retrieved references were reviewed and selected for indexing if they included a peak metric and met additional criteria. Information on health outcomes and peak exposure metrics was extracted from each reference. A total of 1,215 epidemiologic or exposure references were identified, of which 182 were indexed and summarized. For the 72 epidemiologic studies, the health outcomes most frequently evaluated were: chronic respiratory effects, cancer and acute respiratory symptoms. Exposures were frequently assessed using task-based and full-shift time-integrated methods, qualitative methods, and real-time instruments. Peak exposure summary metrics included the presence or absence of a peak event, highest exposure intensity and frequency greater than a target. Peak metrics in the 110 exposure studies most frequently included highest exposure intensity, average short-duration intensity, and graphical presentation of the real-time data (plots). This review provides a framework for considering biologically relevant peak exposure metrics for epidemiologic and exposure studies to help inform risk assessment and exposure mitigation.
Topics: Benchmarking; Epidemiologic Studies; Inhalation Exposure; Risk Assessment
PubMed: 33490023
DOI: 10.3389/fpubh.2020.611693