10 resultados para case-control study

em Duke University


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BACKGROUND: While smoking is the major cause of chronic obstructive pulmonary disease (COPD), occupational exposures to vapors, gases, dusts, and fumes (VGDF) increase COPD risk. This case-control study estimated the risk of COPD attributable to occupational exposures among construction workers. METHODS: The study population included 834 cases and 1243 controls participating in a national medical screening program for older construction workers between 1997 and 2013. Qualitative exposure indices were developed based on lifetime work and exposure histories. RESULTS: Approximately 18% (95% CI = 2-24%) of COPD risk can be attributed to construction-related exposures, which are additive to the risk contributed by smoking. A measure of all VGDF exposures combined was a strong predictor of COPD risk. CONCLUSIONS: Construction workers are at increased risk of COPD as a result of broad and complex effects of many exposures acting independently or interactively. Control methods should be implemented to prevent worker exposures, and smoking cessation should be promoted.

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Previously developed models for predicting absolute risk of invasive epithelial ovarian cancer have included a limited number of risk factors and have had low discriminatory power (area under the receiver operating characteristic curve (AUC) < 0.60). Because of this, we developed and internally validated a relative risk prediction model that incorporates 17 established epidemiologic risk factors and 17 genome-wide significant single nucleotide polymorphisms (SNPs) using data from 11 case-control studies in the United States (5,793 cases; 9,512 controls) from the Ovarian Cancer Association Consortium (data accrued from 1992 to 2010). We developed a hierarchical logistic regression model for predicting case-control status that included imputation of missing data. We randomly divided the data into an 80% training sample and used the remaining 20% for model evaluation. The AUC for the full model was 0.664. A reduced model without SNPs performed similarly (AUC = 0.649). Both models performed better than a baseline model that included age and study site only (AUC = 0.563). The best predictive power was obtained in the full model among women younger than 50 years of age (AUC = 0.714); however, the addition of SNPs increased the AUC the most for women older than 50 years of age (AUC = 0.638 vs. 0.616). Adapting this improved model to estimate absolute risk and evaluating it in prospective data sets is warranted.

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BACKGROUND: Variation in brain structure is both genetically and environmentally influenced. The question about potential differences in brain anatomy across populations of differing race and ethnicity remains a controversial issue. There are few studies specifically examining racial or ethnic differences and also few studies that test for race-related differences in context of other neuropsychiatric research, possibly due to the underrepresentation of ethnic minorities in clinical research. It is within this context that we conducted a secondary data analysis examining volumetric MRI data from healthy participants and compared the volumes of the amygdala, hippocampus, lateral ventricles, caudate nucleus, orbitofrontal cortex (OFC) and total cerebral volume between Caucasian and African-American participants. We discuss the importance of this finding in context of neuroimaging methodology, but also the need for improved recruitment of African Americans in clinical research and its broader implications for a better understanding of the neural basis of neuropsychiatric disorders. METHODOLOGY/PRINCIPAL FINDINGS: This was a case control study in the setting of an academic medical center outpatient service. Participants consisted of 44 Caucasians and 33 ethnic minorities. The following volumetric data were obtained: amygdala, hippocampus, lateral ventricles, caudate nucleus, orbitofrontal cortex (OFC) and total cerebrum. Each participant completed a 1.5 T magnetic resonance imaging (MRI). Our primary finding in analyses of brain subregions was that when compared to Caucasians, African Americans exhibited larger left OFC volumes (F (1,68) = 7.50, p = 0.008). CONCLUSIONS: The biological implications of our findings are unclear as we do not know what factors may be contributing to these observed differences. However, this study raises several questions that have important implications for the future of neuropsychiatric research.

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Prostate cancer (PC) is the second leading cause of cancer death in men. Recent reports suggest that excess of nutrients involved in the one-carbon metabolism pathway increases PC risk; however, empirical data are lacking. Veteran American men (272 controls and 144 PC cases) who attended the Durham Veteran American Medical Center between 2004-2009 were enrolled into a case-control study. Intake of folate, vitamin B12, B6, and methionine were measured using a food frequency questionnaire. Regression models were used to evaluate the association among one-carbon cycle nutrients, MTHFR genetic variants, and prostate cancer. Higher dietary methionine intake was associated with PC risk (OR = 2.1; 95%CI 1.1-3.9) The risk was most pronounced in men with Gleason sum <7 (OR = 2.75; 95%CI 1.32- 5.73). The association of higher methionine intake and PC risk was only apparent in men who carried at least one MTHFR A1298C allele (OR = 6.7; 95%CI = 1.6-27.8), compared to MTHFR A1298A noncarrier men (OR = 0.9; 95%CI = 0.24-3.92) (p-interaction = 0.045). There was no evidence for associations between B vitamins (folate, B12, and B6) and PC risk. Our results suggest that carrying the MTHFR A1298C variants modifies the association between high methionine intake and PC risk. Larger studies are required to validate these findings.

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BACKGROUND: We analyzed the association between 53 genes related to DNA repair and p53-mediated damage response and serous ovarian cancer risk using case-control data from the North Carolina Ovarian Cancer Study (NCOCS), a population-based, case-control study. METHODS/PRINCIPAL FINDINGS: The analysis was restricted to 364 invasive serous ovarian cancer cases and 761 controls of white, non-Hispanic race. Statistical analysis was two staged: a screen using marginal Bayes factors (BFs) for 484 SNPs and a modeling stage in which we calculated multivariate adjusted posterior probabilities of association for 77 SNPs that passed the screen. These probabilities were conditional on subject age at diagnosis/interview, batch, a DNA quality metric and genotypes of other SNPs and allowed for uncertainty in the genetic parameterizations of the SNPs and number of associated SNPs. Six SNPs had Bayes factors greater than 10 in favor of an association with invasive serous ovarian cancer. These included rs5762746 (median OR(odds ratio)(per allele) = 0.66; 95% credible interval (CI) = 0.44-1.00) and rs6005835 (median OR(per allele) = 0.69; 95% CI = 0.53-0.91) in CHEK2, rs2078486 (median OR(per allele) = 1.65; 95% CI = 1.21-2.25) and rs12951053 (median OR(per allele) = 1.65; 95% CI = 1.20-2.26) in TP53, rs411697 (median OR (rare homozygote) = 0.53; 95% CI = 0.35 - 0.79) in BACH1 and rs10131 (median OR( rare homozygote) = not estimable) in LIG4. The six most highly associated SNPs are either predicted to be functionally significant or are in LD with such a variant. The variants in TP53 were confirmed to be associated in a large follow-up study. CONCLUSIONS/SIGNIFICANCE: Based on our findings, further follow-up of the DNA repair and response pathways in a larger dataset is warranted to confirm these results.

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CD133 is one of the most common stem cell markers, and functional single nucleotide polymorphisms (SNPs) of CD133 may modulate its gene functions and thus cancer risk and patient survival. We hypothesized that potentially functional CD133 SNPs are associated with gastric cancer (GC) risk and survival. To test this hypothesis, we conducted a case-control study of 371 GC patients and 313 cancer-free controls frequency-matched by age, sex, and ethnicity. We genotyped four selected, potentially functional CD133 SNPs (rs2240688A>C, rs7686732C>G, rs10022537T>A, and rs3130C>T) and used logistic regression analysis for associations of these SNPs with GC risk and Cox hazards regression analysis for survival. We found that compared with the miRNA binding site rs2240688 AA genotype, AC + CC genotypes were associated with significantly increased GC risk (adjusted OR = 1.52, 95% CI = 1.09-2.13); for another miRNA binding site rs3130C>T SNP, the TT genotype was associated with significantly reduced GC risk (adjusted OR = 0.68, 95% CI = 0.48-0.97), compared with CC + CT genotypes. In all patients, the risk rs3130 TT variant genotype was significantly associated with overall survival (OS) (adjusted P(trend) = 0.016 and 0.007 under additive and recessive models, respectively). These findings suggest that these two CD133 miRNA binding site variants, rs2240688 and rs3130, may be potential biomarkers for genetic susceptibility to GC and possible predictors for survival in GC patients but require further validation by larger studies.

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This chapter presents a model averaging approach in the M-open setting using sample re-use methods to approximate the predictive distribution of future observations. It first reviews the standard M-closed Bayesian Model Averaging approach and decision-theoretic methods for producing inferences and decisions. It then reviews model selection from the M-complete and M-open perspectives, before formulating a Bayesian solution to model averaging in the M-open perspective. It constructs optimal weights for MOMA:M-open Model Averaging using a decision-theoretic framework, where models are treated as part of the ‘action space’ rather than unknown states of nature. Using ‘incompatible’ retrospective and prospective models for data from a case-control study, the chapter demonstrates that MOMA gives better predictive accuracy than the proxy models. It concludes with open questions and future directions.

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BACKGROUND: Curcumin is a natural product that is often explored by patients with cancer. Weight loss due to fat and muscle depletion is a hallmark of pancreatic cancer and is associated with worse outcomes. Studies of curcumin's effects on muscularity show conflicting results in animal models. METHODS AND RESULTS: Retrospective matched 1:2 case-control study to evaluate the effects of curcumin on body composition (determined by computerized tomography) of 66 patients with advanced pancreatic cancer (22 treated,44 controls). Average age (SEM) was 63(1.8) years, 30/66(45%) women, median number of prior therapies was 2, median (IQR) time from advanced pancreatic cancer diagnosis to baseline image was 7(2-13.5) months (p>0.2, all variables). All patients lost weight (3.3% and 1.3%, treated vs. control, p=0.13). Treated patients lost more muscle (median [IQR] percent change -4.8[-9.1,-0.1] vs. -0.05%[-4.2, 2.6] in controls,p<0.001) and fat (median [IQR] percent change -6.8%[-15,-0.6] vs. -4.0%[-7.6, 1.3] in controls,p=0.04). Subcutaneous fat was more affected in the treated patients. Sarcopenic patients treated with curcumin(n=15) had survival of 169(115-223) days vs. 299(229-369) sarcopenic controls(p=0.024). No survival difference was found amongst non-sarcopenic patients. CONCLUSIONS: Patients with advanced pancreatic cancer treated with curcumin showed significantly greater loss of subcutaneous fat and muscle than matched untreated controls.

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Insecticide treated bed nets and indoor residual spraying are the most widely used vector control methods in Africa. The World Health Organization now recommends four classes of insecticides for use against adult mosquitoes in public health programs. Of these four classes of insecticides, pyrethroids have become the insecticides of choice in treating mosquito bed nets and in the use of indoor spraying to prevent malaria transmission. Pyrethroids are not only used in malaria control but also in agriculture to protect against pest insects. This concurrent use of pyrethroids in vector control and protection of crops from pests in agriculture may exert selection pressure on mosquito larval population and induce resistance to this class of insecticides. The main objective of our study was to explore the role of agricultural chemicals and the response of mosquitoes to pyrethroids in an area of high malaria transmission.

We used a cross-sectional study design. This was a two-step study involving both mosquitoes and human subjects. In this study, we collected larvae growing in breeding sites affected by different agricultural practices. We used purposive sampling to identify active mosquito breeding sites and then interviewed households adjacent to those breeding sites to learn about their agricultural practices that might influence the response of mosquitoes to pyrethroids. We also performed secondary analysis of larval data from a previous case-control study by Obala et al.

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Several studies have reported that cigarette smoking is inversely associated with the risk of melanoma. This study further tested whether incorporating genetic factors will provide another level of evaluation of mechanisms underlying the association between smoking and risk of melanoma. We investigated the association between SNPs selected from genome-wide association studies (GWAS) on smoking behaviors and risk of melanoma using 2,298 melanoma cases and 6,654 controls. Among 16 SNPs, three (rs16969968 [A], rs1051730 [A] and rs2036534 [C] in the 15q25.1 region) reached significance for association with melanoma risk in men (0.01 < = P values < = 0.02; 0.85 < = Odds Ratios (ORs) <= 1.20). There was association between the genetic scores based on the number of smoking behavior-risk alleles and melanoma risk with P-trend = 0.005 among HPFS. Further association with smoking behaviors indicating those three SNPs (rs16969968 [A], rs1051730 [A] and rs2036534 [C]) significantly associated with number of cigarettes smoked per day, CPD, with P = 0.009, 0.011 and 0.001 respectively. The SNPs rs215605 in the PDE1C gene and rs6265 in the BDNF gene significantly interacted with smoking status on melanoma risk (interaction P = 0.005 and P = 0.003 respectively). Our study suggests that smoking behavior-related SNPs are likely to play a role in melanoma development and the potential public health importance of polymorphisms in the CHRNA5-A3-B4 gene cluster. Further larger studies are warranted to validate the findings.