Covariates of high-risk human papillomavirus (HPV) infections are distinct for incident CIN1, CIN2 and CIN3 as disclosed by competing-risks regression models

Background: In addition to the oncogenic human papillomavirus (HPV), several cofactors are needed in cervical carcinogenesis, but whether the HPV covariates associated with incident i) CIN1 are different from those of incident ii) CIN2 and iii) CIN3 needs further assessment. Objectives: To gain further insights into the true biological differences between CIN1, CIN2 and CIN3, we assessed HPV covariates associated with incident CIN1, CIN2, and CIN3. Study Design and Methods: HPV covariates associated with progression to CIN1, CIN2 and CIN3 were analysed in the combined cohort of the NIS (n = 3,187) and LAMS study (n = 12,114), using competing-risks regression models (in panel data) for baseline HR-HPV-positive women (n = 1,105), who represent a sub-cohort of all 1,865 women prospectively followed-up in these two studies. Results: Altogether, 90 (4.8%), 39 (2.1%) and 14 (1.4%) cases progressed to CIN1, CIN2, and CIN3, respectively. Among these baseline HR-HPV-positive women, the risk profiles of incident GIN I, CIN2 and CIN3 were unique in that completely different HPV covariates were associated with progression to CIN1, CIN2 and CIN3, irrespective which categories (non-progression, CIN1, CIN2, CIN3 or all) were used as competing-risks events in univariate and multivariate models. Conclusions: These data confirm our previous analysis based on multinomial regression models implicating that distinct covariates of HR-HPV are associated with progression to CIN1, CIN2 and CIN3. This emphasises true biological differences between the three grades of GIN, which revisits the concept of combining CIN2 with CIN3 or with CIN1 in histological classification or used as a common end-point, e.g., in HPV vaccine trials.

Potent Antiretroviral Therapy for Human Immunodeficiency Virus Infection Increases Aortic Stiffness

Background: Highly active antiretroviral therapy for AIDS is known to increase cardiovascular risk, but the effects of potent antiretroviral agents according to gender are unknown. Objective: The present study evaluated the impact of HIV infection treatment on aortic stiffness according to gender. Methods: From university-affiliated hospitals, we recruited 28 AIDS patients undergoing highly active antiretroviral treatment (HAART), 28 treatment-naive HIV-infected patients, 44 patients with type 2 diabetes, and 30 controls. Aortic stiffness was determined by measuring pulse wave velocity (PWV) using a validated and non-invasive automatic device. Results: The crude mean PWV values and 95% confidence intervals (95% CI) for HAART, diabetics, and controls were 9.77 m/s (95% CI 9.17-10.36),, 9.00 m/s (95% CI 8.37-9.63), 9.90 m/s (95% CI 9.32-10.49), and 9.28 m/s (95% CI 8.61-9.95), respectively, for men (P-value for trend = 0.14), and 9.61 m/s (95% CI 8.56-10.66), 8.45 m/s (95% CI 7.51-9.39), 9.83 (95% CI 9.21-10.44), and 7.79 m/s (95% CI 6.99-8.58), respectively, for women (P-value for trend <0.001). Post-hoc analysis revealed a significant difference between the mean PWV values in the HAART group and controls in women (P-value <0.01). After adjusting for other potential covariates, including systolic blood pressure and diabetes, these results did not change. The findings indicate that the impact of HAART treatment on aortic stiffness was amplified in women with hypertension, dyslipidemia, and metabolic syndrome. Conclusion: Potent anti-retroviral agents used in the treatment of HIV infection increases aortic stiffness, mainly among women with higher cardiovascular risk. (Arq Bras Cardiol 2012;99(6):1100-1107)

Thioredoxin interacting protein genetic variation is associated with diabetes and hypertension in the Brazilian general population

Objective: To investigate the relationship between TXNIP polymorphisms, diabetes and hypertension phenotypes in the Brazilian general population. Methods: Five hundred seventy-six individuals randomly selected from the general urban population according to the MONICA-WHO project guidelines were phenotyped for cardiovascular risk factors. A second, independent, sample composed of 487 family-trios from a different site was also selected. Nine TXNIP polymorphisms were studied. The potential association between TXNIP variability and glucose-phenotypes in children was also explored. TXNIP expression was quantified by real-time PCR in 53 samples from human smooth muscle cells primary culture. Results: TXNIP rs7211 and rs7212 polymorphisms were significantly associated with glucose and blood pressure related phenotypes. In multivariate logistic regression models the studied markers remained associated with diabetes even after adjustment for covariates. TXNIP rs7211 T/rs7212 G haplotype (present in approximately 17% of individuals) was significantly associated to diabetes in both samples. In children, the TXNIP rs7211 T/rs7212 G haplotype was associated with fasting insulin concentrations. Finally, cells harboring TXNIP rs7212 G allele presented higher TXNIP expression levels compared with carriers of TXNIP rs7212 CC genotype (p = 0.02). Conclusion: Carriers of TXNIP genetic variants presented higher TXNIP expression, early signs of glucose homeostasis derangement and increased susceptibility to chronic metabolic conditions such as diabetes and hypertension. Our data suggest that genetic variation in the TXNIP gene may act as a "common ground" modulator of both traits: diabetes and hypertension. (C) 2011 Elsevier Ireland Ltd. All rights reserved.

Longitudinal outcomes of high-risk human papillomavirus (HPV) infections as competing-risks events following cervical HPV test at baseline visit in the *NIS-LAMS** cohort

Background: The complex natural history of human papillomavirus (HPV) infections following a single HPV test can be modeled as competing-risks events (i.e., no-, transient- or persistent infection) in a longitudinal setting. The covariates associated with these compet ng events have not been previously assessed using competing-risks regression models. Objectives: To gain further insights in the outcomes of cervical HPV infections, we used univariate- and multivariate competing-risks regression models to assess the covariaies associated with these competing events. Study Design and Methods: Covariates associated with three competing outcomes (no-, transient- or persistent HR-HPV infection) were analysed in a sub-cohort of 1,865 women prospectively followed-up in the NIS (n = 3,187) and LAMS Study (n = 12,114). Results: In multivariate competing-risks models (with two other outcomes as competing events), permanently HR-HPV negative outcome was significantly predicted only by the clearance of ASCUS+Pap during FU, while three independent covariates predicted transient HR-HPV infections: i) number of recent (< 12 months) sexual partners (risk increased), ii) previous Pap screening history (protective), and history of previous CIN (increased risk). The two most powerful predictors of persistent HR-HPV infections were persistent ASCUS+Pap (risk increased), and previous Pap screening history (protective). In pair-wise comparisons, number of recent sexual partners and previous CIN history increase the probability of transient HR-HPV infection against the HR-HPV negative competing event, while previous Pap screening history is protective. Persistent ASCUS+Pap during FU and no previous Pap screening history are significantly associated with the persistent HR-HPV outcome (compared both with i) always negative, and ii) transient events), whereas multiparity is protective. Conclusions: Different covariates are associated with the three main outcomes of cervical HPV infections. The most significant covariates of each competing events are probably distinct enough to enable constructing of a risk-profile for each main outcome.

A multiple time scale survival model with a cure fraction

Many recent survival studies propose modeling data with a cure fraction, i.e., data in which part of the population is not susceptible to the event of interest. This event may occur more than once for the same individual (recurrent event). We then have a scenario of recurrent event data in the presence of a cure fraction, which may appear in various areas such as oncology, finance, industries, among others. This paper proposes a multiple time scale survival model to analyze recurrent events using a cure fraction. The objective is analyzing the efficiency of certain interventions so that the studied event will not happen again in terms of covariates and censoring. All estimates were obtained using a sampling-based approach, which allows information to be input beforehand with lower computational effort. Simulations were done based on a clinical scenario in order to observe some frequentist properties of the estimation procedure in the presence of small and moderate sample sizes. An application of a well-known set of real mammary tumor data is provided.

The Poisson-exponential regression model under different latent activation schemes

In this paper, a new family of survival distributions is presented. It is derived by considering that the latent number of failure causes follows a Poisson distribution and the time for these causes to be activated follows an exponential distribution. Three different activation schemes are also considered. Moreover, we propose the inclusion of covariates in the model formulation in order to study their effect on the expected value of the number of causes and on the failure rate function. Inferential procedure based on the maximum likelihood method is discussed and evaluated via simulation. The developed methodology is illustrated on a real data set on ovarian cancer.

Estimation methods of non-additive effects for characteristics of weight and scrotal circumference in crossbred beef cattle

The objective of this study was to investigate, in a population of crossbred cattle, the obtainment of the non-additive genetic effects for the characteristics weight at 205 and 390 days and scrotal circumference, and to evaluate the consideration of these effects in the prediction of breeding values of sires using different estimation methodologies. In method 1, the data were pre-adjusted for the non-additive effects obtained by least squares means method in a model that considered the direct additive, maternal and non-additive fixed genetic effects, the direct and total maternal heterozygosities, and epistasis. In method 2, the non-additive effects were considered covariates in genetic model. Genetic values for adjusted and non-adjusted data were predicted considering additive direct and maternal effects, and for weight at 205 days, also the permanent environmental effect, as random effects in the model. The breeding values of the categories of sires considered for the weight characteristic at 205 days were organized in files, in order to verify alterations in the magnitude of the predictions and ranking of animals in the two methods of correction data for the non-additives effects. The non-additive effects were not similar in magnitude and direction in the two estimation methods used, nor for the characteristics evaluated. Pearson and Spearman correlations between breeding values were higher than 0.94, and the use of different methods does not imply changes in the selection of animals.

Mayaro Virus Infection in Amazonia: A Multimodel Inference Approach to Risk Factor Assessment

Background: Arboviral diseases are major global public health threats. Yet, our understanding of infection risk factors is, with a few exceptions, considerably limited. A crucial shortcoming is the widespread use of analytical methods generally not suited for observational data - particularly null hypothesis-testing (NHT) and step-wise regression (SWR). Using Mayaro virus (MAYV) as a case study, here we compare information theory-based multimodel inference (MMI) with conventional analyses for arboviral infection risk factor assessment. Methodology/Principal Findings: A cross-sectional survey of anti-MAYV antibodies revealed 44% prevalence (n = 270 subjects) in a central Amazon rural settlement. NHT suggested that residents of village-like household clusters and those using closed toilet/latrines were at higher risk, while living in non-village-like areas, using bednets, and owning fowl, pigs or dogs were protective. The "minimum adequate" SWR model retained only residence area and bednet use. Using MMI, we identified relevant covariates, quantified their relative importance, and estimated effect-sizes (beta +/- SE) on which to base inference. Residence area (beta(Village) = 2.93 +/- 0.41; beta(Upland) = -0.56 +/- 0.33, beta(Riverbanks) = -2.37 +/- 0.55) and bednet use (beta = -0.95 +/- 0.28) were the most important factors, followed by crop-plot ownership (beta = 0.39 +/- 0.22) and regular use of a closed toilet/latrine (beta = 0.19 +/- 0.13); domestic animals had insignificant protective effects and were relatively unimportant. The SWR model ranked fifth among the 128 models in the final MMI set. Conclusions/Significance: Our analyses illustrate how MMI can enhance inference on infection risk factors when compared with NHT or SWR. MMI indicates that forest crop-plot workers are likely exposed to typical MAYV cycles maintained by diurnal, forest dwelling vectors; however, MAYV might also be circulating in nocturnal, domestic-peridomestic cycles in village-like areas. This suggests either a vector shift (synanthropic mosquitoes vectoring MAYV) or a habitat/habits shift (classical MAYV vectors adapting to densely populated landscapes and nocturnal biting); any such ecological/adaptive novelty could increase the likelihood of MAYV emergence in Amazonia.

Is the food frequency consumption essential as covariate to estimate usual intake of episodically consumed foods?

BACKGROUNDS/OBJECTIVES: The aim of this paper is to verify the performance of the frequency of consumption as variable for prediction of the usual intakes of foods. SUBJECTS/METHODS: In total, 725 individuals who answered two nonconsecutive 24-h recall and one food frequency questionnaire (FFQ) in the 'Healthy Survey-Sao Paulo-Brazil'. An additional indicator variable indicating if one is usual consumer was created before analyzing. The Multiple Source Method and National Cancer Institute method were used to estimate usual intake of selected food considering different models of prediction: with no covariates; with FFQ; with FFQ plus indicator variable; and with only indicator variable. RESULTS: For foods that are consumed every day or almost every day, the inclusion of the FFQ and/or the indicator variable as covariates resulted in similar percentiles of consumption when compared with the model with no covariates. For episodically consumed foods, the models with FFQ plus indicator variable and with only indicator variable estimated similar percentiles of intake. CONCLUSIONS: The use of the indicator variable instead the FFQ appears as a good alternative to estimate usual intake of episodically consumed foods.

Can Roads Be Used as Transects for Primate Population Surveys?

Line transect distance sampling (LTDS) can be applied to either trails or roads. However, it is likely that sampling along roads might result in biased density estimates. In this paper, we compared the results obtained with LTDS applied on trails and roads for two primate species (Callithrix penicillata and Callicebus nigrifrons) to clarify whether roads are appropriate transects to estimate densities. We performed standard LTDS surveys in two nature reserves in south-eastern Brazil. Effective strip width and population density were different between trails and roads for C. penicillata, but not for C. nigrifrons. The results suggest that roads are not appropriate for use as transects in primate surveys, at least for some species. Further work is required to fully understand this issue, but in the meantime we recommend that researchers avoid using roads as transects or treat roads and trails as covariates when sampling on roads is unavoidable. Copyright (C) 2012 S. Karger AG, Basel

A General Latent Class Model for Performance Evaluation of Diagnostic Tests in the Absence of a Gold Standard: An Application to Chagas Disease

We propose a new general Bayesian latent class model for evaluation of the performance of multiple diagnostic tests in situations in which no gold standard test exists based on a computationally intensive approach. The modeling represents an interesting and suitable alternative to models with complex structures that involve the general case of several conditionally independent diagnostic tests, covariates, and strata with different disease prevalences. The technique of stratifying the population according to different disease prevalence rates does not add further marked complexity to the modeling, but it makes the model more flexible and interpretable. To illustrate the general model proposed, we evaluate the performance of six diagnostic screening tests for Chagas disease considering some epidemiological variables. Serology at the time of donation (negative, positive, inconclusive) was considered as a factor of stratification in the model. The general model with stratification of the population performed better in comparison with its concurrents without stratification. The group formed by the testing laboratory Biomanguinhos FIOCRUZ-kit (c-ELISA and rec-ELISA) is the best option in the confirmation process by presenting false-negative rate of 0.0002% from the serial scheme. We are 100% sure that the donor is healthy when these two tests have negative results and he is chagasic when they have positive results.

MYLIP p.N342S polymorphism is not associated with lipid profile in the Brazilian population

Background: A recent study investigated the MYLIP region in the Mexican population in order to fine-map the actual susceptibility variants of this locus. The p.N342S polymorphism was identified as the underlying functional variant accounting for one of the previous signals of genome-wide association studies and the N342 allele was associated with higher cholesterol concentrations in Mexican dyslipidemic individuals. To date, there is no further evaluation on this genotype-phenotype association in the literature. In this scenario, and because of a possible pharmacotherapeutic target of dyslipidemia, the main aim of this study was to assess the influence of the MYLIP p.N342S polymorphism on lipid profile in Brazilian individuals. Methods: 1295 subjects of the general population and 1425 consecutive patients submitted to coronary angiography were selected. General characteristics, biochemical tests, blood pressures, pulse wave velocity, and coronary artery disease scores were analyzed. Genotypes for the MYLIP rs9370867 (p.N342S, c.G1025A) polymorphism were detected by high resolution melting analysis. Results: No association of the MYLIP rs9370867 genotypes with lipid profile, hemodynamic data, and coronary angiographic data was found. Analysis stratified by hyperlipidemia, gender, and ethnicity was also performed and the sub-groups presented similar results. In both general population and patient samples, the MYLIP rs9370867 polymorphism was differently distributed according to ethnicity. In the general population, subjects carrying GG genotypes had higher systolic blood pressure (BP), diastolic BP, and mean BP values (129.0 +/- 23.3; 84.9 +/- 14.6; 99.5 +/- 16.8 mmHg) compared with subjects carrying AA genotypes (123.7 +/- 19.5; 81.6 +/- 11.8; 95.6 +/- 13.6 mmHg) (p = 0.01; p = 0.02; p = 0.01, respectively), even after adjustment for covariates. However, in analysis stratified by ethnicity, this finding was not found and there is no evidence that the polymorphism influences BP. Conclusion: Our findings indicate that association studies involving this MYLIP variant can present distinct results according to the studied population. In this moment, further studies are needed to reaffirm if the MYLIP p.N342S polymorphism is functional or not, and to identify other functional markers within this gene.

Survival Analysis of Patients with Heart Failure: Implications of Time-Varying Regression Effects in Modeling Mortality

Background: Several models have been designed to predict survival of patients with heart failure. These, while available and widely used for both stratifying and deciding upon different treatment options on the individual level, have several limitations. Specifically, some clinical variables that may influence prognosis may have an influence that change over time. Statistical models that include such characteristic may help in evaluating prognosis. The aim of the present study was to analyze and quantify the impact of modeling heart failure survival allowing for covariates with time-varying effects known to be independent predictors of overall mortality in this clinical setting. Methodology: Survival data from an inception cohort of five hundred patients diagnosed with heart failure functional class III and IV between 2002 and 2004 and followed-up to 2006 were analyzed by using the proportional hazards Cox model and variations of the Cox's model and also of the Aalen's additive model. Principal Findings: One-hundred and eighty eight (188) patients died during follow-up. For patients under study, age, serum sodium, hemoglobin, serum creatinine, and left ventricular ejection fraction were significantly associated with mortality. Evidence of time-varying effect was suggested for the last three. Both high hemoglobin and high LV ejection fraction were associated with a reduced risk of dying with a stronger initial effect. High creatinine, associated with an increased risk of dying, also presented an initial stronger effect. The impact of age and sodium were constant over time. Conclusions: The current study points to the importance of evaluating covariates with time-varying effects in heart failure models. The analysis performed suggests that variations of Cox and Aalen models constitute a valuable tool for identifying these variables. The implementation of covariates with time-varying effects into heart failure prognostication models may reduce bias and increase the specificity of such models.

Natriuretic Peptides and Long-Term Mortality in Patients with Severe Aortic Stenosis

Background and aim of the study: The natriuretic peptides, brain natriuretic peptide (BNP) and its N-terminal prohormone (NT-proBNP), can be used as diagnostic and prognostic markers for aortic stenosis (AS). However, the association between BNP, NT-proBNP, and long-term clinical outcomes in patients with severe AS remains uncertain. Methods: A total of 64 patients with severe AS was prospectively enrolled into the study, and underwent clinical and echocardiographic assessments at baseline. Blood samples were drawn for plasma BNP and NT-proBNP analyses. The primary outcome was death from any cause, through a six-year follow up period. Cox proportional hazards modeling was used to examine the association between natriuretic peptides and long-term mortality, adjusting for important clinical factors. Results: During a mean period of 1,520 681 days, 51 patients (80%) were submitted to aortic valve replacement, and 13 patients (20%) were medically managed without surgical interventions. Mortality rates were 13.7% in the surgical group and 62% in the medically managed group (p <0.001). Patients with higher plasma BNP (>135 pg/ml) and NT-proBNP (>1,150 pg/ml) levels at baseline had a greater risk of long-term mortality (hazard ratio [HR] 3.2, 95% confidence interval [CI] 1.1-9.1; HR 4.3, 95% CI 1.4-13.5, respectively). After adjusting for important covariates, both BNP and NT-proBNP remained independently associated with long-term mortality (HR 2.9, 95%CI 1.5-5.7; HR 1.8, 95%CI 1.1-3.1, respectively). Conclusion: In patients with severe AS, plasma BNP and NT-proBNP levels were associated with long-term mortality. The use of these biomarkers to guide treatment might represent an interesting approach that deserves further evaluation. The Journal of Heart Valve Disease 2012;21:331-336

Association between the C242T polymorphism in the p22phox gene with arterial stiffness in the Brazilian population

de Oliveira Alvim R, Lima Santos PCJ, Goncalves Dias R, Rodrigues MV, de Sa Cunha R, Mill JG, Junior WN, Krieger JE, Pereira AC. Association between the C242T polymorphism in the p22phox gene with arterial stiffness in the Brazilian population. Physiol Genomics 44: 587-592, 2012. First published April 10, 2012; doi:10.1152/physiolgenomics.00122.2011.-NADPH oxidase p22phox subunit is responsible for the production of reactive oxygen species in the vascular tissue. The C242T polymorphism in the p22phox gene has been associated with diverse coronary artery disease phenotypes, but the findings about the protective or harmful effects of the T allele are still controversial. Our main aim was to assess the effect of p22phox C242T genotypes on arterial stiffness, a predictor of late morbidity and mortality, in individuals from the general population. We randomly selected 1,178 individuals from the general population of Vitoria City, Brazil. Genotypes for the C242T polymorphism were detected by PCR-RFLP, and pulse wave velocity (PWV) values were measured with a noninvasive automatic device Complior. p22phox and TNF-alpha gene expression were quantified by real-time PCR in human arterial mammary smooth muscle cells. In both the entire and nonhypertensive groups: individuals carrying the TT genotype had higher PWV values and higher risk for increased arterial stiffness [odds ratio (OR) 1.93, 95% confidence interval (CI) 1.27-2.92 and OR 1.78, 95% CI 1.07-2.95, respectively] compared with individuals carrying CC + CT genotypes, even after adjustment for covariates. No difference in the p22phox gene expression according C242T genotypes was observed. However, TNF-alpha gene expression was higher in cells from individual carrying the T allele, suggesting that this genetic marker is associated with functional phenotypes at the gene expression level. In conclusion, we suggest that p22phox C242T polymorphism is associated with arterial stiffness evaluated by PWV in the general population. This genetic association shed light on the understanding of the genetic modulation on vascular dysfunction mediated by NADPH oxidase.