Modelos para dados grupados e sensurados aplicados à área biológica: comparação usando fator de Bayes

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Efeito da fragmentação sobre a persistência de anfíbios anuros (Amphibia: Anura) na Mata Atlântica

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Efeito da fragmentação sobre a persistência de anfíbios anuros (Amphibia: Anura) na Mata Atlântica

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A model of road effect using line integrals and a test of the performance of two new road indices using the distribution of small mammals in an Atlantic Forest landscape

Effects of roads on wildlife and its habitat have been measured using metrics, such as the nearest road distance, road density, and effective mesh size. In this work we introduce two new indices: (1) Integral Road Effect (IRE), which measured the sum effects of points in a road at a fixed point in the forest; and (2) Average Value of the Infinitesimal Road Effect (AVIRE), which measured the average of the effects of roads at this point. IRE is formally defined as the line integral of a special function (the infinitesimal road effect) along the curves that model the roads, whereas AVIRE is the quotient of IRE by the length of the roads. Combining tools of ArcGIS software with a numerical algorithm, we calculated these and other road and habitat cover indices in a sample of points in a human-modified landscape in the Brazilian Atlantic Forest, where data on the abundance of two groups of small mammals (forest specialists and habitat generalists) were collected in the field. We then compared through the Akaike Information Criterion (AIC) a set of candidate regression models to explain the variation in small mammal abundance, including models with our two new road indices (AVIRE and IRE) or models with other road effect indices (nearest road distance, mesh size, and road density), and reference models (containing only habitat indices, or only the intercept without the effect of any variable). Compared to other road effect indices, AVIRE showed the best performance to explain abundance of forest specialist species, whereas the nearest road distance obtained the best performance to generalist species. AVIRE and habitat together were included in the best model for both small mammal groups, that is, higher abundance of specialist and generalist small mammals occurred where there is lower average road effect (less AVIRE) and more habitat. Moreover, AVIRE was not significantly correlated with habitat cover of specialists and generalists differing from the other road effect indices, except mesh size, which allows for separating the effect of roads from the effect of habitat on small mammal communities. We suggest that the proposed indices and GIS procedures could also be useful to describe other spatial ecological phenomena, such as edge effect in habitat fragments. (C) 2012 Elsevier B.V. All rights reserved.

Height-diameter relationships of tropical Atlantic moist forest trees in southeastern Brazil

Site-specific height-diameter models may be used to improve biomass estimates for forest inventories where only diameter at breast height (DBH) measurements are available. In this study, we fit height-diameter models for vegetation types of a tropical Atlantic forest using field measurements of height across plots along an altitudinal gradient. To fit height-diameter models, we sampled trees by DBH class and measured tree height within 13 one-hectare permanent plots established at four altitude classes. To select the best model we tested the performance of 11 height-diameter models using the Akaike Information Criterion (AIC). The Weibull and Chapman-Richards height-diameter models performed better than other models, and regional site-specific models performed better than the general model. In addition, there is a slight variation of height-diameter relationships across the altitudinal gradient and an extensive difference in the stature between the Atlantic and Amazon forests. The results showed the effect of altitude on tree height estimates and emphasize the need for altitude-specific models that produce more accurate results than a general model that encompasses all altitudes. To improve biomass estimation, the development of regional height-diameter models that estimate tree height using a subset of randomly sampled trees presents an approach to supplement surveys where only diameter has been measured.

Evaluation of Viral Load Thresholds for Predicting New World Health Organization Stage 3 and 4 Events in HIV-Infected Children Receiving Highly Active Antiretroviral Therapy

Background: This study evaluated a wide range of viral load (VL) thresholds to identify a cut-point that best predicts new clinical events in children on stable highly active antiretroviral therapy (HAART). Methods: Cox proportional hazards modeling was used to assess the adjusted risk for World Health Organization stage 3 or 4 clinical events (WHO events) as a function of time-varying CD4, VL, and hemoglobin values in a cohort study of Latin American children on HAART >= 6 months. Models were fit using different VL cut-points between 400 and 50,000 copies per milliliter, with model fit evaluated on the basis of the minimum Akaike information criterion value, a standard model fit statistic. Results: Models were based on 67 subjects with WHO events out of 550 subjects on study. The VL cut-points of >2600 and >32,000 copies per milliliter corresponded to the lowest Akaike information criterion values and were associated with the highest hazard ratios (2.0, P = 0.015; and 2.1, P = 0.0058, respectively) for WHO events. Conclusions: In HIV-infected Latin American children on stable HAART, 2 distinct VL thresholds (>2600 and >32,000 copies/mL) were identified for predicting children at significantly increased risk for HIV-related clinical illness, after accounting for CD4 level, hemoglobin level, and other significant factors.

A coronary heart disease risk model for predicting the effect of potent antiretroviral therapy in HIV-1 infected men

BACKGROUND: Many HIV-infected patients on highly active antiretroviral therapy (HAART) experience metabolic complications including dyslipidaemia and insulin resistance, which may increase their coronary heart disease (CHD) risk. We developed a prognostic model for CHD tailored to the changes in risk factors observed in patients starting HAART. METHODS: Data from five cohort studies (British Regional Heart Study, Caerphilly and Speedwell Studies, Framingham Offspring Study, Whitehall II) on 13,100 men aged 40-70 and 114,443 years of follow up were used. CHD was defined as myocardial infarction or death from CHD. Model fit was assessed using the Akaike Information Criterion; generalizability across cohorts was examined using internal-external cross-validation. RESULTS: A parametric model based on the Gompertz distribution generalized best. Variables included in the model were systolic blood pressure, total cholesterol, high-density lipoprotein cholesterol, triglyceride, glucose, diabetes mellitus, body mass index and smoking status. Compared with patients not on HAART, the estimated CHD hazard ratio (HR) for patients on HAART was 1.46 (95% CI 1.15-1.86) for moderate and 2.48 (95% CI 1.76-3.51) for severe metabolic complications. CONCLUSIONS: The change in the risk of CHD in HIV-infected men starting HAART can be estimated based on typical changes in risk factors, assuming that HRs estimated using data from non-infected men are applicable to HIV-infected men. Based on this model the risk of CHD is likely to increase, but increases may often be modest, and could be offset by lifestyle changes.

A comparison of estimated glomerular filtration rates using Cockcroft−Gault and the Chronic Kidney Disease Epidemiology Collaboration estimating equations in HIV infection

OBJECTIVES: The aim of this study was to determine whether the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI)- or Cockcroft-Gault (CG)-based estimated glomerular filtration rates (eGFRs) performs better in the cohort setting for predicting moderate/advanced chronic kidney disease (CKD) or end-stage renal disease (ESRD). METHODS: A total of 9521 persons in the EuroSIDA study contributed 133 873 eGFRs. Poisson regression was used to model the incidence of moderate and advanced CKD (confirmed eGFR < 60 and < 30 mL/min/1.73 m(2) , respectively) or ESRD (fatal/nonfatal) using CG and CKD-EPI eGFRs. RESULTS: Of 133 873 eGFR values, the ratio of CG to CKD-EPI was ≥ 1.1 in 22 092 (16.5%) and the difference between them (CG minus CKD-EPI) was ≥ 10 mL/min/1.73 m(2) in 20 867 (15.6%). Differences between CKD-EPI and CG were much greater when CG was not standardized for body surface area (BSA). A total of 403 persons developed moderate CKD using CG [incidence 8.9/1000 person-years of follow-up (PYFU); 95% confidence interval (CI) 8.0-9.8] and 364 using CKD-EPI (incidence 7.3/1000 PYFU; 95% CI 6.5-8.0). CG-derived eGFRs were equal to CKD-EPI-derived eGFRs at predicting ESRD (n = 36) and death (n = 565), as measured by the Akaike information criterion. CG-based moderate and advanced CKDs were associated with ESRD [adjusted incidence rate ratio (aIRR) 7.17; 95% CI 2.65-19.36 and aIRR 23.46; 95% CI 8.54-64.48, respectively], as were CKD-EPI-based moderate and advanced CKDs (aIRR 12.41; 95% CI 4.74-32.51 and aIRR 12.44; 95% CI 4.83-32.03, respectively). CONCLUSIONS: Differences between eGFRs using CG adjusted for BSA or CKD-EPI were modest. In the absence of a gold standard, the two formulae predicted clinical outcomes with equal precision and can be used to estimate GFR in HIV-positive persons.

A multifactorial histopathologic score for the prediction of prognosis of resected esophageal adenocarcinomas after neoadjuvant chemotherapy

BACKGROUND For esophageal adenocarcinoma treated with neoadjuvant chemotherapy, postoperative staging classifications initially developed for non-pretreated tumors may not accurately predict prognosis. We tested whether a multifactorial TNM-based histopathologic prognostic score (PRSC), which additionally applies to tumor regression, may improve estimation of prognosis compared with the current Union for International Cancer Control/American Joint Committee on Cancer (UICC) staging system. PATIENTS AND METHODS We evaluated esophageal adenocarcinoma specimens following cis/oxaliplatin-based therapy from two separate centers (center 1: n = 280; and center 2: n = 80). For the PRSC, each factor was assigned a value from 1 to 2 (ypT0-2 = 1 point; ypT3-4 = 2 points; ypN0 = 1 point; ypN1-3 = 2 points; ≤50 % residual tumor/tumor bed = 1 point; >50 % residual tumor/tumor bed = 2 points). The three-tiered PRSC was based on the sum value of these factors (group A: 3; group B: 4-5; group C: 6) and was correlated with patients' overall survival (OS). RESULTS The PRSC groups showed significant differences with respect to OS (p < 0.0001; hazard ratio [HR] 2.2 [95 % CI 1.7-2.8]), which could also be demonstrated in both cohorts separately (center 1 p < 0.0001; HR 2.48 [95 % CI 1.8-3.3] and center 2 p = 0.015; HR 1.7 [95 % CI 1.1-2.6]). Moreover, the PRSC showed a more accurate prognostic discrimination than the current UICC staging system (p < 0.0001; HR 1.15 [95 % CI 1.1-1.2]), and assessment of two goodness-of-fit criteria (Akaike Information Criterion and Schwarz Bayesian Information Criterion) clearly supported the superiority of PRSC over the UICC staging. CONCLUSION The proposed PRSC clearly identifies three subgroups with different outcomes and may be more helpful for guiding further therapeutic decisions than the UICC staging system.

Combination of expression levels of miR-21 and miR-126 is associated with cancer-specific survival in clear-cell renal cell carcinoma

BACKGROUND Renal cell carcinoma (RCC) is marked by high mortality rate. To date, no robust risk stratification by clinical or molecular prognosticators of cancer-specific survival (CSS) has been established for early stages. Transcriptional profiling of small non-coding RNA gene products (miRNAs) seems promising for prognostic stratification. The expression of miR-21 and miR-126 was analysed in a large cohort of RCC patients; a combined risk score (CRS)-model was constructed based on expression levels of both miRNAs. METHODS Expression of miR-21 and miR-126 was evaluated by qRT-PCR in tumour and adjacent non-neoplastic tissue in n = 139 clear cell RCC patients. Relation of miR-21 and miR-126 expression with various clinical parameters was assessed. Parameters were analysed by uni- and multivariate COX regression. A factor derived from the z-score resulting from the COX model was determined for both miRs separately and a combined risk score (CRS) was calculated multiplying the relative expression of miR-21 and miR-126 by this factor. The best fitting COX model was selected by relative goodness-of-fit with the Akaike information criterion (AIC). RESULTS RCC with and without miR-21 up- and miR-126 downregulation differed significantly in synchronous metastatic status and CSS. Upregulation of miR-21 and downregulation of miR-126 were independently prognostic. A combined risk score (CRS) based on the expression of both miRs showed high sensitivity and specificity in predicting CSS and prediction was independent from any other clinico-pathological parameter. Association of CRS with CSS was successfully validated in a testing cohort containing patients with high and low risk for progressive disease. CONCLUSIONS A combined expression level of miR-21 and miR-126 accurately predicted CSS in two independent RCC cohorts and seems feasible for clinical application in assessing prognosis.

Older patients with low Charlson score and high-risk prostate cancer benefit from radical prostatectomy

INTRODUCTION The aim of the study was to identify the appropriate level of Charlson comorbidity index (CCI) in older patients (>70 years) with high-risk prostate cancer (PCa) to achieve survival benefit following radical prostatectomy (RP). METHODS We retrospectively analyzed 1008 older patients (>70 years) who underwent RP with pelvic lymph node dissection for high-risk prostate cancer (preoperative prostate-specific antigen >20 ng/mL or clinical stage ≥T2c or Gleason ≥8) from 14 tertiary institutions between 1988 and 2014. The study population was further grouped into CCI < 2 and ≥2 for analysis. Survival rate for each group was estimated with Kaplan-Meier method and competitive risk Fine-Gray regression to estimate the best explanatory multivariable model. Area under the curve (AUC) and Akaike information criterion were used to identify ideal 'Cut off' for CCI. RESULTS The clinical and cancer characteristics were similar between the two groups. Comparison of the survival analysis using the Kaplan-Meier curve between two groups for non-cancer death and survival estimations for 5 and 10 years shows significant worst outcomes for patients with CCI ≥ 2. In multivariate model to decide the appropriate CCI cut-off point, we found CCI 2 has better AUC and p value in log rank test. CONCLUSION Older patients with fewer comorbidities harboring high-risk PCa appears to benefit from RP. Sicker patients are more likely to die due to non-prostate cancer-related causes and are less likely to benefit from RP.

Macular atrophy in patients with long-term anti-VEGF treatment for neovascular age-related macular degeneration.

PURPOSE To identify the prevalence and progression of macular atrophy (MA) in neovascular age-related macular degeneration (AMD) patients under long-term anti-vascular endothelial growth factor (VEGF) therapy and to determine risk factors. METHOD This retrospective study included patients with neovascular AMD and ≥30 anti-VEGF injections. Macular atrophy (MA) was measured using near infrared and spectral-domain optical coherence tomography (SD-OCT). Yearly growth rate was estimated using square-root transformation to adjust for baseline area and allow for linearization of growth rate. Multiple regression with Akaike information criterion (AIC) as model selection criterion was used to estimate the influence of various parameters on MA area. RESULTS Forty-nine eyes (47 patients, mean age 77 ± 14) were included with a mean of 48 ± 13 intravitreal anti-VEGF injections (ranibizumab:37 ± 11, aflibercept:11 ± 6, mean number of injections/year 8 ± 2.1) over a mean treatment period of 6.2 ± 1.3 years (range 4-8.5). Mean best-corrected visual acuity improved from 57 ± 17 letters at baseline (= treatment start) to 60 ± 16 letters at last follow-up. The MA prevalence within and outside the choroidal neovascularization (CNV) border at initial measurement was 45% and increased to 74%. Mean MA area increased from 1.8 ± 2.7 mm(2) within and 0.5 ± 0.98 mm(2) outside the CNV boundary to 2.7 ± 3.4 mm(2) and 1.7 ± 1.8 mm(2) , respectively. Multivariate regression determined posterior vitreous detachment (PVD) and presence/development of intraretinal cysts (IRCs) as significant factors for total MA size (R(2) = 0.16, p = 0.02). Macular atrophy (MA) area outside the CNV border was best explained by the presence of reticular pseudodrusen (RPD) and IRC (R(2) = 0.24, p = 0.02). CONCLUSION A majority of patients show MA after long-term anti-VEGF treatment. Reticular pseudodrusen (RPD), IRC and PVD but not number of injections or treatment duration seem to be associated with the MA size.

Handling high level of censoring for endovascular aortic repair risk prediction

Feature selection is important in medical field for many reasons. However, selecting important variables is a difficult task with the presence of censoring that is a unique feature in survival data analysis. This paper proposed an approach to deal with the censoring problem in endovascular aortic repair survival data through Bayesian networks. It was merged and embedded with a hybrid feature selection process that combines cox's univariate analysis with machine learning approaches such as ensemble artificial neural networks to select the most relevant predictive variables. The proposed algorithm was compared with common survival variable selection approaches such as; least absolute shrinkage and selection operator LASSO, and Akaike information criterion AIC methods. The results showed that it was capable of dealing with high censoring in the datasets. Moreover, ensemble classifiers increased the area under the roc curves of the two datasets collected from two centers located in United Kingdom separately. Furthermore, ensembles constructed with center 1 enhanced the concordance index of center 2 prediction compared to the model built with a single network. Although the size of the final reduced model using the neural networks and its ensembles is greater than other methods, the model outperformed the others in both concordance index and sensitivity for center 2 prediction. This indicates the reduced model is more powerful for cross center prediction.

A population dynamical model of Operophtera brumata, L. extended by climatic factors

Setting out from the database of Operophtera brumata, L. in between 1973 and 2000 due to the Light Trap Network in Hungary, we introduce a simple theta-logistic population dynamical model based on endogenous and exogenous factors, only. We create an indicator set from which we can choose some elements with which we can improve the fitting results the most effectively. Than we extend the basic simple model with additive climatic factors. The parameter optimization is based on the minimized root mean square error. The best model is chosen according to the Akaike Information Criterion. Finally we run the calibrated extended model with daily outputs of the regional climate model RegCM3.1, regarding 1961-1990 as reference period and 2021-2050 with 2071-2100 as future predictions. The results of the three time intervals are fitted with Beta distributions and compared statistically. The expected changes are discussed.

Gato-do-mato-pequeno (Leopardus tigrinus) na Caatinga: ocupação e padrão de atividade de um felídeo ameaçado e pouco conhecido na floresta tropical seca do nordeste do Brasil

While the carnivores are considered regulators and structuring of natural communities are also extremely threatened by human activities. Endangered little-spotted-cat (Leopardus tigrinus) is one of the lesser known species from the Neotropical cats. In this work we investigate the occupancy and the activity pattern of L. tigrinus in Caatinga of Rio Grande do Norte testing: 1) how environmental and anthropogenic factors influence their occupation and 2) how biotic and abiotic factors influence their activity pattern. For this we raised occurrence data of species in 10 priority areas for conservation. We built hierarchical models of occupancy based on maximum likelihood to represent biological hypotheses which were ranked using the Akaike Information Criterion (AIC). According to the results the feline occupancy is more likely away from rural settlements and in areas with a higher proportion of woody vegetation. The opportunistic killing of L. tigrinus and in retaliation for poultry predation close to residential areas can explain this result; as well as more complex vegetation structure can better serve as refuge and ensure more food. Analyzing the records of the species through circular statistics we conclude that the activity pattern is mostly nocturnal, although considerable crepuscular and a small diurnal activity. L. tigrinus activity was directly affected by the availability of small terrestrial mammals, which are essentially nocturnal. In addition, the temperatures recorded in the environment directly and indirectly affect the activity of the little-spotted-cat, as also influence the activity of their potential prey. Generally, the cats were more active when possible prey were active, and this happened at night when lower temperatures are recorded. Moreover, the different lunar phases did not affect the activity pattern. The results improve the understanding of an endangered feline inhabiting the Caatinga biome, and thus can help develop conservation and management strategies, as well as in planning future research in this semi-arid ecosystem.