982 resultados para Survival models
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Suppose that having established a marginal total effect of a point exposure on a time-to-event outcome, an investigator wishes to decompose this effect into its direct and indirect pathways, also know as natural direct and indirect effects, mediated by a variable known to occur after the exposure and prior to the outcome. This paper proposes a theory of estimation of natural direct and indirect effects in two important semiparametric models for a failure time outcome. The underlying survival model for the marginal total effect and thus for the direct and indirect effects, can either be a marginal structural Cox proportional hazards model, or a marginal structural additive hazards model. The proposed theory delivers new estimators for mediation analysis in each of these models, with appealing robustness properties. Specifically, in order to guarantee ignorability with respect to the exposure and mediator variables, the approach, which is multiply robust, allows the investigator to use several flexible working models to adjust for confounding by a large number of pre-exposure variables. Multiple robustness is appealing because it only requires a subset of working models to be correct for consistency; furthermore, the analyst need not know which subset of working models is in fact correct to report valid inferences. Finally, a novel semiparametric sensitivity analysis technique is developed for each of these models, to assess the impact on inference, of a violation of the assumption of ignorability of the mediator.
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This paper proposes Poisson log-linear multilevel models to investigate population variability in sleep state transition rates. We specifically propose a Bayesian Poisson regression model that is more flexible, scalable to larger studies, and easily fit than other attempts in the literature. We further use hierarchical random effects to account for pairings of individuals and repeated measures within those individuals, as comparing diseased to non-diseased subjects while minimizing bias is of epidemiologic importance. We estimate essentially non-parametric piecewise constant hazards and smooth them, and allow for time varying covariates and segment of the night comparisons. The Bayesian Poisson regression is justified through a re-derivation of a classical algebraic likelihood equivalence of Poisson regression with a log(time) offset and survival regression assuming piecewise constant hazards. This relationship allows us to synthesize two methods currently used to analyze sleep transition phenomena: stratified multi-state proportional hazards models and log-linear models with GEE for transition counts. An example data set from the Sleep Heart Health Study is analyzed.
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In medical follow-up studies, ordered bivariate survival data are frequently encountered when bivariate failure events are used as the outcomes to identify the progression of a disease. In cancer studies interest could be focused on bivariate failure times, for example, time from birth to cancer onset and time from cancer onset to death. This paper considers a sampling scheme where the first failure event (cancer onset) is identified within a calendar time interval, the time of the initiating event (birth) can be retrospectively confirmed, and the occurrence of the second event (death) is observed sub ject to right censoring. To analyze this type of bivariate failure time data, it is important to recognize the presence of bias arising due to interval sampling. In this paper, nonparametric and semiparametric methods are developed to analyze the bivariate survival data with interval sampling under stationary and semi-stationary conditions. Numerical studies demonstrate the proposed estimating approaches perform well with practical sample sizes in different simulated models. We apply the proposed methods to SEER ovarian cancer registry data for illustration of the methods and theory.
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OBJECTIVES: The objectives of this systematic review were to assess the 5-year survival of resin-bonded bridges (RBBs) and to describe the incidence of technical and biological complications. METHODS: An electronic Medline search complemented by manual searching was conducted to identify prospective and retrospective cohort studies on RBBs with a mean follow-up time of at least 5 years. Patients had to have been examined clinically at the follow-up visit. Assessment of the identified studies and data extraction were performed independently by two reviewers. Failure and complication rates were analyzed using random-effects Poissons regression models to obtain summary estimates of 5-year proportions. RESULTS: The search provided 6110 titles and 214 abstracts. Full-text analysis was performed for 93 articles, resulting in 17 studies that met the inclusion criteria. Meta-analysis of these studies indicated an estimated survival of RBBs of 87.7% (95% confidence interval (CI): 81.6-91.9%) after 5 years. The most frequent complication was debonding (loss of retention), which occurred in 19.2% (95% CI: 13.8-26.3%) of RBBs over an observation period of 5 years. The annual debonding rate for RBBs placed on posterior teeth (5.03%) tended to be higher than that for anterior-placed RBBs (3.05%). This difference, however, did not reach statistical significance (P=0.157). Biological complications, like caries on abutments and RBBs lost due to periodontitis, occurred in 1.5% of abutments and 2.1% of RBBs, respectively. CONCLUSION: Despite the high survival rate of RBBs, technical complications like debonding are frequent. This in turn means that a substantial amount of extra chair time may be needed following the incorporation of RBBs. There is thus an urgent need for studies with a follow-up time of 10 years or more, to evaluate the long-term outcomes.
A systematic review of the 5-year survival and complication rates of implant-supported single crowns
Resumo:
OBJECTIVES: The objective of this systematic review was to assess the 5-year survival of implant-supported single crowns (SCs) and to describe the incidence of biological and technical complications. METHODS: An electronic MEDLINE search complemented by manual searching was conducted to identify prospective and retrospective cohort studies on SCs with a mean follow-up time of at least 5 years. Failure and complication rates were analyzed using random-effects Poisson's regression models to obtain summary estimates of 5-year proportions. RESULTS: Twenty-six studies from an initial yield of 3601 titles were finally selected and data were extracted. In a meta-analysis of these studies, survival of implants supporting SCs was 96.8% [95% confidence interval (CI): 95.9-97.6%] after 5 years. The survival rate of SCs supported by implants was 94.5% (95% CI: 92.5-95.9%) after 5 years of function. The survival rate of metal-ceramic crowns, 95.4% (95% CI: 93.6-96.7%), was significantly (P=0.005) higher than the survival rate, 91.2% (95% CI: 86.8-94.2%), of all-ceramic crowns. Peri-implantitis and soft tissue complications occurred adjacent to 9.7% of the SCs and 6.3% of the implants had bone loss exceeding 2 mm over the 5-year observation period. The cumulative incidence of implant fractures after 5 years was 0.14%. After 5 years, the cumulative incidence of screw or abutment loosening was 12.7% and 0.35% for screw or abutment fracture. For supra-structure-related complications, the cumulative incidence of ceramic or veneer fractures was 4.5%. CONCLUSION: It can be concluded that after an observation period of 5 years, high survival rates for implants and implant-supported SCs can be expected. However, biological and particularly technical complications are frequent.
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OBJECTIVE: Anemia is a common comorbid condition in various inflammatory states and an established predictor of mortality in patients with chronic heart failure, ischemic heart disease, and end-stage renal disease. The present study of patients with abdominal aortic aneurysm (AAA) undergoing endovascular repair (EVAR) assessed the relationships between baseline hemoglobin concentration and AAA size, as well as anemia and long-term survival. METHODS: Between March 1994 and November 2006, 711 patients (65 women, mean age 75.8 +/- 7.8 years) underwent elective EVAR. Anemia was defined as a hemoglobin level <13 g/dL in men and <12 g/dL in women. Post-EVAR mean follow-up was 48.3 +/- 32.0 months. Association of hemoglobin level with AAA size was assessed with multiple linear regression. Mortality was determined with use of the internet-based Social Security Death Index and the electronic hospital record. Kaplan-Meier survival curves of anemic and nonanemic patient groups were compared by the log-rank method. Multivariable logistic regression models were used to determine the influence of anemia on vital status after EVAR. RESULTS: A total of 218/711 (30.7%) of AAA patients undergoing EVAR had anemia at baseline. After adjustment for various risk factors, hemoglobin level was inversely related to maximum AAA diameter (beta: - .144, 95%-CI: -1.482 - .322, P = .002). Post-EVAR survival was 65.5% at 5 years and 44.4% at 10 years. In long-term follow-up, survival was significantly lower in patients with anemia as compared to patients without anemia (P < .0001 by log-rank). Baseline hemoglobin levels were independently related to long-term mortality in multivariable Cox regression analysis adjusted for various risk factors (adjusted HR: 0.866, 95% CI: .783 to .958, P = .005). Within this model, statin use (adjusted HR: .517, 95% CI: .308 to .868, P = .013) was independently related to long-term survival, whereas baseline AAA diameter (adjusted HR: 1.022, 95% CI: 1.009 to 1.036, P = .001) was an independently associated with increased mortality. CONCLUSIONS: Baseline hemoglobin concentration is independently associated with AAA size and reduced long-term survival following EVAR. Thus, the presence or absence of anemia offers a potential refinement of existing risk stratification instruments.
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OBJECTIVES: The objectives of this systematic review were to assess the survival rate of implants placed in sites with transalveolar sinus floor elevation. MATERIAL AND METHODS: An electronic search was conducted to identify prospective and retrospective cohort studies on transalveolar sinus floor elevation, with a mean follow-up time of at least 1 year after functional loading. Failure and complication rates were analyzed using random-effects Poisson regression models to obtain summary estimates/ year proportions. RESULTS: The search provided 849 titles. Full-text analysis was performed for 176 articles, resulting in 19 studies that met the inclusion criteria. Meta-analysis of these studies indicated an estimated annual failure rate of 2.48% (95% confidence interval (95% CI): 1.37-4.49%) translating to an estimated survival rate of 92.8% (95% CI): 87.4-96.0%) for implants placed in transalveolarly augmented sinuses, after 3 years in function. Furthermore, subject-based analysis revealed an estimated annual failure of 3.71% (95% CI: 1.21-11.38%), translating to 10.5% (95% CI: 3.6-28.9%) of the subjects experiencing implant loss over 3 years. CONCLUSION: Survival rates of implants placed in transalveolar sinus floor augmentation sites are comparable to those in non-augmented sites. This technique is predictable with a low incidence of complications during and post-operatively.
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AIM: The purpose of this study was to systematically review the literature on the survival rates of palatal implants, Onplants((R)), miniplates and mini screws. MATERIAL AND METHODS: An electronic MEDLINE search supplemented by manual searching was conducted to identify randomized clinical trials, prospective and retrospective cohort studies on palatal implants, Onplants((R)), miniplates and miniscrews with a mean follow-up time of at least 12 weeks and of at least 10 units per modality having been examined clinically at a follow-up visit. Assessment of studies and data abstraction was performed independently by two reviewers. Reported failures of used devices were analyzed using random-effects Poisson regression models to obtain summary estimates and 95% confidence intervals (CI) of failure and survival proportions. RESULTS: The search up to January 2009 provided 390 titles and 71 abstracts with full-text analysis of 34 articles, yielding 27 studies that met the inclusion criteria. In meta-analysis, the failure rate for Onplants((R)) was 17.2% (95% CI: 5.9-35.8%), 10.5% for palatal implants (95% CI: 6.1-18.1%), 16.4% for miniscrews (95% CI: 13.4-20.1%) and 7.3% for miniplates (95% CI: 5.4-9.9%). Miniplates and palatal implants, representing torque-resisting temporary anchorage devices (TADs), when grouped together, showed a 1.92-fold (95% CI: 1.06-2.78) lower clinical failure rate than miniscrews. CONCLUSION: Based on the available evidence in the literature, palatal implants and miniplates showed comparable survival rates of >or=90% over a period of at least 12 weeks, and yielded superior survival than miniscrews. Palatal implants and miniplates for temporary anchorage provide reliable absolute orthodontic anchorage. If the intended orthodontic treatment would require multiple miniscrew placement to provide adequate anchorage, the reliability of such systems is questionable. For patients who are undergoing extensive orthodontic treatment, force vectors may need to be varied or the roots of the teeth to be moved may need to slide past the anchors. In this context, palatal implants or miniplates should be the TADs of choice.
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BACKGROUND Low-grade gliomas (LGGs) are rare brain neoplasms, with survival spanning up to a few decades. Thus, accurate evaluations on how biomarkers impact survival among patients with LGG require long-term studies on samples prospectively collected over a long period. METHODS The 210 adult LGGs collected in our databank were screened for IDH1 and IDH2 mutations (IDHmut), MGMT gene promoter methylation (MGMTmet), 1p/19q loss of heterozygosity (1p19qloh), and nuclear TP53 immunopositivity (TP53pos). Multivariate survival analyses with multiple imputation of missing data were performed using either histopathology or molecular markers. Both models were compared using Akaike's information criterion (AIC). The molecular model was reduced by stepwise model selection to filter out the most critical predictors. A third model was generated to assess for various marker combinations. RESULTS Molecular parameters were better survival predictors than histology (ΔAIC = 12.5, P< .001). Forty-five percent of studied patients died. MGMTmet was positively associated with IDHmut (P< .001). In the molecular model with marker combinations, IDHmut/MGMTmet combined status had a favorable impact on overall survival, compared with IDHwt (hazard ratio [HR] = 0.33, P< .01), and even more so the triple combination, IDHmut/MGMTmet/1p19qloh (HR = 0.18, P< .001). Furthermore, IDHmut/MGMTmet/TP53pos triple combination was a significant risk factor for malignant transformation (HR = 2.75, P< .05). CONCLUSION By integrating networks of activated molecular glioma pathways, the model based on genotype better predicts prognosis than histology and, therefore, provides a more reliable tool for standardizing future treatment strategies.
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The African great lakes are of utmost importance for the local economy (fishing), as well as being essential to the survival of the local people. During the past decades, these lakes experienced fast changes in ecosystem structure and functioning, and their future evolution is a major concern. In this study, for the first time a set of one-dimensional lake models are evaluated for Lake Kivu (2.28°S; 28.98°E), East Africa. The unique limnology of this meromictic lake, with the importance of salinity and subsurface springs in a tropical high-altitude climate, presents a worthy challenge to the seven models involved in the Lake Model Intercomparison Project (LakeMIP). Meteorological observations from two automatic weather stations are used to drive the models, whereas a unique dataset, containing over 150 temperature profiles recorded since 2002, is used to assess the model’s performance. Simulations are performed over the freshwater layer only (60 m) and over the average lake depth (240 m), since salinity increases with depth below 60 m in Lake Kivu and some lake models do not account for the influence of salinity upon lake stratification. All models are able to reproduce the mixing seasonality in Lake Kivu, as well as the magnitude and seasonal cycle of the lake enthalpy change. Differences between the models can be ascribed to variations in the treatment of the radiative forcing and the computation of the turbulent heat fluxes. Fluctuations in wind velocity and solar radiation explain inter-annual variability of observed water column temperatures. The good agreement between the deep simulations and the observed meromictic stratification also shows that a subset of models is able to account for the salinity- and geothermal-induced effects upon deep-water stratification. Finally, based on the strengths and weaknesses discerned in this study, an informed choice of a one-dimensional lake model for a given research purpose becomes possible.
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Context. According to the sequential accretion model (or core-nucleated accretion model), giant planet formation is based first on the formation of a solid core which, when massive enough, can gravitationally bind gas from the nebula to form the envelope. The most critical part of the model is the formation time of the core: to trigger the accretion of gas, the core has to grow up to several Earth masses before the gas component of the protoplanetary disc dissipates. Aims: We calculate planetary formation models including a detailed description of the dynamics of the planetesimal disc, taking into account both gas drag and excitation of forming planets. Methods: We computed the formation of planets, considering the oligarchic regime for the growth of the solid core. Embryos growing in the disc stir their neighbour planetesimals, exciting their relative velocities, which makes accretion more difficult. Here we introduce a more realistic treatment for the evolution of planetesimals' relative velocities, which directly impact on the formation timescale. For this, we computed the excitation state of planetesimals, as a result of stirring by forming planets, and gas-solid interactions. Results: We find that the formation of giant planets is favoured by the accretion of small planetesimals, as their random velocities are more easily damped by the gas drag of the nebula. Moreover, the capture radius of a protoplanet with a (tiny) envelope is also larger for small planetesimals. However, planets migrate as a result of disc-planet angular momentum exchange, with important consequences for their survival: due to the slow growth of a protoplanet in the oligarchic regime, rapid inward type I migration has important implications on intermediate-mass planets that have not yet started their runaway accretion phase of gas. Most of these planets are lost in the central star. Surviving planets have masses either below 10 M⊕ or above several Jupiter masses. Conclusions: To form giant planets before the dissipation of the disc, small planetesimals (~0.1 km) have to be the major contributors of the solid accretion process. However, the combination of oligarchic growth and fast inward migration leads to the absence of intermediate-mass planets. Other processes must therefore be at work to explain the population of extrasolar planets that are presently known.
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Health-related quality of life (HRQOL) is an important measure of the effects of chronic liver disease in affected patients that helps guide interventions to improve well-being. However, the relationship between HRQOL and survival in liver transplant candidates remains unclear. We examined whether the Physical Component Summary (PCS) and Mental Component Summary (MCS) scores from the Short Form 36 (SF-36) Health Survey were associated with survival in liver transplant candidates. We administered the SF-36 questionnaire (version 2.0) to patients in the Pulmonary Vascular Complications of Liver Disease study, a multicenter prospective cohort of patients evaluated for liver transplantation in 7 academic centers in the United States between 2003 and 2006. Cox proportional hazards models were used with death as the primary outcome and adjustment for liver transplantation as a time-varying covariate. The mean age of the 252 participants was 54 +/- 10 years, 64% were male, and 94% were white. During the 422 person years of follow-up, 147 patients (58%) were listed, 75 patients (30%) underwent transplantation, 49 patients (19%) died, and 3 patients were lost to follow-up. Lower baseline PCS scores were associated with an increased mortality rate despite adjustments for age, gender, Model for End-Stage Liver Disease score, and liver transplantation (P for the trend = 0.0001). The MCS score was not associated with mortality (P for the trend = 0.53). In conclusion, PCS significantly predicts survival in liver transplant candidates, and interventions directed toward improving the physical status may be helpful in improving outcomes in liver transplant candidates.