The Impact of Uncertainty in the AIDS Incubation Period on Reconstructions of the HIV Epidemic

Backcalculation is the primary method used to reconstruct past human immunodeficiency virus (HIV) infection rates, to estimate current prevalence of HIV infection, and to project future incidence of acquired immunodeficiency syndrome (AIDS). The method is very sensitive to uncertainty about the incubation period. We estimate incubation distributions from three sets of cohort data and find that the estimates for the cohorts are substantially different. Backcalculations employing the different estimates produce equally good fits to reported AIDS counts but quite different estimates of cumulative infections. These results suggest that the incubation distribution is likely to differ for different populations and that the differences are large enough to have a big impact on the resulting estimates of HIV infection rates. This seriously limits the usefulness of backcalculation for populations (such as intravenous drug users, heterosexuals, and women) that lack precise information on incubation times.

Locally Efficient Estimation in Censored Data Models: Theory and Examples

In many applications the observed data can be viewed as a censored high dimensional full data random variable X. By the curve of dimensionality it is typically not possible to construct estimators that are asymptotically efficient at every probability distribution in a semiparametric censored data model of such a high dimensional censored data structure. We provide a general method for construction of one-step estimators that are efficient at a chosen submodel of the full-data model, are still well behaved off this submodel and can be chosen to always improve on a given initial estimator. These one-step estimators rely on good estimators of the censoring mechanism and thus will require a parametric or semiparametric model for the censoring mechanism. We present a general theorem that provides a template for proving the desired asymptotic results. We illustrate the general one-step estimation methods by constructing locally efficient one-step estimators of marginal distributions and regression parameters with right-censored data, current status data and bivariate right-censored data, in all models allowing the presence of time-dependent covariates. The conditions of the asymptotics theorem are rigorously verified in one of the examples and the key condition of the general theorem is verified for all examples.

Generalizations of Current Status Data With Applications

In estimation of a survival function, current status data arises when the only information available on individuals is their survival status at a single monitoring time. Here we briefly review extensions of this form of data structure in two directions: (i) doubly censored current status data, where there is incomplete information on the origin of the failure time random variable, and (ii) current status information on more complicated stochastic processes. Simple examples of these data forms are presented for motivation.

Efficiency of the Sieved-NPMLE in CAR-Missing Data Models

We consider nonparametric missing data models for which the censoring mechanism satisfies coarsening at random and which allow complete observations on the variable X of interest. W show that beyond some empirical process conditions the only essential condition for efficiency of an NPMLE of the distribution of X is that the regions associated with incomplete observations on X contain enough complete observations. This is heuristically explained by describing the EM-algorithm. We provide identifiably of the self-consistency equation and efficiency of the NPMLE in order to make this statement rigorous. The usual kind of differentiability conditions in the proof are avoided by using an identity which holds for the NPMLE of linear parameters in convex models. We provide a bivariate censoring application in which the condition and hence the NPMLE fails, but where other estimators, not based on the NPMLE principle, are highly inefficient. It is shown how to slightly reduce the data so that the conditions hold for the reduced data. The conditions are verified for the univariate censoring, double censored, and Ibragimov-Has'minski models.

Uncertainty About the Incubation Period of AIDS and its Impact on Backcalculation

We analyze three sets of doubly-censored cohort data on incubation times, estimating incubation distributions using semi-parametric methods and assessing the comparability of the estimates. Weibull models appear to be inappropriate for at least one of the cohorts, and the estimates for the different cohorts are substantially different. We use these estimates as inputs for backcalculation, using a nonparametric method based on maximum penalized likelihood. The different incubations all produce fits to the reported AIDS counts that are as good as the fit from a nonstationary incubation distribution that models treatment effects, but the estimated infection curves are very different. We also develop a method for estimating nonstationarity as part of the backcalculation procedure and find that such estimates also depend very heavily on the assumed incubation distribution. We conclude that incubation distributions are so uncertain that meaningful error bounds are difficult to place on backcalculated estimates and that backcalculation may be too unreliable to be used without being supplemented by other sources of information in HIV prevalence and incidence.

Smooth Hazard Function Estimation for Interval Censored Data with Time Varying Covariates

In this paper we propose methods for smooth hazard estimation of a time variable where that variable is interval censored. These methods allow one to model the transformed hazard in terms of either smooth (smoothing splines) or linear functions of time and other relevant time varying predictor variables. We illustrate the use of this method on a dataset of hemophiliacs where the outcome, time to seroconversion for HIV, is interval censored and left-truncated.

Estimating Multiple Tumor Transition Rates Based on Data from Survival/Sacrifice Experiments

In this paper, we focus on the model for two types of tumors. Tumor development can be described by four types of death rates and four tumor transition rates. We present a general semi-parametric model to estimate the tumor transition rates based on data from survival/sacrifice experiments. In the model, we make a proportional assumption of tumor transition rates on a common parametric function but no assumption of the death rates from any states. We derived the likelihood function of the data observed in such an experiment, and an EM algorithm that simplified estimating procedures. This article extends work on semi-parametric models for one type of tumor (see Portier and Dinse and Dinse) to two types of tumors.

The Two-Interval Line-Segment Problem

In this paper, the NPMLE in the one-dimensional line segment problem is defined and studied, where line segments on the real line through two non-overlapping intervals are observed. The self-consistency equations for the NPMLE are defined and a quick algorithm for solving them is provided. Supnorm weak convergence to a Gaussian process and efficiency of the NPMLE is proved. The problem has a strong geological application in the study of the lifespan of species.

Shaping the Future of Public Health: The Role of Biostatistics

Comments about the current place for the discipline of Biostatistics within Public Health (1993).

Estimation of Transition Probabilities in Animal Carcinogenicity Experiments

This paper discusses estimation of the tumor incidence rate, the death rate given tumor is present and the death rate given tumor is absent using a discrete multistage model. The model was originally proposed by Dewanji and Kalbfleisch (1986) and the maximum likelihood estimate of the tumor incidence rate was obtained using EM algorithm. In this paper, we use a reparametrization to simplify the estimation procedure. The resulting estimates are not always the same as the maximum likelihood estimates but are asymptotically equivalent. In addition, an explicit expression for asymptotic variance and bias of the proposed estimators is also derived. These results can be used to compare efficiency of different sacrifice schemes in carcinogenicity experiments.

Proving Efficiency of NPMLE and Identities

A method is given for proving efficiency of NPMLE directly linked to empirical process theory. The conditions in general are appropriate consistency of the NPMLE, differentiability of the model, differentiability of the parameter of interest, local convexity of the parameter space, and a Donsker class condition for the class of efficient influence functions obtained by varying the parameters. For the case that the model is linear in the parameter and the parameter space is convex, as with most nonparametric missing data models, we show that the method leads to an identity for the NPMLE which almost says that the NPMLE is efficient and provides us straightforwardly with a consistency and efficiency proof. This identify is extended to an almost linear class of models which contain biased sampling models. To illustrate, the method is applied to the univariate censoring model, random truncation models, interval censoring case I model, the class of parametric models and to a class of semiparametric models.

Percutaneous autologous venous valve transplantation: short-term feasibility study in an ovine model

BACKGROUND: Limited experience with bioprosthetic venous valve percutaneously inserted into femoral veins in 15 patients has been promising in short-term results only to show disappointing long-term results. Percutaneous autogenous venous valve (PAVV) transplantation was explored in an ovine model as a possible alternative treatment. METHODS: PAVV consisted of a vein segment containing a valve that was attached to a stent template. The stent templates (n = 9) were designed and hand made in our research laboratory. They consist of two stainless steel square stents 13 or 15 mm in diameter to fit the ovine jugular veins (JV), which ranges from 10 to 15 mm in diameter. A valve-containing segment of JV was harvested and attached with sutures and barbs inside the stent template (n = 9). The valve devices were then manually folded and front loaded inside the 4 cm chamber of the 13F delivery sheath and delivered into the contralateral JV by femoral vein approach. Transplanted PAVVs were studied by immediate and 3 months venograms. Animals were euthanized at 3 months, and jugular veins harvested to perform angioscopic evaluations in vitro. RESULTS: PAVV transplantation was successful in all nine animals. Good valve function with no reflux was observed on immediate and 3 months venograms in eight valves. The transplanted maximal JV diameter ranged from 10.2 mm to 15.4 mm (mean 13.1 +/- 1.5 mm). Venoscopic examination revealed intact, flexible, nonthickened valve leaflets in eight specimens. One PAVV exhibited normal function of one leaflet only; the other cusp was accidentally cut during the transplantation procedure. All transplanted autologous valves were free of thrombus and incorporated into the vein wall of the host vessel. CONCLUSION: This study demonstrated that autogenous valve transplants remained patent and competent without long-term anticoagulation for up to 3 months. The percutaneous autogenous venous valve may provide in future minimally invasive treatment for patients with chronic deep venous insufficiency, but long-term studies need to be done to document its continued patency and function.

Anisotropic diffusion at the field scale in a 4-year multi-tracer diffusion and retention experiment – I: Insights from the experimental data

Abstract Claystones are considered worldwide as barrier materials for nuclear waste repositories. In the Mont Terri underground research laboratory (URL), a nearly 4-year diffusion and retention (DR) experiment has been performed in Opalinus Clay. It aimed at (1) obtaining data at larger space and time scales than in laboratory experiments and (2) under relevant in situ conditions with respect to pore water chemistry and mechanical stress, (3) quantifying the anisotropy of in situ diffusion, and (4) exploring possible effects of a borehole-disturbed zone. The experiment included two tracer injection intervals in a borehole perpendicular to bedding, through which traced artificial pore water (APW) was circulated, and a pressure monitoring interval. The APW was spiked with neutral tracers (HTO, HDO, H2O-18), anions (Br, I, SeO4), and cations (Na-22, Ba-133, Sr-85, Cs-137, Co-60, Eu-152, stable Cs, and stable Eu). Most tracers were added at the beginning, some were added at a later stage. The hydraulic pressure in the injection intervals was adjusted according to the measured value in the pressure monitoring interval to ensure transport by diffusion only. Concentration time-series in the APW within the borehole intervals were obtained, as well as 2D concentration distributions in the rock at the end of the experiment after overcoring and subsampling which resulted in �250 samples and �1300 analyses. As expected, HTO diffused the furthest into the rock, followed by the anions (Br, I, SeO4) and by the cationic sorbing tracers (Na-22, Ba-133, Cs, Cs-137, Co-60, Eu-152). The diffusion of SeO4 was slower than that of Br or I, approximately proportional to the ratio of their diffusion coefficients in water. Ba-133 diffused only into �0.1 m during the �4 a. Stable Cs, added at a higher concentration than Cs-137, diffused further into the rock than Cs-137, consistent with a non-linear sorption behavior. The rock properties (e.g., water contents) were rather homogeneous at the centimeter scale, with no evidence of a borehole-disturbed zone. In situ anisotropy ratios for diffusion, derived for the first time directly from field data, are larger for HTO and Na-22 (�5) than for anions (�3�4 for Br and I). The lower ionic strength of the pore water at this location (�0.22 M) as compared to locations of earlier experiments in the Mont Terri URL (�0.39 M) had no notable effect on the anion accessible pore fraction for Cl, Br, and I: the value of 0.55 is within the range of earlier data. Detailed transport simulations involving different codes will be presented in a companion paper.

The effects of endothelin-1 on coronary perfusion pressure during cardiopulmonary resuscitation in a canine model

OBJECTIVE To study the hemodynamic effects of exogenously administered endothelin-1 (ET-1), a peptide produced by endothelial cells with potent non-adrenergically mediated vasoconstrictor properties. METHODS A prospective drug intervention study was carried out in a resuscitation research laboratory. Fifteen mixed-breed dogs were anesthetized and instrumented for hemodynamic monitoring. Asphyxia arrest was produced by clamping the endotracheal tube. Hemodynamic data were collected continuously. Following loss of aortic fluctuations monitored by thoracic aortic catheter, the animals remained in pulseless electrical activity (PEA) for 10 minutes. After 10 minutes of no-flow PEA, closed-chest CPR was begun and the animals were randomized to one of three treatment groups (EPI, 0.02 mg/kg epinephrine IV every 3 minutes; ENDO, 100 micrograms ET-1 IV at 0 minutes; and EPI/ENDO, a combination of the EPI and ENDO treatments). RESULTS ENDO and EPI alone produced similar coronary perfusion pressures (CPPs). The EPI/ENDO combination produced significantly improved CPP compared with that of either EPI or ENDO alone. In the EPI group, the best mean CPP was 16 +/- 14 mm Hg and occurred 7 minutes after drug administration. In the ENDO group, the best mean CPP was 28 +/- 7 mm Hg and occurred 13 minutes after drug administration. In the EPI/ENDO combination group, the best mean CPP was 61 +/- 37 mm Hg and occurred 7 minutes after drug administration (p < 0.05 compared with the EPI and ENDO groups alone). CONCLUSION ET-1 is a potent vasoconstrictor. The combination of EPI and ENDO significantly improved CPP compared with that for either agent alone. ET-1 should be investigated further as a vasoconstrictor in cardiac arrest.

Identification of Sleep-Modulated Pathways Involved in Neuroprotection from Stroke.

STUDY OBJECTIVES Sleep deprivation (SDp) performed before stroke induces an ischemic tolerance state as observed in other forms of preconditioning. As the mechanisms underlying this effect are not well understood, we used DNA oligonucleotide microarray analysis to identify the genes and the gene-pathways underlying SDp preconditioning effects. DESIGN Gene expression was analyzed 3 days after stroke in 4 experimental groups: (i) SDp performed before focal cerebral ischemia (IS) induction; (ii) SDp performed before sham surgery; (iii) IS without SDp; and (iv) sham surgery without SDp. SDp was performed by gentle handling during the last 6 h of the light period, and ischemia was induced immediately after. SETTINGS Basic sleep research laboratory. MEASUREMENTS AND RESULTS Stroke induced a massive alteration in gene expression both in sleep deprived and non-sleep deprived animals. However, compared to animals that underwent ischemia alone, SDp induced a general reduction in transcriptional changes with a reduction in the upregulation of genes involved in cell cycle regulation and immune response. Moreover, an upregulation of a new neuroendocrine pathway which included melanin concentrating hormone, glycoprotein hormones-α-polypeptide and hypocretin was observed exclusively in rats sleep deprived before stroke. CONCLUSION Our data indicate that sleep deprivation before stroke reprogrammed the signaling response to injury. The inhibition of cell cycle regulation and inflammation are neuroprotective mechanisms reported also for other forms of preconditioning treatment, whereas the implication of the neuroendocrine function is novel and has never been described before. These results therefore provide new insights into neuroprotective mechanisms involved in ischemic tolerance mechanisms.