Why do transplant surgeons turn down organs? A model of the accept/reject decision

Despite the scarcity of transplantable organs, 45% of livers are rejected by the first surgeon to whom they are offered. I present a model in which a surgeon decides to accept or reject an organ for a patient based on the patient's current health level. Using data on transplanted patients, I show that surgeons' behavior is consistent with the solution to an optimal stopping problem in which they reject low quality organs for relatively healthy patients in the hope that they will receive a better organ offer in the future. I discuss trends in organ procurement in light of this finding.     

Population toxicokinetic analysis of 2,3,7,8-tetrachlorodibenzo-p-dioxin using Bayesian techniques

Understanding the kinetics of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) concentrations in humans is an important step for TCDD cancer risk assessment. In this paper longitudinal series of serum TCDD concentration measurements on U.S. veterans of the Vietnam war, who were exposed to dioxin during herbicide-spraying operations, are studied. The overall aim is to use these data to infer the dynamics of TCDD concentrations in humans. This is done by identifying a kinetic model describing the dioxin time course at the individual level. The individual toxicokinetic model is then expanded into a population model within a Bayesian hierarchical framework which allows residual variations across subjects that cannot be explained by observed covariates. Other complications in the data, such as unknown exposure histories, are also resolved implicitly through the hierarchical model. Moreover, the choice of a Bayesian approach enables the accumulation of external source of information in the form of prior distributions. The model is subjected to various diagnostic checks and analyses of sensitivity to distributional assumptions showing a good fit in terms of both the population and the kinetic features.     

Functional data analysis with application to periodically stimulated foetal heart rate data. II: functional logistic regression

We present a basis solution for the modelling of a binary response with a functional covariate plus any number of scalar covariates. This can be thought of as singular longitudinal data analysis as there are more measurements on the functional covariate than subjects in the study. The maximum likelihood parameter estimates are found using a basis expansion and a modified Fisher scoring algorithm. This technique has been extended to model a functional covariate with a repeated stimulus. We used periodically stimulated foetal heart rate tracings to predict the probability of a high risk birth outcome. It was found that these tracings could predict 94.1 per cent of the high risk pregnancies and without the stimulus, the heart rates were no more predictive than chance.     

Estimating risk and rate levels,ratios and differences in case-control studies

Classic (or 'cumulative') case-control sampling designs do not admit inferences about quantities of interest other than risk ratios, and then only by making the rare events assumption. Probabilities, risk differences and other quantities cannot be computed without knowledge of the population incidence fraction. Similarly, density (or 'risk set') case-control sampling designs do not allow inferences about quantities other than the rate ratio. Rates, rate differences, cumulative rates, risks, and other quantities cannot be estimated unless auxiliary information about the underlying cohort such as the number of controls in each full risk set is available. Most scholars who have considered the issue recommend reporting more than just risk and rate ratios, but auxiliary population information needed to do this is not usually available. We address this problem by developing methods that allow valid inferences about all relevant quantities of interest from either type of case-control study when completely ignorant of or only partially knowledgeable about relevant auxiliary population information.     

Jointly modelling the relationship between survival and pulmonary function in cystic fibrosis patients

Modelling the relationship between pulmonary function and survival in cystic fibrosis (CF) is complicated by the fact that measures of pulmonary function commonly used such as the forced expiratory volume in one second (FEV(1)) are measured with error, and patients with the poorest lung function are increasingly censored by death, that is, data are available only for the patients who have survived to the current age. We assume a linear random effects model for FEV1 per cent predicted, where the random intercept and slope of FEV(1) per cent predicted, along with a specified transformation of the age at death follow a trivariate normal distribution. We illustrate how this model can be used to describe the relationship between age at death and parameters of the individual patient's regression of FEV(1) per cent predicted versus age, such as the slope and the intercept or true value of FEV(1) per cent predicted at a given age. We also illustrate how the model provides empirical Bayes estimates of these individual parameters. In particular, we explore how the predicted value of the age at death might be used as a prognostic or severity index. The model and methods are illustrated on a cohort of 188 cystic fibrosis patients with a common genotype (homozygous for the DeltaF508 mutation), born on or after 1965 and followed at the CF Center at the Rainbow Babies and Children's Hospital, Cleveland, OH, U.S.A.     

IL-2和IL-12基因联合治疗小鼠头颈鳞癌的实验研究

目的观察白细胞介素-2(IL-2)基因与白细胞介素-12(IL-12)基因联合治疗小鼠头颈鳞癌的疗效. 方法建立小鼠头颈鳞癌动物模型,在荷瘤部位将脂质体包裹的IL-2基因和IL-12基因直接注入肿瘤中,观察肿瘤大小变化,并检测此两种基因在肿瘤细胞中的蛋白表达情况、小鼠脾脏自然杀伤细胞(NK)和细胞毒T淋巴细胞(CTL)活性. 结果 IL-2基因和IL-12基因联合治疗组,肿瘤生长明显受抑制,疗效显著优于单独治疗组和对照组(P<0.01).在注射有IL-2、IL-12基因的肿瘤组织中,其相对应的IL-2、IL- 12蛋白水平明显升高,小鼠脾细胞NK活性和CTL杀伤活性增强. 结论 IL-2、IL-12基因治疗可抑制小鼠头颈鳞癌生长,提高机体的抗肿瘤免疫应答.二者联合应用,可产生协同效应并加强其抗肿瘤效果.     

Biological mechanisms in the relationship between depression and heart disease

Psychological depression is shown to be associated with several aspects of coronary artery disease (CAD), including arrhythmias, myocardial infarction, heart failure and sudden death. The physiological mechanisms accounting for this association are unclear. Hypothalamic–pituitary–adrenal dysregulation, diminished heart rate variability, altered blood platelet function and noncompliance with medial treatments have been proposed as mechanisms underlying depression and cardiovascular disease. Recent evidence also suggests that reduced baroreflex sensitivity, impaired immune function, chronic fatigue and the co-morbidity of depression and anxiety may be involved in the relationship between depression and cardiovascular dysregulation. An experimental strategy using animal models for investigating underlying physiological abnormalities in depression is presented. A key to understanding the bidirectional association between depression and heart disease is to determine whether there are common changes in brain systems that are associated with these conditions. Such approaches may hold promise for advancing our understanding of the interaction between this mood disorder and CAD.     

A morphometric evidence for a hyperfunctioning mesolimbic system in an animal model of ADHD

The hyperfunctioning dopamine hypothesis in the mesocorticolimbic (MCL) system has been addressed by a neurogenetic approach in model systems. Thus, a morphometric analysis was carried out on neurons of origin of Substantia Nigra (SN) and Ventral Tegmental Area (VTA) dopamine systems of the Naples High-Excitability (NHE), Low-Excitability (NLE) and control lines. Male adult rats were tested in a spatial novelty for indices of activity and non-selective attention. Mesencephalic coronal sections were processed for tyrosine hydroxylase (TH) immunohistochemistry and cytochromoxidase (C.O.) histochemistry. Image analysis in the rostro-caudal plane showed (i) a higher neuron size of TH+ elements in the VTA of NHE and NLE, across the entire structure in the NHE, and only in the middle portion in the NLE; (ii) a higher expression of TH in the neuropil of the VTA in NHE; (iii) a lower C.O. activity in both NLE and NHE; (iv) no differences in the SN. The larger neuron size in both NHE and NLE rats as compared with control rats, along with higher TH expression mainly in the NHE, in absence of any relevant alteration in the SN, reveals an unbalance between the two dopamine systems and a subsequent alteration in limbic (reward, motivation, sustained attention) functions. The decreased C.O. activity might be due to reduced feedback inhibition by striatal GABA neurons and interneurons leading to increased DA neuron firing. In conclusion, the increased behavioral activity and impaired attention observed in the NHE rats are associated to hyperfunctioning MCL system in this genetic model of Attention-Deficit Hyperactivity Disorder (ADHD).     

A Bayesian Hierarchical Approach to Comparative Audit for Carotid Surgery

OBJECTIVES: the aim of this study was to illustrate how a Bayesian hierarchical modelling approach can aid the reliable comparison of outcome rates between surgeons. DESIGN: retrospective analysis of prospective and retrospective data. MATERIALS: binary outcome data (death/stroke within 30 days), together with information on 15 possible risk factors specific for CEA were available on 836 CEAs performed by four vascular surgeons from 1992-99. The median patient age was 68 (range 38-86) years and 60% were men. METHODS: the model was developed using the WinBUGS software. After adjusting for patient-level risk factors, a cross-validatory approach was adopted to identify "divergent" performance. A ranking exercise was also carried out. RESULTS: the overall observed 30-day stroke/death rate was 3.9% (33/836). The model found diabetes, stroke and heart disease to be significant risk factors. There was no significant difference between the predicted and observed outcome rates for any surgeon (Bayesian p -value>0.05). Each surgeon had a median rank of 3 with associated 95% CI 1.0-5.0, despite the variability of observed stroke/death rate from 2.9-4.4%. After risk adjustment, there was very little residual between-surgeon variability in outcome rate. CONCLUSIONS: Bayesian hierarchical models can help to accurately quantify the uncertainty associated with surgeons' performance and rank.