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Multivariate survival data are frequently encountered in biomedical applications in the form of clustered failures (or recurrent events data). A popular way of analyzing such data is by using shared frailty models, which assume that the proportional hazards assumption holds conditional on an unobserved cluster-specific random effect. Such models are often incorporated in more complicated joint models in survival analysis. If the random effect distribution has finite expectation, then the conditional proportional hazards assumption does not carry over to the marginal models. It has been shown that, for univariate data, this makes it impossible to distinguish between the presence of unobserved heterogeneity (eg, due to missing covariates) and marginal nonproportional hazards. We show that time-dependent covariate effects may falsely appear as evidence in favor of a frailty model also in the case of clustered failures or recurrent events data, when the cluster size or number of recurrent events is small. When true unobserved heterogeneity is present, the presence of nonproportional hazards leads to overestimating the frailty effect. We show that this phenomenon is somewhat mitigated as the cluster size grows. We carry out a simulation study to assess the behavior of test statistics and estimators for frailty models in such contexts. The gamma, inverse Gaussian, and positive stable shared frailty models are contrasted using a novel software implementation for estimating semiparametric shared frailty models. Two main questions are addressed in the contexts of clustered failures and recurrent events: whether covariates with a time-dependent effect may appear as indication of unobserved heterogeneity and whether the additional presence of unobserved heterogeneity can be detected in this case. Finally, the practical implications are illustrated in a real-world data analysis example.  相似文献   
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Metabolomics may reveal novel insights into the etiology of prostate cancer, for which few risk factors are established. We investigated the association between patterns in baseline plasma metabolite profile and subsequent prostate cancer risk, using data from 3,057 matched case–control sets from the European Prospective Investigation into Cancer and Nutrition (EPIC). We measured 119 metabolite concentrations in plasma samples, collected on average 9.4 years before diagnosis, by mass spectrometry (AbsoluteIDQ p180 Kit, Biocrates Life Sciences AG). Metabolite patterns were identified using treelet transform, a statistical method for identification of groups of correlated metabolites. Associations of metabolite patterns with prostate cancer risk (OR1SD) were estimated by conditional logistic regression. Supplementary analyses were conducted for metabolite patterns derived using principal component analysis and for individual metabolites. Men with metabolite profiles characterized by higher concentrations of either phosphatidylcholines or hydroxysphingomyelins (OR1SD = 0.77, 95% confidence interval 0.66–0.89), acylcarnitines C18:1 and C18:2, glutamate, ornithine and taurine (OR1SD = 0.72, 0.57–0.90), or lysophosphatidylcholines (OR1SD = 0.81, 0.69–0.95) had lower risk of advanced stage prostate cancer at diagnosis, with no evidence of heterogeneity by follow-up time. Similar associations were observed for the two former patterns with aggressive disease risk (the more aggressive subset of advanced stage), while the latter pattern was inversely related to risk of prostate cancer death (OR1SD = 0.77, 0.61–0.96). No associations were observed for prostate cancer overall or less aggressive tumor subtypes. In conclusion, metabolite patterns may be related to lower risk of more aggressive prostate tumors and prostate cancer death, and might be relevant to etiology of advanced stage prostate cancer.  相似文献   
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Lesion evolution during focal cerebral ischemia may depend on flow restrictions or on accumulation of toxic mediators within the infarct and expansion of these factors to the periinfarct region. So far, the precise contribution of flow dependent versus spreading-mediated impairment of viable periinfarct tissue has not been determined. Therefore, we measured lesion expansion, flow restrictions and glutamate distribution on serial brain sections at different time points after experimental focal ischemia.Permanent focal ischemia was induced by occlusion of the right middle cerebral artery in male rats and the flow reduction was subsequently measured at 1, 12 and 24 h using iodo[14C]antipyrine autoradiography. Additionally, the necrotic volume was determined on serial brain sections and the glutamate content was measured in tissue samples from adjacent microdissections.Twelve hours after focal ischemia no noteworthy viable areas with blood flow restrictions of 20-40 ml 100 g− 1 min− 1 existed but at 24 h the necrotic tissue exceeded the hemodynamically compromised region by 40 ± 21 mm3 (24%). Furthermore, at 12 and 24 h the glutamate content was elevated in areas surrounding the infarct.Relevant flow restrictions are detectable only during early stages of infarct maturation, whereas the propagation of secondary factors may be the predominant mechanism for delayed infarct evolution.  相似文献   
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A 59-year-old hypertensive male, 1 year after uncomplicatedmitral annuloplasty for regurgitation with MAZE procedure, witha history of chronic obstructive pulmonary disease and repeatedpulmonary  相似文献   
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