A general threshold stress hybrid hazard model for lifetime data

In this paper we propose a hybrid hazard regression model with threshold stress which includes the proportional hazards and the accelerated failure time models as particular cases. To express the behavior of lifetimes the generalized-gamma distribution is assumed and an inverse power law model with a threshold stress is considered. For parameter estimation we develop a sampling-based posterior inference procedure based on Markov Chain Monte Carlo techniques. We assume proper but vague priors for the parameters of interest. A simulation study investigates the frequentist properties of the proposed estimators obtained under the assumption of vague priors. Further, some discussions on model selection criteria are given. The methodology is illustrated on simulated and real lifetime data set.

Treatment modalities for T1N0 esophageal cancers: a comparative analysis of local therapy versus surgical resection

BACKGROUND To investigate the role of nonsurgical treatment for early-stage esophageal cancer, we compared the outcomes of local therapy to esophagectomy, using a large, national database. METHODS Five-year cancer-specific and overall survival (OS) of patients, with T1N0M0 squamous cell or adenocarcinoma of the mid or distal esophagus treated with either surgery or local therapy, with ablative and/or excision techniques, in the Surveillance Epidemiology and End Results cancer registry from 1998 to 2008, were compared using the Kaplan-Meier approach, and multivariable and propensity-score adjusted Cox proportional hazard, and competing risk models. RESULTS Of 1458 patients with T1N0 esophageal cancer, 1204 (83%) had surgery and 254 (17%) had local therapy only. The use of local therapy increased significantly from 8.1% in 1998 to 24.1% in 2008 (p < 0.001). The 5-year OS after local excisional therapy and surgery was not significantly different (55.5% versus 64.1% respectively, p = 0.07), and 5-year cancer-specific survival (CSS) also did not differ (81.7% versus 75.8%, p = 0.10). However, after propensity-score adjustment, CSS was better for patients who underwent local therapy compared with those who underwent surgery (hazard ratio: 0.46, 95% confidence interval: 0.27-0.77, p = 0.003), whereas OS remained similar. CONCLUSION The use of local therapy for T1N0 esophageal cancers increased significantly from 1998 to 2008. Compared with those treated with esophagectomy, patients treated with local therapy had similar OS but improved CSS, indicating a higher chance of dying from other causes. Further studies are needed to confirm the oncologic efficacy of local therapy when used in patients whose lifespans are not limited by conditions other than esophageal cancer.

Parametric accelerated failure time models with random effects and an application to kidney transplant survival

Accelerated failure time models with a shared random component are described, and are used to evaluate the effect of explanatory factors and different transplant centres on survival times following kidney transplantation. Different combinations of the distribution of the random effects and baseline hazard function are considered and the fit of such models to the transplant data is critically assessed. A mixture model that combines short- and long-term components of a hazard function is then developed, which provides a more flexible model for the hazard function. The model can incorporate different explanatory variables and random effects in each component. The model is straightforward to fit using standard statistical software, and is shown to be a good fit to the transplant data. Copyright (C) 2004 John Wiley Sons, Ltd.

Rank regression for accelerated failure time model with clustered and censored data

For clustered survival data, the traditional Gehan-type estimator is asymptotically equivalent to using only the between-cluster ranks, and the within-cluster ranks are ignored. The contribution of this paper is two fold: - (i) incorporating within-cluster ranks in censored data analysis, and; - (ii) applying the induced smoothing of Brown and Wang (2005, Biometrika) for computational convenience. Asymptotic properties of the resulting estimating functions are given. We also carry out numerical studies to assess the performance of the proposed approach and conclude that the proposed approach can lead to much improved estimators when strong clustering effects exist. A dataset from a litter-matched tumorigenesis experiment is used for illustration.

On the Accelerated Failure Time Model for Current Status and Interval Censored Data

This paper introduces a novel approach to making inference about the regression parameters in the accelerated failure time (AFT) model for current status and interval censored data. The estimator is constructed by inverting a Wald type test for testing a null proportional hazards model. A numerically efficient Markov chain Monte Carlo (MCMC) based resampling method is proposed to simultaneously obtain the point estimator and a consistent estimator of its variance-covariance matrix. We illustrate our approach with interval censored data sets from two clinical studies. Extensive numerical studies are conducted to evaluate the finite sample performance of the new estimators.

A joint hazard and time scaling model to compare survival curves.

To provide a more general method for comparing survival experience, we propose a model that independently scales both hazard and time dimensions. To test the curve shape similarity of two time-dependent hazards, h1(t) and h2(t), we apply the proposed hazard relationship, h12(tKt)/ h1(t) = Kh, to h1. This relationship doubly scales h1 by the constant hazard and time scale factors, Kh and Kt, producing a transformed hazard, h12, with the same underlying curve shape as h1. We optimize the match of h12 to h2 by adjusting Kh and Kt. The corresponding survival relationship S12(tKt) = [S1(t)]KtKh transforms S1 into a new curve S12 of the same underlying shape that can be matched to the original S2. We apply this model to the curves for regional and local breast cancer contained in the National Cancer Institute's End Results Registry (1950-1973). Scaling the original regional curves, h1 and S1 with Kt = 1.769 and Kh = 0.263 produces transformed curves h12 and S12 that display congruence with the respective local curves, h2 and S2. This similarity of curve shapes suggests the application of the more complete curve shapes for regional disease as templates to predict the long-term survival pattern for local disease. By extension, this similarity raises the possibility of scaling early data for clinical trial curves according to templates of registry or previous trial curves, projecting long-term outcomes and reducing costs. The proposed model includes as special cases the widely used proportional hazards (Kt = 1) and accelerated life (KtKh = 1) models.

In vivo and in vitro models demonstrate a role for caveolin-1 in the pathogenesis of ischaemic acute renal failure

Caveolae and their proteins, the caveolins, transport macromolecules; compartmentalize signalling molecules; and are involved in various repair processes. There is little information regarding their role in the pathogenesis of significant renal syndromes such as acute renal failure (ARF). In this study, an in vivo rat model of 30 min bilateral renal ischaemia followed by reperfusion times from 4 h to 1 week was used to map the temporal and spatial association between caveolin-1 and tubular epithelial damage (desquamation, apoptosis, necrosis). An in vitro model of ischaemic ARF was also studied, where cultured renal tubular epithelial cells or arterial endothelial cells were subjected to injury initiators modelled on ischaemia-reperfusion (hypoxia, serum deprivation, free radical damage or hypoxia-hyperoxia). Expression of caveolin proteins was investigated using immunohistochemistry, immunoelectron microscopy, and immunoblots of whole cell, membrane or cytosol protein extracts. In vivo, healthy kidney had abundant caveolin-1 in vascular endothelial cells and also some expression in membrane surfaces of distal tubular epithelium. In the kidneys of ARF animals, punctate cytoplasmic localization of caveolin-1 was identified, with high intensity expression in injured proximal tubules that were losing basement membrane adhesion or were apoptotic, 24 h to 4 days after ischaemia-reperfusion. Western immunoblots indicated a marked increase in caveolin-1 expression in the cortex where some proximal tubular injury was located. In vitro, the main treatment-induced change in both cell types was translocation of caveolin-1 from the original plasma membrane site into membrane-associated sites in the cytoplasm. Overall, expression levels did not alter for whole cell extracts and the protein remained membrane-bound, as indicated by cell fractionation analyses. Caveolin-1 was also found to localize intensely within apoptotic cells. The results are indicative of a role for caveolin-1 in ARF-induced renal injury. Whether it functions for cell repair or death remains to be elucidated.

Failure detectors and communication efficiency in the crash and general omisión failure models

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Association of Caveolin-1 gene polymorphism with kidney transplant fibrosis and allograft failure

Context: Caveolin-1 (CAV1) is an inhibitor of tissue fibrosis.
Objective: To study the association of CAV1 gene variation with kidney transplant outcome, using kidney transplantation as a model of accelerated fibrosis.
Design, Setting, and Patients: Candidate gene association and validation study. Genomic DNA from 785 white kidney transplant donors and their respective recipients (transplantations in Birmingham, England, between 1996 and 2006; median followup, 81 months) were analyzed for common variation in CAV1 using a singlenucleotide polymorphism (SNP) tagging approach. Validation of positive findings was sought in an independent kidney transplant donor-recipient cohort (transplantations in Belfast, Northern Ireland, between 1986 and 2005; n=697; median follow-up, 69 months). Association between genotype and allograft failure was initially assessed by Kaplan-Meier analysis, then in an adjusted Cox model.
Main Outcome Measure: Death-censored allograft failure, defined as a return to dialysis or retransplantation.
Results: The presence of donor AA genotype for the CAV1 rs4730751 SNP was associated with increased risk of allograft failure in the Birmingham group (donor AA vs non-AA genotype in adjusted Cox model, hazard ratio [HR], 1.97; 95% confidence interval [CI], 1.29-3.16; P=.002). No other tag SNPs showed a significant association. This finding was validated in the Belfast cohort (in adjusted Cox model, HR, 1.56; 95% CI, 1.07-2.27; P=.02). Overall graft failure rates were as follows: for the Birmingham cohort, donor genotype AA, 22 of 57 (38.6%); genotype CC, 96 of 431 (22.3%); and genotype AC, 66 of 297 (22.2%); and for the Belfast cohort, donor genotype AA, 32 of 48 (67%); genotype CC, 150 of 358 (42%); and genotype AC, 119 of 273 (44%).
Conclusion: Among kidney transplant donors, the CAV1 rs4730751 SNP was significantly associated with allograft failure in 2 independent cohorts.

Co-ordination failure, moral hazard and sovereign bankruptcy procedures

We study a model of sovereign debt crisis that combines problems of creditor coordination and debtor moral hazard. Solving the sovereign debtor's incentives leads to excessive 'rollover failure' by creditors when sovereign default occurs. We discuss how the incidence of crises might be reduced by international sovereign bankruptcy procedures and relate this to the current debate on revising international financial architecture. Paper prepared for Bank of England Conference on "The Role of the Official and Private Sectors in Resolving International Financial Crises", London, and for the Latin American Meeting of the Econometric Society, Sao Paolo, Brazil. (Preliminary draft circulated for comments, please do not cite without reference to the authors).

Tests of proportional hazards and proportional odds models for grouped survival data

In this paper, we derive score test statistics to discriminate between proportional hazards and proportional odds models for grouped survival data. These models are embedded within a power family transformation in order to obtain the score tests. In simple cases, some small-sample results are obtained for the score statistics using Monte Carlo simulations. Score statistics have distributions well approximated by the chi-squared distribution. Real examples illustrate the proposed tests.

Choosing between Cox proportional hazards and logistic models for interval-censored data via bootstrap

This work develops a new methodology in order to discriminate models for interval-censored data based on bootstrap residual simulation by observing the deviance difference from one model in relation to another, according to Hinde (1992). Generally, this sort of data can generate a large number of tied observations and, in this case, survival time can be regarded as discrete. Therefore, the Cox proportional hazards model for grouped data (Prentice & Gloeckler, 1978) and the logistic model (Lawless, 1982) can befitted by means of generalized linear models. Whitehead (1989) considered censoring to be an indicative variable with a binomial distribution and fitted the Cox proportional hazards model using complementary log-log as a link function. In addition, a logistic model can be fitted using logit as a link function. The proposed methodology arises as an alternative to the score tests developed by Colosimo et al. (2000), where such models can be obtained for discrete binary data as particular cases from the Aranda-Ordaz distribution asymmetric family. These tests are thus developed with a basis on link functions to generate such a fit. The example that motivates this study was the dataset from an experiment carried out on a flax cultivar planted on four substrata susceptible to the pathogen Fusarium oxysoprum. The response variable, which is the time until blighting, was observed in intervals during 52 days. The results were compared with the model fit and the AIC values.

Nephron number, hypertension, renal disease, and renal failure

Essential hypertension is one of the most common diseases in the Western world, affecting about 26.4% of the adult population, and it is increasing (1). Its causes are heterogeneous and include genetic and environmental factors (2), but several observations point to an important role of the kidney in its genesis (3). In addition to variations in tubular transport mechanisms that could, for example, affect salt handling, structural characteristics of the kidney might also contribute to hypertension. The burden of chronic kidney disease is also increasing worldwide, due to population growth, increasing longevity, and changing risk factors. Although single-cause models of disease are still widely promoted, multideterminant or multihit models that can accommodate multiple risk factors in an individual or in a population are probably more applicable (4,5). In such a framework, nephron endowment is one potential determinant of disease susceptibility. Some time ago, Brenner and colleagues (6,7) proposed that lower nephron numbers predispose both to essential hypertension and to renal disease. They also proposed that hypertension and progressive renal insufficiency might be initiated and accelerated by glomerular hypertrophy and intraglomerular hypertension that develops as nephron number is reduced (8). In this review, we summarize data from recent studies that shed more light on these hypotheses. The data supply a new twist to possible mechanisms of the Barker hypothesis, which proposes that intrauterine growth retardation predisposes to chronic disease in later life (9). The review describes how nephron number is estimated and its range and some determinants and morphologic correlates. It then considers possible causes of low nephron numbers. Finally, associations of hypertension and renal disease with reduced nephron numbers are considered, and some potential clinical implications are discussed.