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When comparing survival times between two treatment groups, it may be more appropriate to compare the restricted mean lifetime, i.e., the expectation of lifetime restricted to a time L, rather than mean lifetime in order to accommodate censoring. When the treatments are not assigned to patients randomly, as in observational studies, we also need to account for treatment imbalances in confounding factors. In this article, we propose estimators for the difference of the restricted mean lifetime between two groups that account for treatment imbalances in prognostic factors assuming a proportional hazards relationship. Large-sample properties of our estimators based on martingale theory for counting processes are also derived. Simulation studies were conducted to compare these estimators and to assess the adequacy of the large-sample approximations. Our methods are also applied to an observational database of acute coronary syndrome patients from Duke University Medical Center to estimate the treatment effect on the restricted mean lifetime over 5 years. 相似文献
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Summary Nested case–control (NCC) design is a popular sampling method in large epidemiological studies for its cost effectiveness to investigate the temporal relationship of diseases with environmental exposures or biological precursors. Thomas' maximum partial likelihood estimator is commonly used to estimate the regression parameters in Cox's model for NCC data. In this article, we consider a situation in which failure/censoring information and some crude covariates are available for the entire cohort in addition to NCC data and propose an improved estimator that is asymptotically more efficient than Thomas' estimator. We adopt a projection approach that, heretofore, has only been employed in situations of random validation sampling and show that it can be well adapted to NCC designs where the sampling scheme is a dynamic process and is not independent for controls. Under certain conditions, consistency and asymptotic normality of the proposed estimator are established and a consistent variance estimator is also developed. Furthermore, a simplified approximate estimator is proposed when the disease is rare. Extensive simulations are conducted to evaluate the finite sample performance of our proposed estimators and to compare the efficiency with Thomas' estimator and other competing estimators. Moreover, sensitivity analyses are conducted to demonstrate the behavior of the proposed estimator when model assumptions are violated, and we find that the biases are reasonably small in realistic situations. We further demonstrate the proposed method with data from studies on Wilms' tumor. 相似文献
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Lu B 《Biometrics》2005,61(3):721-728
In observational studies with a time-dependent treatment and time-dependent covariates, it is desirable to balance the distribution of the covariates at every time point. A time-dependent propensity score based on the Cox proportional hazards model is proposed and used in risk set matching. Matching on this propensity score is shown to achieve a balanced distribution of the covariates in both treated and control groups. Optimal matching with various designs is conducted and compared in a study of a surgical treatment, cystoscopy and hydrodistention, given in response to a chronic bladder disease, interstitial cystitis. Simulation studies also suggest that the statistical analysis after matching outperforms the analysis without matching in terms of both point and interval estimations. 相似文献
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Differing reproductive effort, individual qualities and local environmental conditions can lead to uneven mortality risk among individuals within populations and may result in survival differences according to age and sex. Identification of factors contributing to unequal operational sex ratios has been important for understanding population dynamics and conservation management. In this study, sex‐ and age‐specific mortality was estimated in three wild Grey Partridge populations from analysis of year‐round radiotracking data from 168 individuals. Survival days were counted in three periods defined individually for each bird: the pairing period (covey break‐up to laying of the first egg); the nesting period (between clutch initiation date and failure of the last nesting attempt, or the date when chicks were 14 days old); and the covey period (the end of the nesting period or joining a group until covey break‐up). Predation was the main cause of mortality. A significant effect of age on survival was found during the pairing period, when older individuals paired off faster and survived better. The highest mortality risk overall was found during the nesting period. Furthermore, significantly higher mortality of females was recorded during the nesting period, suggesting that greater investments in reproduction, behaviour at the nest or the quality of nesting habitats can decrease survival of females and cause a male‐skewed sex ratio. No significant effect of age or sex was found during the covey period, or for the year as a whole, but there was a significant difference in annual mortality rates between the three study populations. Our results confirm age‐ and sex‐specific variation of adult mortality in a ground‐nesting bird with biparental care during the annual cycle, documenting differing sensitivities of various population cohorts to predation. 相似文献
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PurposeThis study explored a novel homological analysis method for prognostic prediction in lung cancer patients.Materials and methodsThe potential of homology-based radiomic features (HFs) was investigated by comparing HFs to conventional wavelet-based radiomic features (WFs) and combined radiomic features consisting of HFs and WFs (HWFs), using training (n = 135) and validation (n = 70) datasets, and Kaplan–Meier analysis. A total of 13,824 HFs were derived through homology-based texture analysis using Betti numbers, which represent the topologically invariant morphological characteristics of lung cancer. The prognostic potential of HFs was evaluated using statistically significant differences (p-values, log-rank test) to compare the survival curves of high- and low-risk patients. Those patients were stratified into high- and low-risk groups using the medians of the radiomic scores of signatures constructed with an elastic-net-regularized Cox proportional hazard model. Furthermore, deep learning (DL) based on AlexNet was utilized to compare HFs by stratifying patients into the two groups using a network that was pre-trained with over one million natural images from an ImageNet database.ResultsFor the training dataset, the p-values between the two survival curves were 6.7 × 10−6 (HF), 5.9 × 10−3 (WF), 7.4 × 10−6 (HWF), and 1.1 × 10−3 (DL). The p-values for the validation dataset were 3.4 × 10−5 (HF), 6.7 × 10−1 (WF), 1.7 × 10−7 (HWF), and 1.2 × 10−1 (DL).ConclusionThis study demonstrates the excellent potential of HFs for prognostic prediction in lung cancer patients. 相似文献
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Nested case‐control designs are attractive in studies with a time‐to‐event endpoint if the outcome is rare or if interest lies in evaluating expensive covariates. The appeal is that these designs restrict to small subsets of all patients at risk just prior to the observed event times. Only these small subsets need to be evaluated. Typically, the controls are selected at random and methods for time‐simultaneous inference have been proposed in the literature. However, the martingale structure behind nested case‐control designs allows for more powerful and flexible non‐standard sampling designs. We exploit that structure to find simultaneous confidence bands based on wild bootstrap resampling procedures within this general class of designs. We show in a simulation study that the intended coverage probability is obtained for confidence bands for cumulative baseline hazard functions. We apply our methods to observational data about hospital‐acquired infections. 相似文献
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AIDS Clinical Trial Group (ACTG) randomized trial 021 compared the effect of bactrim versus aerosolized pentamidine (AP) as prophylaxis therapy for pneumocystis pneumonia (PCP) in AIDS patients. Although patients randomized to the bactrim arm experienced a significant delay in time to PCP, the survival experience in the two arms was not significantly different (p = .32). In this paper, we present evidence that bactrim therapy improves survival but that the standard intent-to-treat comparison failed to detect this survival advantage because a large fraction of the subjects either crossed over to the other therapy or stopped therapy altogether. We obtain our evidence of a beneficial bactrim effect on survival by artificially regarding the subjects as dependently censored at the first time the subject either stops or switches therapy; we then analyze the data with the inverse probability of censoring weighted Kaplan-Meier and Cox partial likelihood estimators of Robins (1993, Proceedings of the Biopharmaceutical Section, American Statistical Association, pp. 24-33) that adjust for dependent censoring by utilizing data collected on time-dependent prognostic factors. 相似文献
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Aileigh Kay Jason B. Coe Ian Young David Pearl 《Journal of applied animal welfare science : JAAWS》2018,21(4):375-388
Millions of companion animals are relinquished to shelters each year. For each dog entering, their characteristics and the characteristics of the shelter holding him/her influence their time to adoption. Using a Cox proportional hazards frailty model, these issues were explored using data from 31 shelters within the British Columbia Society for the Prevention of Cruelty to Animals shelter system. Results indicated that surrender reason, age, original source, coat color, breed, human population density of the shelter location, and year the nonhuman animal entered the shelter significantly influenced time to adoption. This study identified characteristics of dogs that make them less likely to be adopted quickly. Given limited resources, these results may help inform shelters on how to best allocate resources, particularly in interventions to improve adoption rates in shelters. 相似文献
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Recently, personalized medicine has received great attention to improve safety and effectiveness in drug development. Personalized medicine aims to provide medical treatment that is tailored to the patient's characteristics such as genomic biomarkers, disease history, etc., so that the benefit of treatment can be optimized. Subpopulations identification is to divide patients into several different subgroups where each subgroup corresponds to an optimal treatment. For two subgroups, traditionally the multivariate Cox proportional hazards model is fitted and used to calculate the risk score when outcome is survival time endpoint. Median is commonly chosen as the cutoff value to separate patients. However, using median as the cutoff value is quite subjective and sometimes may be inappropriate in situations where data are imbalanced. Here, we propose a novel tree‐based method that adopts the algorithm of relative risk trees to identify subgroup patients. After growing a relative risk tree, we apply k‐means clustering to group the terminal nodes based on the averaged covariates. We adopt an ensemble Bagging method to improve the performance of a single tree since it is well known that the performance of a single tree is quite unstable. A simulation study is conducted to compare the performance between our proposed method and the multivariate Cox model. The applications of our proposed method to two public cancer data sets are also conducted for illustration. 相似文献
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Cheryl A. Johnson John M. Fryxell Ian D. Thompson James A. Baker 《Proceedings. Biological sciences / The Royal Society》2009,276(1671):3361-3367
The assumption that mortality risk increases with dispersal distance has rarely been tested. We compared patterns of natal dispersal in the American marten (Martes americana) between a large regenerating forest landscape and an uncut landscape that was dominated by more mature forest to test whether mortality risk increased with dispersal distance, and whether variation in mortality risk influenced dispersal distance. Mortality risk increased with dispersal distance in both landscape treatments, but the distance-dependent increase in mortality in the regenerating landscape was twice that in the uncut landscape. Differences in body condition, supported by other data on foraging efficiency, suggested that juveniles from the regenerating landscape were less able to cope with the energetic demands of dispersal compared with juveniles from older forests. Juveniles travelled shorter distances in the regenerating versus uncut landscape. These results implied that dispersal was costly in terms of juvenile survival and that mean dispersal distance was shaped, in part, by mortality risk. 相似文献
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Young Min Kim John B. Cologne Euna Jang Theis Lange Yoshimi Tatsukawa Waka Ohishi Mai Utada Harry M. Cullings 《Biometrical journal. Biometrische Zeitschrift》2020,62(8):1939-1959
The paper proposes an approach to causal mediation analysis in nested case-control study designs, often incorporated with countermatching schemes using conditional likelihood, and we compare the method's performance to that of mediation analysis using the Cox model for the full cohort with a continuous or dichotomous mediator. Simulation studies are conducted to assess our proposed method and investigate the efficiency relative to the cohort. We illustrate the method using actual data from two studies of potential mediation of radiation risk conducted within the Adult Health Study cohort of atomic-bomb survivors. The performance becomes comparable to that based on the full cohort, illustrating the potential for valid mediation analysis based on the reduced data obtained through the nested case-control design. 相似文献
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Genetic epidemiologic studies often collect genotype data at multiple loci within a genomic region of interest from a sample of unrelated individuals. One popular method for analyzing such data is to assess whether haplotypes, i.e., the arrangements of alleles along individual chromosomes, are associated with the disease phenotype or not. For many study subjects, however, the exact haplotype configuration on the pair of homologous chromosomes cannot be derived with certainty from the available locus-specific genotype data (phase ambiguity). In this article, we consider estimating haplotype-specific association parameters in the Cox proportional hazards model, using genotype, environmental exposure, and the disease endpoint data collected from cohort or nested case-control studies. We study alternative Expectation-Maximization algorithms for estimating haplotype frequencies from cohort and nested case-control studies. Based on a hazard function of the disease derived from the observed genotype data, we then propose a semiparametric method for joint estimation of relative-risk parameters and the cumulative baseline hazard function. The method is greatly simplified under a rare disease assumption, for which an asymptotic variance estimator is also proposed. The performance of the proposed estimators is assessed via simulation studies. An application of the proposed method is presented, using data from the Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study. 相似文献
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We study a hybrid model that combines Cox proportional hazards regression with tree-structured modeling. The main idea is to use step functions, provided by a tree structure, to 'augment' Cox (1972) proportional hazards models. The proposed model not only provides a natural assessment of the adequacy of the Cox proportional hazards model but also improves its model fitting without loss of interpretability. Both simulations and an empirical example are provided to illustrate the use of the proposed method. 相似文献
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Heiko Becher Göran Kauermann Pavel Khomski Bocar Kouyaté 《Biometrical journal. Biometrische Zeitschrift》2009,51(1):110-122
Several previous studies have identified risk factors for childhood mortality in high risk areas, such as Sub‐Saharan Africa. Among these are lifestyle factors related for example to nutrition or sanitation. Other factors are related to social class, ethnicity and poverty in general. Few studies have investigated a dependence of these factors by age and season of birth which is the focus in this study. We perform a survival analysis of 9121 children born between 1998 and 2001 in a rural area of western Burkina Faso. The whole population is under demographic surveillance since 1993. All cause mortality is used as the endpoint and follow‐up information until the age of five years is available. Recently developed spline regression methods are used for the analysis. Ethnic group, religion, age of mother, twin status, sex, and distance to next health center are used as covariates all of which having a clear effect on survival in standard Cox regression analysis. With penalized spline regression, a more detailed risk pattern is observed. Ethnicity is more related to death at early age, as well as age of mother. The effect of the risk factors considered also appear to be related with season of birth (© 2009 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim) 相似文献
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