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Results for “Bootstrap resampling”

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PubMed2000

Definition of individual bioequivalence: occasion-to-occasion versus mean switchability.

Two moment-based scaled definitions of individual bioequivalence are discussed. Based on a mixed effects linear model, their evaluations respectively lead to an unweighted (theta(11)) and a parametric (theta(15)) metric. The two metrics are estimated with respect to study design and two estimation methods. Results show that the two IBE metrics perform equivalently in the fully replicated design. In the semi-replicated design, the definition of theta(11) may not be valid while the evaluation of theta(15) results in a reduction of the weights in the mean difference and switchability components of the metric. Percentage rejection rates in the latter design indicate that theta(11) is more conservative than theta(15). This is because there is an increase of about 15 per cent in the producer risk in theta(11) relative to theta(15) compared to a 7 per cent increase in the consumer risk in theta(15) relative to theta(11). A further disadvantage of the design is that there is a 33 per cent loss in the subject-by-treatment variance efficiency which is reflected in a similar amount of decreased sensitivity to departures from perfect bioequivalence even when more subjects are used to equalize the number of exposure occasions in the two designs. It is concluded that a mean switchability criterion may be more appropriate from an interpretability perspective, the bootstrap resampling method used to evaluate individual bioequivalence based on theta(11) may need to be bias-corrected and that the semi-replicated design should be used cautiously.

Humans↗

PubMed2001

Non-parametric estimates of overlap.

Kernel densities provide accurate non-parametric estimates of the overlapping coefficient or the proportion of similar responses (PSR) in two populations. Non-parametric estimates avoid strong assumptions on the shape of the populations, such as normality or equal variance, and possess sampling variation approaching that of parametric estimates. We obtain accurate standard error estimates by bootstrap resampling. We illustrate the practical use of these methods in two examples and use simulations to explore the properties of the estimators under various sampling situations.

Acetates↗

PubMed2003

Cost-effectiveness and lung cancer clinical trials.

BACKGROUND: Lung cancer is the leading cause of cancer death in the U.S., with an estimated annual economic burden of $5 billion. Clinical trials offer innovative therapeutic options with potentially better outcomes, but their effects on health care costs are disputed. METHODS: The authors analyzed the 1-year facility-based treatment cost and survival of 336 newly diagnosed nonsmall cell lung cancer patients who were deemed eligible for clinical trials between 1994 and 1998 at the Karmanos Cancer Institute. The incremental cost-effectiveness ratio (ICER) of clinical trial treatments with adjustment for confounders was calculated along with its 95% confidence interval (CI) using the bootstrap resampling method. RESULTS: Of the 336 patients, 76 (22.6%) were treated on clinical trials. Trial participation was associated significantly with race (P < 0.01), gender (P = 0.01), age (P = 0.02), and insurance type (P = 0.02). The average 1-year cost for trial enrollees was $41,734 with a median survival of 1.3 years, whereas the average 1-year cost for nonenrollees was $34,191 with a median survival period of 0.9 years. Differences in survival and 1-year cost between enrollees and nonenrollees were significant when controlling for age, race, gender, insurance, stage, performance status, and comorbidities. The ICER for trial participation after adjustment for confounders was $9741 per life year saved (95% CI, $3089-$19,149). CONCLUSIONS: Enrollment in lung cancer clinical trials was found to be associated with improved survival at a moderate incremental cost. Cancer 2003;98:1491-6.

Adult↗

PubMed2025

S-GMAS: Genome-Wide Mediation Analysis With Brain Subcortical Shape Mediators.

Mediation analysis is widely utilized in neuroscience to investigate the role of brain image phenotypes in the neurological pathways from genetic exposures to clinical outcomes. However, it is still difficult to conduct mediation analyses with whole genome-wide exposures and brain subcortical shape mediators due to several challenges including (i) large-scale genetic exposures, that is, millions of single-nucleotide polymorphisms (SNPs); (ii) nonlinear Hilbert space for shape mediators; and (iii) statistical inference on the direct and indirect effects. To tackle these challenges, this paper proposes a genome-wide mediation analysis framework with brain subcortical shape mediators. First, to address the issue caused by the high dimensionality in genetic exposures, a fast genome-wide association analysis is conducted to discover potential genetic variants with significant genetic effects on the clinical outcome. Second, the square-root velocity function representations are extracted from the brain subcortical shapes, which fall in an unconstrained linear Hilbert subspace. Third, to identify the underlying causal pathways from the detected SNPs to the clinical outcome implicitly through the shape mediators, we utilize a shape mediation analysis framework consisting of a shape-on-scalar model and a scalar-on-shape model. Furthermore, the bootstrap resampling approach is adopted to investigate both global and spatial significant mediation effects. Finally, our framework is applied to the corpus callosum shape data from the Alzheimer's Disease Neuroimaging Initiative.

Humans↗

PubMed2002

Estimating survival gain for economic evaluations with survival time as principal endpoint: a cost-effectiveness analysis of adding early hormonal therapy to radiotherapy in patients with locally advanced prostate cancer.

The problem of estimating expected outcomes for the economic evaluation of treatments for which the outcome of principal interest is (quality adjusted) survival time has so far not received sufficient attention in the literature. The best estimate of expected survival is mean survival time, but with censored survival data, the true survival time for all the subjects is not known, so the mean is not defined.A possible solution to this estimation problem is illustrated by a retrospective cost-effectiveness analysis of the addition of hormonal therapy to standard radiotherapy for patients with locally advanced prostate cancer. A recently proposed method is used to approach the problem caused by censored cost data, and the impact of uncertainty is assessed by bootstrap resampling techniques. Mean survival time is estimated by a restricted means analysis with the time point of restriction determined by statistical criteria. When average total costs and mean survival time is evaluated at this time point of restriction, the result is that the combined therapy (radiotherapy plus hormonal therapy) increases mean survival time by about 1 year, while reducing the costs per patient for the French health insurance system by 12 700 FF. The time point of restriction may also be determined by other criteria and mean survival time may be estimated by extrapolating the survival curves by means of various parametric survival distributions. We show that the exact results of the economic evaluation are decisively determined by the restriction time point chosen and the approach taken to estimate mean survival time.

Antineoplastic Agents, Hormonal↗

PubMed2002

TP53 mutations in breast cancer tumors of patients from Rio de Janeiro, Brazil: association with risk factors and tumor characteristics.

Somatic mutations in the TP53 gene are the most frequently observed genetic alterations in human malignancies, including breast cancer, which is one of the leading causes of death among women in Brazil. In our study, we determined the frequency and the pattern of TP53 mutations in malignant breast tumors from 120 patients living in Rio de Janeiro, Brazil. TP53 mutations were found in 20% of the tumors, which contained a diversity of mutation types: missense (62.5%), nonsense (8.3%), silent (4.2%), intronic (12.5%), insertion (4.2%) and deletion (8.3%). Of a total of 15 missense mutations, 4 were observed at Arg248 and 2 at Cys242, which are directly involved in DNA binding and in zinc binding, respectively. A subgroup of 51 patients was analyzed with respect to the relation between the presence of TP53 mutations and classical risk factors and with tumor and patient characteristics. For this analysis, we used logistic regression and, in order to obtain more precise confidence intervals, they were recalculated using a bootstrap resampling technique. Our results demonstrate that these mutations are not statistically associated with the risk factors or the patients' characteristics. However, the presence of TP53 mutations is strongly associated with the aggressiveness of the tumors, measured by Elston classification (OR = 11.97 and 95% CI of 2.24-307.05). This finding is in agreement with previous studies, which report the presence of TP53 mutations in tumors with poor prognosis. This correlation between tumor aggressiveness and TP53 mutations could be a crucial variable for the treatment and prognosis of breast cancer.

Adult↗

PubMed2004

Confidence intervals for the effect of a prognostic factor after selection of an 'optimal' cutpoint.

When investigating the effects of potential prognostic or risk factors that have been measured on a quantitative scale, values of these factors are often categorized into two groups. Sometimes an 'optimal' cutpoint is chosen that gives the best separation in terms of a two-sample test statistic. It is well known that this approach leads to a serious inflation of the type I error and to an overestimation of the effect of the prognostic or risk factor in absolute terms. In this paper, we illustrate that the resulting confidence intervals are similarly affected. We show that the application of a shrinkage procedure to correct for bias, together with bootstrap resampling for estimating the variance, yields confidence intervals for the effect of a potential prognostic or risk factor with the desired coverage.

Breast Neoplasms↗

PubMed2007

A combined superiority and non-inferiority approach to multiple endpoints in clinical trials.

Treatment comparisons in clinical trials often involve multiple endpoints. By making use of bootstrap tests, we develop a new non-parametric approach to multiple-endpoint testing that can be used to demonstrate non-inferiority of a new treatment for all endpoints and superiority for some endpoint when it is compared to an active control. It is shown that this approach does not incur a large multiplicity cost in sample size to achieve reasonable power and that it can incorporate complex dependencies in the multivariate distributions of all outcome variables for the two treatments via bootstrap resampling.

Algorithms↗

PubMed1991

A statistical method for assessing a threshold in epidemiological studies.

I describe a method for estimating and testing a threshold value in epidemiological studies. A threshold effect indicates an association between a risk factor and a defined outcome above the threshold value but none below it. An important field of application is occupational medicine where, for a lot of chemical compounds and other agents which are non-carcinogenic health hazards, so-called threshold limit values or TLVs are specified. The method is presented within the framework of the logistic regression model, which is widely used in the analysis of the relationship between some explanatory variables and a dependent dichotomous outcome. In most available programs for this and also for other models the concept of a threshold is disregarded. The method for assessing a threshold consists of an estimation procedure using the maximum-likelihood technique and a test procedure based on the likelihood-ratio statistic R, following under the null hypothesis (no threshold) a quasi one-sided chi 2 distribution with one degree of freedom. This use of this distribution is supported by a simulation study. The method is applied to data from an epidemiological study of the relationship between occupational dust exposure and chronic bronchitic reactions. The results are confirmed by bootstrap resampling.

Bronchitis↗

PubMed2001

A standardization method to adjust for the effect of patient selection in phase II clinical trials.

New combination regimens evaluated in phase II cancer clinical trials often show promising results compared to the standard therapy for a disease system. Selection of patients with a better prognosis can be a prominent factor for this optimism. For most disease systems, prognostic variables that are related to the outcome are available and are called risk factors. Patients are classified into risk categories depending on the number of risk factors they possess. The patient distribution is defined as the proportion of patients falling into each of these risk categories. Typically, the patient distribution observed for a phase II study differs from the standard therapy reports so that the outcomes are not comparable. A randomized trial is the ultimate step for establishing the efficacy of a new treatment. In order to determine whether a regimen should progress to a phase III trial, we suggest adjusting the standard therapy outcome for the effect of the observed phase II patient distribution. If the endpoint of interest is tumour response proportion, a weighted average utilizing the standard therapy response proportions and the phase II patient distribution would provide an estimate of the adjusted standard therapy response proportion. Confirmatory phase II trials often attempt to estimate median survival in addition to response proportion, since this is the primary endpoint for most phase III cancer studies. Because data are censored, we propose an adjustment method based on the bootstrap resampling technique. We illustrate the problem of disparate patient selection with data from melanoma studies and demonstrate the usefulness of the proposed adjustment method with data from bladder cancer studies. A simulation study indicates that the magnitude of the adjustment is heavily dependent on the degree of separation of the risk categories. SAS code is available on a website (http://lib.stat.cmu.edu) for easy implementation.

Antineoplastic Combined Chemotherapy Protocols↗

PubMed2001

Why nuclear ribosomal DNA spacers (ITS) tell different stories in Quercus.

The molecular systematics of Quercus (Fagaceae) was recently assessed by two teams using independently generated ITS sequences. Although the results disagreed in several remarkable features, the phylogenetic trees for either hypothesis were highly supported by bootstrap resampling. We have reanalyzed the ITS sequences used by both teams (eight taxa) to reveal the underlying patterns of this divergence. Within species, conspicuous length and G + C% divergence were evident in most sequence comparisons. In addition, a high rate of substitutions and deletions involving highly conserved motifs in both ITS spacers were present in a set of sequences. This was coupled with a less thermodynamic stability in the RNA structure, lacking conserved hairpins that are putatively involved in the processing of the RNA transcripts. Compelling evidence suggests that the divergent ITS alleles reported by one team are pseudogenes, i.e., nonfunctional paralogous loci. The hypothesis that the contrasting phylogenetic histories drawn from Quercus using ITS data are not strictly related to technical differences between laboratories, but that they have rather been generated from the analysis of paralogous sequences, best reconciles the available data. The risk of incorporating ITS paralogues in plant evolutionary studies which can distortion the phylogenetic signal should caution molecular systematists. Without a detailed inspection of some basic features of the sequence, including the integrity of the conserved motifs and the thermodynamic stability of the secondary structures of the RNA transcripts, errors in evolutionary inferences could be easily overlooked.

Base Composition↗

PubMedDate not supplied

Aerobic exercise and bone density at the hip in postmenopausal women: a meta-analysis.

BACKGROUND: The effects of aerobic exercise on bone density at the hip in postmenopausal women in the absence of estrogen replacement therapy are not currently known. The purpose of this study was to examine the effects of aerobic exercise on bone density at the hip in postmenopausal women. METHODS: Using the meta-analytic approach, studies dealing with the effects of aerobic exercise on bone density at the hip in postmenopausal women were searched for using computerized literature searches (MEDLINE, January 1978 to December 1995) as well as cross-referencing from retrieved review articles and original investigations. RESULTS: A total of 18 effect sizes were derived from six studies. Using a fixed-effects model and bootstrap resampling (5,000 iterations) overall changes in bone density at the hip yielded an average effect size of 0.43 (95% CI = 0.04 to 0.81), equivalent to an overall change of approximately 2.42% (exercise = 2.13%; nonexercise = -0.29%). Statistically significant differences were observed when effect sizes were partitioned by country in which studies were conducted (United States, mean = 1.03, 95% CI = 0.48 to 1.68; other countries, mean = 0.18, 95% CI = -0.27 to 0.54; Qb = 5.44, P = 0.04) and calcium intake (> or =1,000 mg/day, mean = 0.83, 95% CI = 0.49 to 1.23; <1,000 mg/day = -0.23, 95% CI = -0.85 to 0.21; Qb = 10.64, P = 0.002). CONCLUSIONS: The overall results of this study suggest that site-specific aerobic exercise has a moderately positive effect on bone density at the hip in postmenopausal women. However, a need exists for additional, well-designed studies before a final recommendation can be made regarding the efficacy of aerobic exercise as a nonpharmacologic intervention for optimizing bone density at the hip in postmenopausal women.

Absorptiometry, Photon↗

PubMed1995

The evolutionary divergence of neurotransmitter receptors and second-messenger pathways.

Members of the superfamily of G-protein-coupled neurotransmitter receptors have a conserved secondary structure, a moderate and reasonably steady rate of sequence change, and usually lack introns within the coding sequence. These properties are advantageous for evolutionary studies. The duplication and divergence of the genes in this gene family led to the formation of distinct neurotransmitter pathways and may have facilitated the evolution of complex nervous systems. I have analyzed this evolutionary divergence by quantitative multiple sequence alignment, bootstrap resampling, and statistical analysis of 49 adrenergic, muscarinic cholinergic, dopamine, and octopamine receptor sequences from 12 animal species. The results indicate that the first event to occur within this gene family was the divergence of the catecholamine receptors from the muscarinic acetylcholine receptors, which occurred prior to the divergence of the arthropod and vertebrate lineages. Subsequently, the ability to activate specific second-messenger pathways diverged independently in both the muscarinic and the catecholamine receptors. This appears to have occurred after the divergence of the arthropod and vertebrate lineages but before the divergence of the avian and mammalian lineages. However, the second-messenger pathways activated by adrenergic and dopamine receptors did not diverge independently. Rather, the ability of the catecholamine receptors to bind to specific ligands, such as epinephrine, norepinephrine, dopamine, or octopamine, was repeatedly modified in evolutionary history, and in some cases was modified after the divergence of the second-messenger pathways.

Adenylyl Cyclases↗

PubMed1992

The nucleotide sequence of the small subunit ribosomal RNA gene from Symbiodinium pilosum, a symbiotic dinoflagellate.

The complete sequence of the small subunit ribosomal RNA (SSU rRNA) gene was determined for the symbiotic dinoflagellate Symbiodinium pilosum. This sequence was compared with sequences from two other dinoflagellates (Prorocentrum micans and Crypthecodinium cohnii), five Apicomplexa, five Ciliata, five other eukaryotes and one archaebacterium. The corresponding structurally conserved regions of the molecule were used to determine which portions of the sequences could be unambiguously aligned. Phylogenetic relationships were inferred from an analysis of distance matrices, where pair-wise distances were determined using a maximum likelihood model for transition and transversion ratios, and from maximum parsimony analysis, with bootstrap resampling. By either analytical approach, the dinoflagellates appear distantly related to prokaryotes, and are most closely related to two of the Apicomplexa, Sarcocystis muris and Theileria annulata. Among the dinoflagellates, C. cohnii was found to be more closely affiliated with the Apicomplexa than either P. micans or S. pilosum.

Animals↗

PubMed1989

Evaluation of the maximum likelihood estimate of the evolutionary tree topologies from DNA sequence data, and the branching order in hominoidea.

A maximum likelihood method for inferring evolutionary trees from DNA sequence data was developed by Felsenstein (1981). In evaluating the extent to which the maximum likelihood tree is a significantly better representation of the true tree, it is important to estimate the variance of the difference between log likelihood of different tree topologies. Bootstrap resampling can be used for this purpose (Hasegawa et al. 1988; Hasegawa and Kishino 1989), but it imposes a great computation burden. To overcome this difficulty, we developed a new method for estimating the variance by expressing it explicitly. The method was applied to DNA sequence data from primates in order to evaluate the maximum likelihood branching order among Hominoidea. It was shown that, although the orangutan is convincingly placed as an outgroup of a human and African apes clade, the branching order among human, chimpanzee, and gorilla cannot be determined confidently from the DNA sequence data presently available when the evolutionary rate constancy is not assumed.

Animals↗

PubMed2003

Advantage of single-trial models for response to selection in wheat breeding multi-environment trials.

An investigation was conducted to evaluate the impact of experimental designs and spatial analyses (single-trial models) of the response to selection for grain yield in the northern grains region of Australia (Queensland and northern New South Wales). Two sets of multi-environment experiments were considered. One set, based on 33 trials conducted from 1994 to 1996, was used to represent the testing system of the wheat breeding program and is referred to as the multi-environment trial (MET). The second set, based on 47 trials conducted from 1986 to 1993, sampled a more diverse set of years and management regimes and was used to represent the target population of environments (TPE). There were 18 genotypes in common between the MET and TPE sets of trials. From indirect selection theory, the phenotypic correlation coefficient between the MET and TPE single-trial adjusted genotype means [ r(p(MT))] was used to determine the effect of the single-trial model on the expected indirect response to selection for grain yield in the TPE based on selection in the MET. Five single-trial models were considered: randomised complete block (RCB), incomplete block (IB), spatial analysis (SS), spatial analysis with a measurement error (SSM) and a combination of spatial analysis and experimental design information to identify the preferred (PF) model. Bootstrap-resampling methodology was used to construct multiple MET data sets, ranging in size from 2 to 20 environments per MET sample. The size and environmental composition of the MET and the single-trial model influenced the r(p(MT)). On average, the PF model resulted in a higher r(p(MT)) than the IB, SS and SSM models, which were in turn superior to the RCB model for MET sizes based on fewer than ten environments. For METs based on ten or more environments, the r(p(MT)) was similar for all single-trial models.

Agriculture↗

PubMed1997

Evaluation of three larval instars of the midge Chironomus petiolatus as bioassay tools using a computationally intensive statistical algorithm.

Sensitivity to toxicants is a major criterion for selecting organisms for bioassay testing. If a sensitive species is also abundant and occupies a role as prey for many other species within a community, then the species become a valuable tool in environmental monitoring. These features apply to larval midge Chironomus petiolatus in freshwater environments of central Chile. The youngest larval instar is the most sensitive and presents the additional feature of lower survival within control arenas, making it more difficult to discern toxicant-related mortality from background mortality. In this work, we perform acute bioassays with the three larval stages of C. petiolatus and K2Cr2O7 as reference toxicant, with the goal of selecting a particular instar as the best bioassay tool using two criteria: sensitivity and background mortality. Sensitivity is evaluated through Monte Carlo estimation of LC50 and background mortality through bootstrap resampling, and a final Bioassay Performance Index as the product of LC50 and background mortality. For this task we developed a new computationally intensive statistical algorithm. Results show that the best bioassay tool is not the youngest and most sensitive instar but an intermediate one.

Algorithms↗

PubMed1993

The phylogenetic position of the Aspidobothrea within the parasitic flatworms inferred from ribosomal RNA sequence data.

Sequence data from parts of the small subunit ribosomal RNA gene (18s rRNA) from an aspidobothrean and two digeneans have been added to a published data set which includes sequences from a number of parasitic and non-parasitic flatworms. Parsimony and distance matrix analyses of the data were carried out. Tests for particular clades were done using bootstrap resampling methods, and tests of particular topologies done using 4- and 5-taxon tests. The aspidobothrean Lobatostoma manteri emerges from near the base of the Neodermata, but whether as a sister group to the rest of the Neodermata or as a sister to the Digenea alone cannot be determined from the number of nucleotide sites available. Gyrocotyle is included with the cestodes in a very strongly supported clade in all analyses. There is evidence that the Monogenea is a paraphyletic group, although more data are needed to confirm this possibility.

Animals↗