Biomedical subjects

M J van der Laan

Publications and source records attributed to M J van der Laan.

6 recordsLinked to original sources

PubMed2006

Computed tomography versus magnetic resonance imaging of endoleaks after EVAR.

AIM: The aim of study was to compare the sensitivity of MRI and CTA for endoleak detection and classification after EVAR. PATIENTS & METHODS: Twenty-eight patients, between 2 days and 65 months after EVAR, were evaluated with both CT and MRI. Twenty-five patients had an Ancure graft and the other three had an Excluder. The MRI protocol for endoleak evaluation included: a T1-weighted spin echo, a high-resolution 3D CE-MRA, and a post-contrast T1-weighted spin echo. In total 40 ml Gadolinium was administered. The CT protocol consisted of a blank survey followed by a spiral CT angiography (CTA) using 140 ml of Ultravist. An experienced, blinded observer evaluated all CTs and MRIs. RESULTS: Using MRI and MRA techniques significantly more endoleaks (23/35) were detected than with CTA (11/35) (p=0.01, Chi-Square). CT could not determine the type of endoleak in 3 of the 11 endoleaks detected and was uncertain in one. MRI was uncertain about the type in 14 of the 23 endoleaks detected. All endoleaks visible on CT were visible by MRI as well. CONCLUSIONS: MRI techniques are more sensitive for the detection of endoleak after endovascular AAA repair than CT.

Aged↗

PubMed2005

Dynamic CE-MRA for endoleak classification after endovascular aneurysm repair.

AIM: To evaluate the value of dynamic contrast enhanced magnetic resonance angiography (CE-MRA) for classification of endoleaks after endovascular aneurysm repair (EVAR). MATERIALS AND METHODS: Twenty-eight patients, between 2 days and 54 months after EVAR, were evaluated with CTA, MRI and dynamic CE-MRA. The additional diagnostic value of the dynamic 3D CE-MRA was evaluated by determining the ability of the dynamic series in pinpointing the site of inflow of an endoleak. RESULTS: An endoleak was detected in 23 patients. Seventeen of the 23 dynamic series were technically successful (no disturbing artifacts limiting the diagnostic value). Using MRI our findings were: 2 type I, 6 type II, 1 type III, no type IV endoleaks and in 14 cases classification could not be made. The classification results for MRI plus the dynamic CE-MRA were: 2 type I, 12 type II, 1 type III, no type IV endoleaks and in eight cases classification could not be made. In six cases the dynamic MRA allowed classification of the endoleak, which was not possible with the non-dynamic images alone (p=0.091, Fisher exact). CONCLUSION: This pilot study shows that dynamic CE-MRA can have additional value in the classification of endoleaks. Dynamic CE-MRA might obviate the need for diagnostic digital subtraction angiography and aid planning for intervention.

Aged↗

PubMed2003

Short- and long-term effects of neonatal glucocorticoid therapy: is hydrocortisone an alternative to dexamethasone?

AIM: To compare short-term effects and neurodevelopmental outcome of neonatal glucocorticoid therapy between two centres. METHODS: A retrospective study was performed in two centres using a tapering course of either 5 to 1 mg kg(-1) hydrocortisone (HC; 22 d) or 0.5 to 0.1 mg kg(-1) dexamethasone (DEX; 21 d). In both centres glucocorticoid-treated infants and control patients were matched for gestational age, birthweight, severity of infant respiratory distress syndrome and periventricular-intraventricular haemorrhage. The following short-term glucocorticoid-induced effects were investigated in 25 HC-treated and 25 control patients in centre A, and in 23 DEX-treated and 23 control patients in centre B: oxygen dependency (inspiratory oxygen fraction), arterial pressure, blood glucose and urea concentrations, weight gain and head circumference before, during and after therapy (in treated infants), or at an interval comparable to treated infants (in control infants). Neurological outcome, psychomotor development and school performance at 5-7 y of age was evaluated in all groups. RESULTS: HC and DEX were equally potent in reducing oxygen dependency. Mean arterial pressure as well as blood glucose and urea concentrations were significantly increased during DEX, but not during HC treatment. Weight gain stopped during DEX therapy, but not during HC. Head circumference in both treatment groups was decreased after therapy compared with controls. Neonatally DEX-treated children needed special school education significantly more often (p < 0.01) than controls at 5-7 y of age. No differences between neonatally HC-treated children and controls on neurodevelopmental outcome were found at 5-7 y of age. CONCLUSION: Neonatal HC therapy has fewer short- and long-term adverse effects than neonatal DEX therapy.

Anti-Inflammatory Agents↗

PubMed2001

Gene expression analysis with the parametric bootstrap.

Recent developments in microarray technology make it possible to capture the gene expression profiles for thousands of genes at once. With this data researchers are tackling problems ranging from the identification of 'cancer genes' to the formidable task of adding functional annotations to our rapidly growing gene databases. Specific research questions suggest patterns of gene expression that are interesting and informative: for instance, genes with large variance or groups of genes that are highly correlated. Cluster analysis and related techniques are proving to be very useful. However, such exploratory methods alone do not provide the opportunity to engage in statistical inference. Given the high dimensionality (thousands of genes) and small sample sizes (often <30) encountered in these datasets, an honest assessment of sampling variability is crucial and can prevent the over-interpretation of spurious results. We describe a statistical framework that encompasses many of the analytical goals in gene expression analysis; our framework is completely compatible with many of the current approaches and, in fact, can increase their utility. We propose the use of a deterministic rule, applied to the parameters of the gene expression distribution, to select a target subset of genes that are of biological interest. In addition to subset membership, the target subset can include information about relationships between genes, such as clustering. This target subset presents an interesting parameter that we can estimate by applying the rule to the sample statistics of microarray data. The parametric bootstrap, based on a multivariate normal model, is used to estimate the distribution of these estimated subsets and relevant summary measures of this sampling distribution are proposed. We focus on rules that operate on the mean and covariance. Using Bernstein's Inequality, we obtain consistency of the subset estimates, under the assumption that the sample size converges faster to infinity than the logarithm of the number of genes. We also provide a conservative sample size formula guaranteeing that the sample mean and sample covariance matrix are uniformly within a distance epsilon > 0 of the population mean and covariance. The practical performance of the method using a cluster-based subset rule is illustrated with a simulation study. The method is illustrated with an analysis of a publicly available leukemia data set.

Journal Article↗

PubMed2000

Inference with bivariate truncated data.

In this paper we build on previous work for estimation of the bivariate distribution of the time variables T1 and T2 when they are observable only on the condition that one of the time variables, say T1, is greater than (left-truncation) or less than (right truncation) some observed time variable C1. In this paper, we introduce several results based on the Influence Curve (which we derive in this paper) of the NPMLE of the distribution F of (T1, T2) developed by van der Laan (van der Laan, 1996). Specifically we will: prove that the NPMLE is asymptotically equivalent to an estimator developed by Gürler (Gürler, 1997), derive the asymptotic distribution of the NPMLE based on its Influence Curve, present tests to determine the amount of dependence between T1 and T2, present the results of simulation studies that compare the NPMLE and Gürler's estimator and evaluate the performance of both the above mentioned tests and confidence intervals of F based on the asymptotic distribution of the NPMLE, and finally we will apply the methods in a data analysis in which we also point out practical issues that arise in the implementation of the estimator.

Acquired Immunodeficiency Syndrome↗

PubMed1999

Locally efficient estimation of the quality-adjusted lifetime distribution with right-censored data and covariates.

Zhao and Tsiatis (1997) consider the problem of estimation of the distribution of the quality-adjusted lifetime when the chronological survival time is subject to right censoring. The quality-adjusted lifetime is typically defined as a weighted sum of the times spent in certain states up until death or some other failure time. They propose an estimator and establish the relevant asymptotics under the assumption of independent censoring. In this paper we extend the data structure with a covariate process observed until the end of follow-up and identify the optimal estimation problem. Because of the curse of dimensionality, no globally efficient nonparametric estimators, which have a good practical performance at moderate sample sizes, exist. Given a correctly specified model for the hazard of censoring conditional on the observed quality-of-life and covariate processes, we propose a closed-form one-step estimator of the distribution of the quality-adjusted lifetime whose asymptotic variance attains the efficiency bound if we can correctly specify a lower-dimensional working model for the conditional distribution of quality-adjusted lifetime given the observed quality-of-life and covariate processes. The estimator remains consistent and asymptotically normal even if this latter submodel is misspecified. The practical performance of the estimators is illustrated with a simulation study. We also extend our proposed one-step estimator to the case where treatment assignment is confounded by observed risk factors so that this estimator can be used to test a treatment effect in an observational study.

Biometry↗