Search PubMed⌕ Search
Home/Archive/PubMed

PubMed · 16258787

[Physical activity].

G Schuler
View original source ↗Export metadata ↓

Abstract

There are a total of 30 publications regarding the role physical exercise in primary prevention of coronary artery disease, nearly a quarter of a million patients have participated in these studies. The average observation time reaches 10 years. According to the guidelines of the ACC/AHA Task Force this is the basis for the evidence/recommendation class I. The benefit derived from this treatment considerably exceeds the risk; thus, there is no need for additional studies. A great number of population-based risk factors were evaluated; in several randomized studies and meta-analyses concordant results were achieved with respect to direction and degree of the therapeutic effect (Level B).

Explore related subjects

Clinical Trials as TopicCoronary Artery DiseaseExercise TherapyHumansIncidenceMotor ActivityRisk AssessmentRisk FactorsTreatment OutcomeEnglish AbstractJournal ArticleMeta-Analysis

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

G Schuler. 2005. [Physical activity].. https://doi.org/10.1007/s00392-005-1303-1

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

PubMed2007

Appropriateness of some resampling-based inference procedures for assessing performance of prognostic classifiers derived from microarray data.

The goal of many gene-expression microarray profiling clinical studies is to develop a multivariate classifier to predict patient disease outcome from a gene-expression profile measured on some biological specimen from the patient. Often some preliminary validation of the predictive power of a profile-based classifier is carried out using the same data set that was used to derive the classifier. Techniques such as cross-validation or bootstrapping can be used in this setting to assess predictive power, and if applied correctly, can result in a less biased estimate of predictive accuracy of a classifier. However, some investigators have attempted to apply standard statistical inference procedures to assess the statistical significance of associations between true and cross-validated predicted outcomes. We demonstrate in this paper that naïve application of standard statistical inference procedures to these measures of association under null situations can result in greatly inflated testing type I error rates. Under alternatives of small to moderate associations, confidence interval coverage probabilities may be too low, although for very large associations coverage probabilities approach their intended values. Our results suggest that caution should be exercised in interpreting some of the claims of exceptional prognostic classifier performance that have been reported in prominent biomedical journals in the past few years.

Clinical Trials as Topic↗
PubMed2006

Some design issues of strata-matched non-randomized studies with survival outcomes.

Non-randomized studies for the evaluation of a medical intervention are useful for quantitative hypothesis generation before the initiation of a randomized trial and also when randomized clinical trials are difficult to conduct. A strata-matched non-randomized design is often utilized where subjects treated by a test intervention are matched to a fixed number of subjects treated by a standard intervention within covariate based strata. In this paper, we consider the issue of sample size calculation for this design. Based on the asymptotic formula for the power of a stratified log-rank test, we derive a formula to calculate the minimum number of subjects in the test intervention group that is required to detect a given relative risk between the test and standard interventions. When this minimum number of subjects in the test intervention group is available, an equation is also derived to find the multiple that determines the number of subjects in the standard intervention group within each stratum. The methodology developed is applied to two illustrative examples in gastric cancer and sarcoma.

Clinical Trials as Topic↗
PubMed2006

Estimation in flexible two stage designs.

Adaptive test designs for clinical trials allow for a wide range of data driven design adaptations using all information gathered until an interim analysis. The basic principle is to use a test statistics which is invariant with respect to the design adaptations under the null hypothesis. This allows for a control of the type I error rate for the primary hypothesis even for adaptations not specified a priori in the study protocol. Estimation is usually another important part of a clinical trial, however, is more difficult in adaptive designs. In this research paper we give an overview of point and interval estimates for flexible designs and compare methods for typical sample size rules. We also make some proposals for confidence intervals which have nominal coverage probability also after an unforeseen design adaptation and which contain the maximum likelihood estimate and the usual unadjusted confidence interval.

Clinical Trials as Topic↗