WorldCat Identities

Sauerbrei, Willi

Overview
Works: 37 works in 72 publications in 2 languages and 544 library holdings
Roles: Author, Other, Contributor
Publication Timeline
.
Most widely held works by Willi Sauerbrei
Multivariable model-building : a pragmatic approach to regression analysis based on fractional polynomials for modelling continuous variables by Patrick Royston( )

23 editions published between 2008 and 2009 in English and held by 442 WorldCat member libraries worldwide

"Multivariable regression models are widely used in all areas of science in which empirical data are analysed. Using the multivariable fractional polynomials (MFP) approach this book focuses on the selection of important variables and the determination of functional form for continuous predictors. Despite being relatively simple, the selected models often extract most of the important information from the data. The authors have chosen to concentrate on examples drawn from medical statistics, although the MFP method has applications in many other subject-matter areas as well. This book is aimed at graduate students studying regression modelling and professionals in statistics as well as researchers from medical, physical, social and many other sciences where regression models play a central role."--Jacket
Variablenselektion in Regressionsmodellen unter besonderer Berücksichtigung medizinischer Fragestellungen by Willi Sauerbrei( Book )

3 editions published in 1992 in German and held by 12 WorldCat member libraries worldwide

Investigation of continuous effect modifiers in a meta-analysis on higher versus lower PEEP in patients requiring mechanical ventilation - protocol of the ICEM study by Benjamin Kasenda( )

3 editions published in 2014 in English and held by 5 WorldCat member libraries worldwide

Abstract: Background: Categorizing an inherently continuous predictor in prognostic analyses raises several critical methodological issues: dependence of the statistical significance on the number and position of the chosen cut-point(s), loss of statistical power, and faulty interpretation of the results if a non-linear association is incorrectly assumed to be linear. This also applies to a therapeutic context where investigators of randomized clinical trials (RCTs) are interested in interactions between treatment assignment and one or more continuous predictors.<br>Methods/Design: Our goal is to apply the multivariable fractional polynomial interaction (MFPI) approach to investigate interactions between continuous patient baseline variables and the allocated treatment in an individual patient data meta-analysis of three RCTs (N = 2,299) from the intensive care field. For each study, MFPI will provide a continuous treatment effect function. Functions from each of the three studies will be averaged by a novel meta-analysis approach for functions. We will plot treatment effect functions separately for each study and also the averaged function. The averaged function with a related confidence interval will provide a suitable basis to assess whether a continuous patient characteristic modifies the treatment comparison and may be relevant for clinical decision-making. The compared interventions will be a higher or lower positive end-expiratory pressure (PEEP) ventilation strategy in patients requiring mechanical ventilation. The continuous baseline variables body mass index, PaO2/FiO2, respiratory compliance, and oxygenation index will be the investigated potential effect modifiers. Clinical outcomes for this analysis will be in-hospital mortality, time to death, time to unassisted breathing, and pneumothorax.<br>Discussion: This project will be the first meta-analysis to combine continuous treatment effect functions derived by the MFPI procedure separately in each of several RCTs. Such an approach requires individual patient data (IPD). They are available from an earlier IPD meta-analysis using different methods for analysis. This new analysis strategy allows assessing whether treatment effects interact with continuous baseline patient characteristics and avoids categorization-based subgroup analyses. These interaction analyses of the present study will be exploratory in nature. However, they may help to foster future research using the MFPI approach to improve interaction analyses of continuous predictors in RCTs and IPD meta-analyses. This study is registered in PROSPERO (CRD42012003129)
A plea for taking all available clinical information into account when assessing the predictive value of omics data by Alexander Volkmann( )

2 editions published in 2019 in English and held by 5 WorldCat member libraries worldwide

Exploration of the variability of variable selection based on distances between bootstrap sample results by Christian Hennig( )

2 editions published in 2019 in English and held by 5 WorldCat member libraries worldwide

Abstract: It is well known that variable selection in multiple regression can be unstable and that the model uncertainty can be considerable. The model uncertainty can be quantified and explored by bootstrap resampling, see Sauerbrei et al. (Biom J 57:531-555, 2015). Here approaches are introduced that use the results of bootstrap replications of the variable selection process to obtain more detailed information about the data. Analyses will be based on dissimilarities between the results of the analyses of different bootstrap samples. Dissimilarities are computed between the vector of predictions, and between the sets of selected variables. The dissimilarities are used to map the models by multidimensional scaling, to cluster them, and to construct heatplots. Clusters can point to different interpretations of the data that could arise from different selections of variables supported by different bootstrap samples. A new measure of variable selection instability is also defined. The methodology can be applied to various regression models, estimators, and variable selection methods. It will be illustrated by three real data examples, using linear regression and a Cox proportional hazards model, and model selection by AIC and BIC
Methods for Evaluating Medical Tests and Biomarkers Birmingham, UK. 19-20 July 2016 by Gowri Gopalakrishna( )

2 editions published in 2017 in English and held by 5 WorldCat member libraries worldwide

Assessment of the extent of unpublished studies in prognostic factor research: a systematic review of p53 immunohistochemistry in bladder cancer as an example by Peggy Sekula( )

3 editions published in 2016 in English and held by 5 WorldCat member libraries worldwide

Abstract: Objectives When study groups fail to publish their results, a subsequent systematic review may come to incorrect conclusions when combining information only from published studies. p53 expression measured by immunohistochemistry is a potential prognostic factor in bladder cancer. Although numerous studies have been conducted, its role is still under debate. The assumption that unpublished studies too harbour evidence on this research topic leads to the question about the attributable effect when adding this information and comparing it with published data. Thus, the aim was to identify published and unpublished studies and to explore their differences potentially affecting the conclusion on its function as a prognostic biomarker.DesignSystematic review of published and unpublished studies assessing p53 in bladder cancer in Germany between 1993 and 2007.ResultsThe systematic search revealed 16 studies of which 11 (69%) have been published and 5 (31%) have not. Key reason for not publishing the results was a loss of interest of the investigators. There were no obviously larger differences between published and unpublished studies. However, a meaningful meta-analysis was not possible mainly due to the poor (ie, incomplete) reporting of study results.ConclusionsWithin this well-defined population of studies, we could provide empirical evidence for the failure of study groups to publish their results that was mainly caused by loss of interest. This fact may be coresponsible for the role of p53 as a prognostic factor still being unclear. We consider p53 and the restriction to studies in Germany as a specific example, but the critical issues are probably similar for other prognostic factors and other countries
A review of spline function procedures in R by Aris Perperoglou( )

1 edition published in 2019 in English and held by 3 WorldCat member libraries worldwide

Abstract: Background<br>With progress on both the theoretical and the computational fronts the use of spline modelling has become an established tool in statistical regression analysis. An important issue in spline modelling is the availability of user friendly, well documented software packages. Following the idea of the STRengthening Analytical Thinking for Observational Studies initiative to provide users with guidance documents on the application of statistical methods in observational research, the aim of this article is to provide an overview of the most widely used spline-based techniques and their implementation in R.<br><br>Methods<br>In this work, we focus on the R Language for Statistical Computing which has become a hugely popular statistics software. We identified a set of packages that include functions for spline modelling within a regression framework. Using simulated and real data we provide an introduction to spline modelling and an overview of the most popular spline functions.<br><br>Results<br>We present a series of simple scenarios of univariate data, where different basis functions are used to identify the correct functional form of an independent variable. Even in simple data, using routines from different packages would lead to different results.<br><br>Conclusions<br>This work illustrate challenges that an analyst faces when working with data. Most differences can be attributed to the choice of hyper-parameters rather than the basis used. In fact an experienced user will know how to obtain a reasonable outcome, regardless of the type of spline used. However, many analysts do not have sufficient knowledge to use these powerful tools adequately and will need more guidance
An Experimental Evaluation of Boosting Methods for Classification by Rainer Stollhoff( )

2 editions published between 2010 and 2018 in English and held by 3 WorldCat member libraries worldwide

Objectives: In clinical medicine, the accuracy achieved by classification rules is often not sufficient to justify their use in daily practice. In order to improve classifiers it has become popular to combine single classification rules into a classification ensemble. Two popular boosting methods will be compared with classical statistical approaches. Methods: Using data from a clinical study on the diagnosis of breast tumors and by simulation we will compare AdaBoost with gradient boosting ensembles of regression trees. We will also consider a tree approach and logistic regression as traditional competitors. In logistic regression we allow to select non-linear effects by the fractional polynomial approach. Performance of the classifiers will be assessed by estimated misclassification rates and the Brier score. Results: We will show that boosting of simple base classifiers gives classification rules with improved predictive ability. However, the performance of boosting classifiers was not generally superior to the performance of logistic regression. In contrast to the computer intensive methods the latter are based on classifiers which are much easier to interpret and to use. Conclusions: In medical applications, the logistic regression model remains a method of choice or, at least, a serious competitor of more sophisticated techniques. Refinement of boosting methods by using optimized number of boosting steps may lead to further improvement
Did the reporting of prognostic studies of tumour markers improve since the introduction of REMARK guideline? A comparison of reporting in published articles by Peggy Sekula( )

2 editions published in 2017 in English and held by 3 WorldCat member libraries worldwide

Abstract: Although biomarkers are perceived as highly relevant for future clinical practice, few biomarkers reach clinical utility for several reasons. Among them, poor reporting of studies is one of the major problems. To aid improvement, reporting guidelines like REMARK for tumour marker prognostic (TMP) studies were introduced several years ago. The aims of this project were to assess whether reporting quality of TMP-studies improved in comparison to a previously conducted study assessing reporting quality of TMP-studies (PRE-study) and to assess whether articles citing REMARK (citing group) are better reported, in comparison to articles not citing REMARK (not-citing group).<br><br>For the POST-study, recent articles citing and not citing REMARK (53 each) were identified in selected journals through systematic literature search and evaluated in same way as in the PRE-study. Ten of the 20 items of the REMARK checklist were evaluated and used to define an overall score of reporting quality.<br><br>The observed overall scores were 53.4% (range: 10%-90%) for the PRE-study, 57.7% (range: 20%-100%) for the not-citing group and 58.1% (range: 30%-100%) for the citing group of the POST-study. While there is no difference between the two groups of the POST-study, the POST-study shows a slight but not relevant improvement in reporting relative to the PRE-study. Not all the articles of the citing group, cited REMARK appropriately. Irrespective of whether REMARK was cited, the overall score was slightly higher for articles published in journals requesting adherence to REMARK than for those published in journals not requesting it: 59.9% versus 51.9%, respectively.<br><br>Several years after the introduction of REMARK, many key items of TMP-studies are still very poorly reported. A combined effort is needed from authors, editors, reviewers and methodologists to improve the current situation. Good reporting is not just nice to have but is essential for any research to be useful
Introduction to statistical simulations in health research by Anne-Laure Isabeau Boulesteix( )

1 edition published in 2020 in English and held by 3 WorldCat member libraries worldwide

Abstract: In health research, statistical methods are frequently used to address a wide variety of research questions. For almost every analytical challenge, different methods are available. But how do we choose between different methods and how do we judge whether the chosen method is appropriate for our specific study? Like in any science, in statistics, experiments can be run to find out which methods should be used under which circumstances. The main objective of this paper is to demonstrate that simulation studies, that is, experiments investigating synthetic data with known properties, are an invaluable tool for addressing these questions. We aim to provide a first introduction to simulation studies for data analysts or, more generally, for researchers involved at different levels in the analyses of health data, who (1) may rely on simulation studies published in statistical literature to choose their statistical methods and who, thus, need to understand the criteria of assessing the validity and relevance of simulation results and their interpretation; and/or (2) need to understand the basic principles of designing statistical simulations in order to efficiently collaborate with more experienced colleagues or start learning to conduct their own simulations. We illustrate the implementation of a simulation study and the interpretation of its results through a simple example inspired by recent literature, which is completely reproducible using the R-script available from online supplemental file 1
Improving the prognostic ability through better use of standard clinical data - the Nottingham prognostic index as an example by Klaus-Jürgen Winzer( )

2 editions published in 2016 in English and held by 3 WorldCat member libraries worldwide

Abstract: BackgroundPrognostic factors and prognostic models play a key role in medical research and patient management. The Nottingham Prognostic Index (NPI) is a well-established prognostic classification scheme for patients with breast cancer. In a very simple way, it combines the information from tumor size, lymph node stage and tumor grade. For the resulting index cutpoints are proposed to classify it into three to six groups with different prognosis. As not all prognostic information from the three and other standard factors is used, we will consider improvement of the prognostic ability using suitable analysis approaches.Methods and Findings Reanalyzing overall survival data of 1560 patients from a clinical database by using multivariable fractional polynomials and further modern statistical methods we illustrate suitable multivariable modelling and methods to derive and assess the prognostic ability of an index.Using a REMARK type profile we summarize relevant steps of the analysis. Adding the information from hormonal receptor status and using the full information from the three NPI components, specifically concerning the number of positive lymph nodes, an extended NPI with improved prognostic ability is derived. ConclusionsThe prognostic ability of even one of the best established prognostic index in medicine can be improved by using suitable statistical methodology to extract the full information from standard clinical data. This extended version of the NPI can serve as a benchmark to assess the added value of new information, ranging from a new single clinical marker to a derived index from omics data. An established benchmark would also help to harmonize the statistical analyses of such studies and protect against the propagation of many false promises concerning the prognostic value of new measurements. Statistical methods used are generally available and can be used for similar analyses in other disease
Prevention of cervical cancer guideline of the DGGG and the DKG (S3 Level, AWMF Register Number 015/027OL, December 2017) : Part 1 with introduction, screening and the pathology of cervical dysplasia = Prävention des Zervixkarzinoms : Leitlinie der DGGG und DKG (S3-Level, AWMF-Register-Nummer 015/027OL, Dezember<br>2017) : Teil 1 mit Einführung, Screening und Pathologie von zervikalen Dysplasien by Peter Hillemanns( )

1 edition published in 2019 in English and held by 3 WorldCat member libraries worldwide

Abstract: Ziele <br>Seit 1971 erfolgt in Deutschland die jährliche, opportunistische Früherkennungsuntersuchung des Zervixkarzinoms. Durch die Etablierung dieser S3-Leitlinie wird zum einen eine wichtige Forderung des Nationalen Krebsplans zum Zervixkarzinom-Screening erfüllt. Zum anderen kann die S3-Leitlinie wesentliche Informationen und Hilfestellungen für das geplante organisierte Zervixkarzinomscreening in Deutschland geben.<br><br>Methoden <br>Mit finanzieller Unterstützung durch die Deutsche Krebshilfe wurden durch 21 Fachgesellschaften evidenzbasierte Statements und Empfehlungen (GRADE-System) zu Screening, Management und Behandlung von Zervixkarzinom-Vorstufen erarbeitet. Zwei unabhängige wissenschaftliche Institute haben systematische Reviews für diese Leitlinie erarbeitet.<br><br>Empfehlungen <br>Der erste Teil dieser Kurzzusammenfassung behandelt pathologische Grundlagen und Fragen zum Screening. Ähnliche wie in früheren Reviews konnte auch die Metaanalyse durch Kleijnen Systematic Reviews einen besseren Schutz vor einem invasiven Zervixkarzinom durch ein HPV-basiertes Screening im Vergleich zur Zytologie zeigen. Daher empfiehlt die Leitliniengruppe - entsprechend den Richtlinien des Gemeinsamen Bundesauschusses (G-BA) - ein HPV-basiertes Screening mit Intervallen von mind. 3 Jahren für Frauen ab 35 Jahren. Ein Co-Testing kann ebenfalls durchgeführt werden. Frauen zwischen 20 und 35 sollten ein zytologisches Screening alle 2 Jahre erhalten
Statistical models for complex data in clinical and epidemiological research by Jan Beyersmann( )

1 edition published in 2020 in English and held by 3 WorldCat member libraries worldwide

Systematic review of education and practical guidance on regression modeling for medical researchers who lack a strong statistical background: study protocol by Paul Bach( )

1 edition published in 2020 in English and held by 3 WorldCat member libraries worldwide

Abstract: In the last decades, statistical methodology has developed rapidly, in particular in the field of regression modeling. Multivariable regression models are applied in almost all medical research projects. Therefore, the potential impact of statistical misconceptions within this field can be enormous Indeed, the current theoretical statistical knowledge is not always adequately transferred to the current practice in medical statistics. Some medical journals have identified this problem and published isolated statistical articles and even whole series thereof. In this systematic review, we aim to assess the current level of education on regression modeling that is provided to medical researchers via series of statistical articles published in medical journals. The present manuscript is a protocol for a systematic review that aims to assess which aspects of regression modeling are covered by statistical series published in medical journals that intend to train and guide applied medical researchers with limited statistical knowledge. Statistical paper series cannot easily be summarized and identified by common keywords in an electronic search engine like Scopus. We therefore identified series by a systematic request to statistical experts who are part or related to the STRATOS Initiative (STRengthening Analytical Thinking for Observational Studies). Within each identified article, two raters will independently check the content of the articles with respect to a predefined list of key aspects related to regression modeling. The content analysis of the topic-relevant articles will be performed using a predefined report form to assess the content as objectively as possible. Any disputes will be resolved by a third reviewer. Summary analyses will identify potential methodological gaps and misconceptions that may have an important impact on the quality of analyses in medical research. This review will thus provide a basis for future guidance papers and tutorials in the field of regression modeling which will enable medical researchers 1) to interpret publications in a correct way, 2) to perform basic statistical analyses in a correct way and 3) to identify situations when the help of a statistical expert is required
State of the art in selection of variables and functional forms in multivariable analysis - outstanding issues by Willi Sauerbrei( )

1 edition published in 2020 in English and held by 3 WorldCat member libraries worldwide

Abstract: Background<br>How to select variables and identify functional forms for continuous variables is a key concern when creating a multivariable model. Ad hoc 'traditional' approaches to variable selection have been in use for at least 50 years. Similarly, methods for determining functional forms for continuous variables were first suggested many years ago. More recently, many alternative approaches to address these two challenges have been proposed, but knowledge of their properties and meaningful comparisons between them are scarce. To define a state of the art and to provide evidence-supported guidance to researchers who have only a basic level of statistical knowledge, many outstanding issues in multivariable modelling remain. Our main aims are to identify and illustrate such gaps in the literature and present them at a moderate technical level to the wide community of practitioners, researchers and students of statistics.<br><br>Methods<br>We briefly discuss general issues in building descriptive regression models, strategies for variable selection, different ways of choosing functional forms for continuous variables and methods for combining the selection of variables and functions. We discuss two examples, taken from the medical literature, to illustrate problems in the practice of modelling.<br><br>Results<br>Our overview revealed that there is not yet enough evidence on which to base recommendations for the selection of variables and functional forms in multivariable analysis. Such evidence may come from comparisons between alternative methods. In particular, we highlight seven important topics that require further investigation and make suggestions for the direction of further research.<br><br>Conclusions<br>Selection of variables and of functional forms are important topics in multivariable analysis. To define a state of the art and to provide evidence-supported guidance to researchers who have only a basic level of statistical knowledge, further comparative research is required
Prevention of cervical cancer guideline of the DGGG and the DKG (S3 Level, AWMF Register Number 015/027OL, December 2017) : Part 2 on triage, treatment and follow-up = Prävention des Zervixkarzinoms : Leitlinie der DGGG und DKG (S3-Level, AWMF-Register-Nummer 015/027OL, Dezember 2017) : Teil 2 mit Abklärung, Therapie und Nachbetreuung by Peter Hillemanns( )

1 edition published in 2019 in English and held by 3 WorldCat member libraries worldwide

Abstract: Ziele <br>Seit 1971 erfolgt in Deutschland die jährliche, opportunistische Früherkennungsuntersuchung des Zervixkarzinoms. Durch die Etablierung dieser S3-Leitlinie wird zum einen eine wichtige Forderung des Nationalen Krebsplans zum Zervixkarzinom-Screening erfüllt. Zum anderen kann die S3-Leitlinie wesentliche Informationen und Hilfestellungen für das geplante organisierte Zervixkarzinomscreening in Deutschland geben.<br><br>Methoden <br>Mit finanzieller Unterstützung durch die Deutsche Krebshilfe wurden durch 21 Fachgesellschaften evidenzbasierte Statements und Empfehlungen (GRADE-System) zu Screening, Management und Behandlung von Zervixkarzinom-Vorstufen erarbeitet. Zwei unabhängige wissenschaftliche Institute haben systematische Reviews für diese Leitlinie erarbeitet.<br><br>Empfehlungen <br>Der zweite Teil dieser Kurzzusammenfassung behandelt u. a. Abklärung, Therapie und Nachbetreuung zervikaler Dysplasien. Im Hinblick auf Nichtteilnehmerinnen am Screening empfiehlt die Leitliniengruppe erneute Einladungsschreiben oder eine HPV-Selbstabnahme. Ab einer Zytologie von Pap II-p in Kombination mit einem positiven HPV-Befund sollte eine Kolposkopie zur weiteren Abklärung durchgeführt werden, ebenso bei einem positiven HPV 16 oder HPV 18 Screening Test. Ein alleiniger auffälliger Pap-Abstrich sollte eine Triage mittels HPV-Test oder p16/Ki67 Dual-stain zur Folge haben
Doug Altman: driving critical appraisal and improvements in the quality of methodological and medical research by Willi Sauerbrei( )

1 edition published in 2021 in English and held by 3 WorldCat member libraries worldwide

Abstract: Doug Altman was a visionary leader and one of the most influential medical statisticians of the last 40 years. Based on a presentation in the "Invited session in memory of Doug Altman" at the 40th Annual Conference of the International Society for Clinical Biostatistics (ISCB) in Leuven, Belgium and our long-standing collaborations with Doug, we discuss his contributions to regression modeling, reporting, prognosis research, as well as some more general issues while acknowledging that we cannot cover the whole spectrum of Doug's considerable methodological output. His statement "To maximize the benefit to society, you need to not just do research but do it well" should be a driver for all researchers. To improve current and future research, we aim to summarize Doug's messages for these three topics
Overinterpretation and misreporting of prognostic factor studies in oncology: a systematic review by Emmanuelle Kempf( )

1 edition published in 2018 in English and held by 2 WorldCat member libraries worldwide

REporting recommendations for tumor MARKer prognostic studies (REMARK) by Lisa M McShane( )

1 edition published in 2006 in English and held by 2 WorldCat member libraries worldwide

 
moreShow More Titles
fewerShow Fewer Titles
Audience Level
0
Audience Level
1
  General Special  
Audience level: 0.64 (from 0.59 for Multivaria ... to 0.97 for Multivaria ...)

Multivariable model-building : a pragmatic approach to regression analysis based on fractional polynomials for modelling continuous variables
Covers
Alternative Names
Sauerbrei, Wilhelm

Sauerbrei, Willi

Willi Sauerbrei wetenschapper

Languages
English (51)

German (3)