In April 2018 I retired from the Luxembourg Institute of Health, a publicly funded health care research institute in Luxembourg. I no longer take on postgraduate students. The list of topics here are thus mainly of historical rather than potential future interest
Basically I am interested in any aspect of statistics that has to do with the pharmaceutical industry and drug development. There is a list of my publications: here However, and my blogs may also be of interest. My interests can be organised under the following headings.
I make some brief comments about these interests below.
A particular emphasis of this work has been design and analysis of cross-over trials and I have a book on the subject with Wiley (first edition 1993, second edition 2002) Cross-over Trials in Clinical Research. My collaborators in this area have included Andy Grieve (several times), and my PhD students Dimitris Lambrou, Sally Lee and Boikanyo Makubate as well as Farkad Ezzet, Pina D'Angelo, Diane Potvin, Denise Till, Juergen Lillienthal, Francesco Patalano and Hartwig Hildebrand. Bioequivalence is a particular field of application for cross-over trials that has interesting philosophical implications and is also something I have written on. In particular I believe that more pharmacokinetic and pharmacodynamic insights should be employed in designing and analysing cross-over trials. I also believe that cross-over trials have a very important role to play in personalized medicine.
However, I have also been interested in parallel group trials, and in particular anything to do with designing and interpreting multi-centre trials. (Actually that is more or less all parallel group trials but what I mean by this is that it is specifically the multi-centre aspect of such trials that interests me.) My PhD students Andy Garrett and Steven Julious have worked in problems to do with parallel group studies, the former with matters to do with subgroup analysis and the latter with sample size determination when nuisance parameters are unknown. See also my book Statistical Issues in Drug Development (Wiley, 1997, second edition 2007, third edition due 2021) for examples of some of the interesting problems that can arise.
Most of my work in the area of clinical trials is readily accessible but one of my favourite papers is in a Liber Amicorum for Roel van Strik (Erasmus University, 1996) and is hard to get hold of and is therefore included here on this website. The AB.BA Cross-over. How to perform the two-stage analysis if you can't be persuaded that you shouldn't.
I am also interested in the
use of prognostic information in analysing clinical
trials and have had separate collaborations with Emmanual
Measurement is also a theme that interests me. In my opinion many clinical measurements used are wasteful of information and not a few are potentially very misleading. I have been collaborating in this area with Steven Julious and more recently also with Katie Rolfe.
I am particularly interested in anything to do with P-values or with parallels with and differences between Bayesian and frequentist modes of inference. (See, for example, You May Believe You are a Bayesian but You are Probably Wrong.) I also am interested in issues to do with randomisation and additivity and also causal inference (although I have not produced much in the latter area yet - but I have ambitions!) and have done some work on multiplicity with Frank Bretz.
My research in this field has been mainly on the use of placebos and the applications of Rawlsian theories of justice to the conduct of clinical trials. I am also interested in the issue of honest reporting of scientific findings both in and out of the pharmaceutical industry.
My interests here are in weighting to allow for imprecisely estimated variances and also in interpretation of effects in the presence of varying background risk as well as comparison of Bayesian and frequentist approaches.
A particular concern is that current approaches to reporting safety data, including in monitoring clinical trials, are very destructive of information. I have participated in a number of data safety monitoring boards and am interested in principle in trying to develop methods for better monitoring.
During the last two of the eight years (1987-1995) I worked for CIBA-Geigy, I was involved, amongst other matters, in looking at the question of how one decides which drugs to develop. My interest in decision analysis grew out of that. I have some papers on the subject of portfolio management. I have collaborated with Carl-Fredrik Burman (Astra-Zeneca) and Andy Grieve (Pfizer) on applications of decision analysis to drug development. Again this is a topic that has an important role to play in personalized medicine.
researching the first edition of my cross-over trials book I became intrigued
by the story of Cushny and Peebles and the trial they
organised at Kalamazoo, the data from which were
(incorrectly) reported by Student in his famous paper in Biometrika.
Bill Richardson and I published a paper in Statistics in Medicine (1994)
on the subject. I have remained interested in the history of statistics and
have also written a paper about RA Fisher's only involvement in a clinical
trial. The history of statistics is also a feature of my book with
I was involved in the multi-disciplinary EPSRC-funded SCAM project. More details are given here The SCAM project: Simplicity, Complexity and Modelling. Together with other members of the team, Peter Challenor, Andrew Cliffe, Mike Christie, Philip Dawid, Suraje Dessai, Jim Hall, Zoran Kapelan and Jeremy Oakley, I have written a book for Wiley. Simplicity, Complexity and Modelling
More recently I have collaborated with Nick Holford and Hans Hockey on modeling observations below the limit of quantitation (specifically in the context of pharmacokinetics).
Rob Donald did a PhD with me as one of his supervisors in real-time modeling in the context of intensive care. I would like to claim credit for this but in fact the idea is all his own!
In my opinion this whole field is in a terrible mess. Some excellent work has been done but it is lost in the hype and the noise. Contrary to popular belief, for most diseases, we do not know what percentage of patients respond because the work on isolating the components of variation, between patient, within patient and patient by treatment interaction has not been done. Progress in this area will depend on a synthesis of research from laboratory to patient. Unfortunately at the moment it is being driven by the former. This is likely to continue to be the focus of my research over the next few years.
Comets, Contagion and Contingency
A paper criticising an aspect of Hoyle and Wickramasinghe's cometary theory
and presented to the International Society for Clinical Biostatistics in
An incomplete blocks cross-over trial in asthma. A paper published as, ������ Senn, SJ, Lillienthal, J, Patalano, F, Till, MD, An incomplete blocks cross-over in asthma: a case study in collaboration, in Cross-over Clinical Trials, Vollmar, J., and Hothorn, L. A., Eds., Fischer, Stuttgart;1997 pp. 3-26, but available here in pre-print form.
These are datasets to accompany various papers I have written.
1. Programs to accompany Cross-over Trials in Clinical Research .2, SAS� macros for meta-analysis (First author Jim Weir and important input from Tsushung Hua, Connie Berlin, Mike Branson, Ekkehard Glimm) 3. Programs for analysing cross-over trials in infertility (Mainly written by Boikanyo Makubate.)
Previously, I had suggestions for topics in the following areas. P indicates practical and T theoretical and the number of stars indicates the degree of each. A D indicates a topic that is likely to be difficult.
� Decision analysis and sequential bioequivalence P* T*** D (Taken by Odile Coudert, MSc awarded 2006)
� Cross-over trials in infertility P* T*** (Taken by Boikanyo Makubate, PhD awarded 2009)
� Translation into SAS� and R of an existing Mathcad�� computer tool for sample-size determination for cross-over trials (MSc only) P*** T*� (Taken by Michael Tracy, MSc� awarded 2009)
� Power comparison of Prescott's test and the Mainland-Gart test for cross-over trials with binary outcomes P* T***
� Random effects for variance estimates for meta-analysis P*T*** (Taken by Giorgio DiGessa, MSc awarded 2008)
� Realistic priors for related parameters P*T***D
� Quality of meta-analyses, an empirical investigation� P**** (Taken by Edith Eze, MSc awarded 2009)
� Implications of size (of trial) dependent effects for meta-analysis P* T***
� Random effects variances and effect sizes in meta-analysis an empirical investigation P**T* (Taken by Nicola Greenlaw, MSc awarded 2010)
� Comparison of propensity score and analysis of covariance P** T**
� Problems with propensity based multiple imputation P** T*** (Taken by Jim Weir, MSc awarded 2006)
� Decision analytic approaches to using biomarkers and surrogate endpoints in clinical trials T**** D
� Two-tailed tests for discrete data T****
� Predicting patient recruitment P*** T* (Taken by Andisheh Bakhshi. MSc awarded 2012)
� Analysis of data on spontaneous reports of adverse events associated with drugs P**T**D (Taken by Emmanuel Baah, PhD awarded 2014)
� Decision analysis and implication for ethics of clinical trials T**** D
� Equivalence of Inhaled Formulations.htm� P**T**D
I maintain a declaration of all* my interests in order that all those who find this a useful way to judge work may judge my work accordingly.
*That is to say all that I have not missed due to oversight
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This page last updated 23 February 2021.