PHARMACEUTICAL STATISTICS

Pharmaceut. Statist. 2006; 5: 75–77

Published online in Wiley InterScience (www.interscience.wiley.com).

Book Reviews

This section of the journal aims to inform you about recent

books. We target books specifically about the theory and

application of statistics in the pharmaceutical sector, though

reviews of statistical books relevant to a wider audience are also

welcome. We cover new books or substantially new editions,

and include both those aimed at statisticians and those intended

to inform scientists about statistics. We are particularly

interested in comparative reviews of books on a similar subject.

Please contact Peter Lane (peter.w.lane@gsk.com) to offer to

review a book or suggest further books that should be reviewed.

You can find a list of books already suggested on the PSI

website, at

http://www.psiweb.org/resources/resources.asp?parent

folderid=252&subgroup_id=4 and on the Wiley website, at

http://www3.interscience.wiley.com/cgi-bin/jabout/

93012805/Reviews.html

These include information about the current status of

reviews, and are updated approximately monthly; the

list is also published quarterly in SPIN, the newsletter of

the PSI.

Encyclopedia of Biopharmaceutical Statistics

Edited by Chow S-C (2003)

ISBN 0824742613 (paper) 1055 pages; £252; $445

ISBN 0824742621 (electronic); £153; $252 (combined purchase

available)

Dekker, marketed by Taylor-Francis and CRC; http:/www.

crcpress.com/

This is an impressive collection of material describing those

processes and techniques in the pharmaceutical industry that

are particularly relevant to statisticians. Most of the articles

have been written by individuals contributing just one technical

essay each, averaging about seven pages, though some articles

have two or more authors. They are mostly practitioners within

the industry, who are describing and explaining subjects with

which they have long familiarity. Don’t expect to find enlight-

enment on areas with which you are yourself already familiar,

for this is no deep manual into the complexities of statistical

methods, nor up-to-the-minute review of cutting-edge research.

But who in the industry can claim recent familiarity with a

substantial proportion of the issues that concern us? The book

serves an admirable purpose in providing readable and

informative summaries about areas of which you have not

had recent first-hand experience, including suggestions for

further and deeper reading if needed.

The second edition of this single-volume encyclopaedia

appeared quickly: only three years since the first in 2000. The

intervening time has been spent in almost doubling its size, from

72 topics occupying 535 pages to 141 occupying 1055. I found

only one substantial review of the first edition, in The Statistician

(2001; 50:101–103). The reviewer pointed to three examples of

areas that were then not covered. Two now have their own

articles – logistic regression and survival analysis – as anyone

would expect given the title. The other deficiency noted was of

guidance in specific therapeutic areas: the single article on cancer

trials has now been joined by one on vaccine trials, though there

is nothing specific on trials in other areas such as neurology or the

central nervous system. Another criticism was of inconsistency in

the graphics; the poor examples cited are regrettably still present,

though the quality of the graphs in most articles is good.

I looked up a couple of areas I have been working in recently,

and found the description clear, readable and informative,

though lacking in recent developments and any depth. The

article on ‘Dropout’ gave a well-structured overview of the issues

and described many of the available techniques, including the

usual explanation of MCAR and MAR (Missing Completely At

Random or just At Random) which many will have seen recently

at statistical meetings. I learnt a little more about selection

models, but found no mention of the latest abbreviationMMRM

(Multivariate, or Mixed, according to preference, Models for

Copyright # 2006 John Wiley & Sons, Ltd.Received 15 January 20012006

Repeated Measurements) or any reference to the influential

recent publications by Craig Mallinckrodt. Though SOLAS gets

a mention when describing multiple imputation, none is made of

the MI and MIANALYZE Procedures introduced in SAS 8.

Similarly, the article on ‘Multicenter trials’ covers the material I

am familiar with, but has no references later than 1998.

Looking at an area I have only briefly touched on once, over

five years ago, I found the article on ‘Stability matrix designs’ to

be a useful introduction to the terminology and methodology of

this area of manufacturing. There are several examples to

illustrate the text, and a reasonable list of 24 references for

further reading. I also took a look at a topic about which I

know virtually nothing in the context of clinical trials. The

short three-page article on ‘Ethnic factors’ lays out the

background of this issue briefly, and then gives a series of

assessments in various contexts; however, no references are

given for further reading.

A question that clearly needs answering for a book

of this nature is how it fits in with the competition. Wiley’s

eight-volume Encyclopedia of Biostatistics is now also in

its second edition, appearing in 2005, and can claim far

more width and depth. But at £2095 for the 6100 pages, I can

imagine that many readers will find it hard to get access.

Another alternative nowadays, of course, is to rely on search

engines on the Internet, and seek information on new topics as

and when the need arises. However, despite the ingenuity of the

algorithms, it is unlikely that you will easily find reliable,

authoritative and well-written introductions to specific issues.

So there is clearly a place for this short encyclopedia as a

general reference resource in the pharmaceutical industry.

Peter Lane

Research Statistics Unit, GlaxoSmithKline, UK

(DOI: 10.1002/pst.202)

Design of Studies for Medical Research

Machin D, Campbell MJ (2005)

ISBN 0470 844 957; 286 pages; £29.95; h45.00; $55.00

Wiley; http:/www.wiley.com/

This book provides an excellent overview, as the title states, of

the design of studies for medical research. As the blurb details

‘This book is intended for anyone working in medical research, . . .It will be ideal for anyone embarking upon research for the first

time . . ., but is of relevance to all health and allied health

professionals.’ From the point of view of a statistician, it is not a

statistics text book and does not give detail of statistical analyses.

Instead, it is a text book for statisticians, and other health

professionals involved in medical research, wishing to understand

the importance of, and wishing to implement, good study design.

It provokes the reader into considering the many aspects involved

in designing studies, and is a good resource for the inexperienced

researcher. For those new to medical research, the book provides

an introduction to study design within a wide area of human

research, detailing the design of surveys, clinical trials and

epidemiological studies, as well as studies involved with diag-

nostics and prognostic factors.

The book broadly breaks down medical research into three

areas: preclinical, clinical and epidemiological. There are 11

chapters, covering the following topics: defining evidence in

evidence-based health care; the importance of appropriate

measurements and measurement tools; principles of study-size

calculation; randomization; cross-sectional and longitudinal

studies; surveys, cohorts and case-control studies; general issues

in clinical trials; early phase clinical trials; phase III trials;

diagnosis; and prognostic factor studies. Each chapter contains a

good number of practical examples of the topic being discussed,

giving an extensive reference list, and key design features are

summarized at the end of each section as appropriate. Statistical

detail is discussed only where necessary, and tables of reference

are supplied as an appendix. For the more technical reader, there

are extra technical notes at the end of many of the chapters.

However, these expand only a little further on any statistical

detail mentioned within the chapter.

The first chapter introduces the notion of evidence and the

hierarchy of designs (in terms of the weight given to evidence

obtained) within each of preclinical, clinical and epidemiological

studies. It also introduces statistical considerations, informed

consent and ethics, study protocol and reporting. The second

chapter is concerned with the design of forms and questionnaires,

and the importance of taking appropriate measurements. It

describes different types of data and measurements, and the

layout and design of forms and questionnaires, and discusses the

issue of data collection and processing. Chapter 3 details the

importance of the study-size calculation, and gives an outline of

the basic workings required to carry out a sample-size calcula-

tion. It details significance tests, hypotheses, and type I and II

errors, and gives sample-size formulae for continuous, binary

and survival outcomes. It discusses the calculation of sample

sizes in practice, considering effect sizes, limited resources,

situations with more than one primary outcome, and internal

pilot studies, with examples to illustrate.

Chapter 4 discusses randomization within preclinical studies,

observational studies, surveys and clinical trials, and also the

practicalities of randomizing patients. Chapter 5 describes the

design of cross-sectional and longitudinal studies, and the

differences between the two. It discusses designs for cross-

sectional studies with a single group, two groups and more than

two groups, and considers repeated measures and autocorrela-

tion for longitudinal studies. Identifying groups to be compared,

achieving representative samples, selecting appropriate endpoints

Book Reviews76

Copyright # 2006 John Wiley & Sons, Ltd. Pharmaceut. Statist. 2006; 5: 75–77