PHARMACEUTICAL STATISTICS

Pharmaceut. Statist. 2008; 7: 302–304

Published online in Wiley InterScience

(www.interscience.wiley.com) DOI: 10.1002/pst.353

Literature Review July– September 2008

Kevin Carroll1,�,y and S. Krishna Padmanabhan2

1AstraZeneca Pharmaceuticals, CMOs Office, Alderley Park, Macclesfield, UK2Wyeth Research and Development, 500 Arcola Rd, Collegeville, PA 19426, USA

INTRODUCTION

This review covers the following journals receivedduring the period from July to September 2008:

� Applied Statistics, volume 57, part 4.� Biometrical Journal, volume 50, issues 3 and 4.� Biometrics, volume 64, issue 3.� Biometrika, volume 95, issue 3.� Biostatistics, volume 9, part 3.� Clinical Trials, volume 5, part 3.� Drug Information Journal, volume 42, part 4.� Journal of Biopharmaceutical Statistics, volume

18, part 4.� Statistics in Medicine, volume 27, parts 16–20.� Statistical Methods in Medical Research,

volume 17, part 4.

SELECTED HIGHLIGHTS FROMTHE LITERATURE

Regulation

Given the ever-increasing importance of China indrug development, an informative paper regardingrequirements for clinical trials conducted in Chinacan be found here.

� Chen F et al. Current statistical requirementsfor pharmaceutical clinical trials in China.Drug Information Journal 2008; 42:321–330.

Interim analyses, flexible designs and data mon-

itoring committees

An interesting paper, together with commentary,regarding final, upward alpha level adjustment inthe case of interim analyses where the intention isto stop only for harm (or futility) and not foroverwhelming efficacy, is well worth a read:

� Dallas MJ. Accounting for interim safetymonitoring of an adverse event upon termina-tion of a clinical trial. Journal of Biopharma-ceutical Statistics 2008; 18:631–638.

� Tsong Y. Commentary on ‘Accounting forinterim safety monitoring of an adverse eventupon termination of a clinical trial’. Journalof Biopharmaceutical Statistics 2008; 18:

639–640.� Liu J-P. Commentary on ‘Accounting for the

interim safety monitoring of an adverse eventupon termination of a clinical trial’. Journal ofBiopharmaceutical Statistics 2008; 18:641–643.

� ‘Response to commentary’. Journal of Bio-pharmaceutical Statistics 2008; 18:644–645.

Data analysis

Longitudinal data analysis and the handling ofmissing data is a longstanding problem in clinicaltrials. Mallinckrodt and colleagues provide aposition paper and recommendations for theanalysis of such data:

� Mallinckrodt CH et al. Recommendations forthe primary analysis of continuous endpointsin longitudinal clinical trials. Drug InformationJournal 2008; 42:321–330.yE-mail: kevin.carroll2@astrazeneca.com

*Correspondence to: Kevin Carroll, AstraZeneca Pharma-ceuticals, CMOs Office, Alderley Park, Macclesfield, UK.

Copyright r 2008 John Wiley & Sons, Ltd.

It can sometimes be a challenge for the non-statistician to fully appreciate what the hazardratio means in survival and time to event analyses.A nice reformulation of this quantity is providedin the following paper:

� Moser BK, McCann M. Reformulating thehazard ratio to enhance communication withclinical investigators. Clinical Trials 2008;5:248–252.

Over recent years, interest has been growingin how best to analyse interval censoredsurvival data. The following papers are interest-ing additions to the growing literature in thisarea.

� Huang J et al. A generalized log-rank test forinterval-censored failure time data via multipleimputation. Statistics in Medicine 2008;27:3217–3226.

� Zhao X et al. Generalized log-rank tests forpartly interval-censored failure time data.Biometrical Journal 2008; 50:375–385.

Fisher’s exact test is firmly established as theanalysis method of choice for binary outcomes incomparative clinical trials. The following papertakes a closer look at this test, particularly in termsof the actual significance level attained and istherefore well worth a read.

� Crans GG, Shuster JJ. How conservative isFisher’s exact test? A quantitative of the two-sample comparative binomial trial. Statistics inMedicine 2008; 27:3598–3611

In clinical trials, it is often of interest to examinerare events, such as adverse events, in terms ofrelative event rates per x 1000 patient yearsexposure. There are, however, several possibilitiesfor the calculation of the confidence interval forthe event rate ratio that can leave the statisticianpondering which is best. The following papercomes to the aid of the confused statisticianby comparing and contrasting the variousapproaches.

� Barker L and Cadwell BL. An analysis ofeight 95 per cent confidence intervals for aratio of Poisson parameters when eventsare rare. Statistics in Medicine 2008;27:4030–4037.

The analysis of survival data when there isevidence of non-proportionality can be challen-ging. The following interesting papers providesomewhat differing approaches to the problem:

� Wei G and Schaubel DE. Estimating cumu-lative treatment effects in the presence ofnonproportional hazards. Biometrics 2008;64:724–732.

� Logan BR, Klein JP and Zhang M-J. Compar-ing treatments in the presence of crossingsurvival curves: An application to bone mar-row transplantation. Biometrics 2008; 64(3):733–740.

A substantial number of papers has been writtenon the issue of multiple testing in clinical trials sothat the volume of the literature in this area can bea little overwhelming. Fortunately, a nice, com-prehensive review of multiple testing methods isprovided in the following paper:

� Farcomeni A. A review of modern multiplehypothesis testing, with particular attention tothe false discovery proportion. StatisticalMethods in Medical Research 2008; 17:347–388.

Design

Simulation is an important and frequentlyused tool in the design of clinical trials. Westfallet al. provide a useful and comprehensive overviewof clinical trial simulation that will likely be ofsome value to all those engaged in complex trialdesign:

� Westfall PH et al. Clinical trials simulation: astatistical approach. Journal of Biopharmaceu-tical Statistics 2008; 18:611–630.

Copyright r 2008 John Wiley & Sons, Ltd. Pharmaceut. Statist. 2008; 7: 302–304DOI: 10.1002/pst

Literature Review 303

The design and analysis of dose finding studiescontinues to be the subject of huge swathes ofstatistical literature. The sheer volume of papers onthe subject is quite literally dizzying. The bewilderedstatistician looking for a nice overview of the issues

is likely to find some solace in the following paper:

� Bretz F, Hsu J, Pinheiro J and Liu Y. Dosefinding – a challenge in statistics. BiometricalJournal 2008; 50:480–504.

Copyright r 2008 John Wiley & Sons, Ltd. Pharmaceut. Statist. 2008; 7: 302–304DOI: 10.1002/pst

304 Literature Review