Course with Prof. Emmanuel Lesaffre

The course has reached its full capacity and the registration is now CLOSED!

The Czech National Group of the

International Society for Clinical Biostatistics

in cooperation with the

Institute of Computer Science AS CR in Prague &

Faculty of Mathematics and Physics, Charles University in Prague

is delighted to invite you to attend

a 1-day course on

„Principles of Biostatistical Reasoning:

A Practical Introduction to Statistical Methods in Clinical Research“

presented by

Prof. Emmanuel Lesaffre, Ph.D.

Professor in Biostatistics

Chair, Department of Biostatistics, Erasmus MC, Rotterdam, the Netherlands

L-Biostat, School of Public Health, KULeuven University of Leuven, Belgium

Where: Institute of Computer Science AS CR

(in Czech: Ústav informatiky AV ČR, v.v.i.)

Room # 318

Pod Vodárenskou věží 2

Prague 8 - Ládví (Metro red line "C", exit "Ládví")

Czech Republic

When: October 17, 2014 (Friday)

Registration deadline: Sep 30, 2014 (payment needs to be received by this date)

(ii) Posting an appropriate payment to the bank account shown below (bank transfer only)

Registration rates:

Payments only via bank transfer (*** all international payments need to be made in EUR ***)

All domestic (CZK) and international transfers (EUR), except Slovakia

Account number: 2100009829 / 2010

Transfers from Slovakia only (EUR)

Account number: 2100009829 / 8330

IBAN: CZ3820100000002100009829

BIC code/SWIFT: FIOBCZPPXXX

Bank name and address: Fio banka, a.s., V Celnici 1028/10, Praha 1, Czech Republic

Course Venue:

Institute of Computer Science AS CR

Pod Vodarenskou vezi 2

182 07 Prague

Czech Republic

Web: http://www.ustavinformatiky.cz/?id_jazyk=en

Course Secretary:

Ms. Lenka Semeráková

Dept. of Medical Informatics & Biostatistics

Institute of Computer Science AS CR

Tel. +420 266 053 640

E-mail: semerakova@cs.cas.cz

The Course Outline

Clinical journals are becoming more and more demanding regarding the correct use of statistics in clinical research. This puts clinical researchers under pressure to make sure that their data are analyzed in an appropriate manner. Most likely this is the job for the collaborating statistician, but also the clinical researcher should master the key concepts in statistics at the least to communicate with the statistician. To put it more positively: good clinical research involves a tremendous amount of (human and financial) resources; it would then be a shame to waste all that hard work by poor statistics. After all, the combination of good clinical research with a good statistical analysis is the key to publication of your work in highly reputed clinical journals.

This course introduces or refreshes the clinical researchers to basic statistical concepts. However, also novel concepts are introduced. Mathematics is restricted to the bare minimum. Ample examples from clinical research are used as illustrations. Summarized, the course aims to convey the basic principles behind good statistical practice and hence it is hoped that thereby the participants may communicate more efficiently with the statistician, but also will have developed a more critical attitude towards appropriate methodology in the published clinical literature.

The Course' Content

• The choice of appropriate descriptive statistics

• A brief review of the fundaments of classical statistics, i.e. the p-value and the confidence interval, together with pitfalls in the use of the P-value as tool for inference. This includes also determining the necessary sample size of a clinical study

• Fundamental and practical aspects in the design of the clinical study, involving e.g. the choice between an epidemiological and randomized clinical trial, cross-over versus parallel group designs, factorial designs, stratified analyses, etc.

• The randomized clinical trial (RCT): stages in drug research, choice between a superiority and non-inferiority study in stage III RCTs, group-sequential and adaptive RCTs, the basics of meta-analyses

• A brief introduction of regression models: classical linear regression, logistic regression and Cox regression

• Guidelines for analyzing and reporting the findings of your study, including e.g. CONSORT guidelines, STROBE guidelines, etc.

Tentative Course Schedule

8:00 - 9:00 Registration

9:00-12:00 Morning session (includes 15 min coffee break)

12:00-13:00 Lunch break

13:00-16:00 Afternoon session (includes 15 min coffee break)

16:10-16:30 Closing discussion and course evaluation