gms | German Medical Science

62. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e. V. (GMDS)

Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie

17.09. - 21.09.2017, Oldenburg

Design of observational studies and the need for guidance – prognostic studies as an example

Meeting Abstract

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  • Peggy Sekula - Universitätsklinikum Freiburg, Freiburg, Deutschland

Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie. 62. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e.V. (GMDS). Oldenburg, 17.-21.09.2017. Düsseldorf: German Medical Science GMS Publishing House; 2017. DocAbstr. 236

doi: 10.3205/17gmds050, urn:nbn:de:0183-17gmds0504

Veröffentlicht: 29. August 2017

© 2017 Sekula.
Dieser Artikel ist ein Open-Access-Artikel und steht unter den Lizenzbedingungen der Creative Commons Attribution 4.0 License (Namensnennung). Lizenz-Angaben siehe



For any study in medical research, design is a key aspect. A good design tries to handle potential issues and threat. Problems overlooked at the time of designing a study can introduce biases that often cannot be addressed adequately at a later stage and thus limit both the internal and external validity of a study. Topic Group 5 (TG5) of the STRengthening Analytical Thinking for Observational Studies (STRATOS) Initiative focuses on these issues and aims to provide accessible guidance for the design of observational studies, in addition to already existing literature such as reporting guidelines [1].

Although many of the discussed issues are also relevant to other types of studies, the focus herein is on observational studies assessing the prognostic impact of single biomarkers. Such studies have become increasingly common partly because of the demand of medical decisions tailored to individual patients. The need for general guidance in this area has long been recognised and discussed because methodological weaknesses are common regarding design, conduct, analysis and reporting of such studies.

Especially in cancer research, where clinical data and biosamples from patients are often collected during routine care, studies on the prognostic potential of a specific biomarker can be conducted rather easily and quickly by making use of these archives. These circumstances may tempt researchers to proceed in a ‘quick and dirty’ fashion without thorough design of a suitable project which can provide (nearly) unbiased information. I will present examples from published literature to illustrate the need for guidance specifically regarding aspects such as research question, sample size calculation or selection bias.

Die Autoren geben an, dass kein Interessenkonflikt besteht.

Die Autoren geben an, dass kein Ethikvotum erforderlich ist.


Sauerbrei W, Abrahamowicz M, Altman DG, le Cessie S, Carpenter J; STRATOS initiative. STRengthening analytical thinking for observational studies: the STRATOS initiative. Stat Med. 2014;33(30):5413-32. DOI: 10.1002/sim.6265 Externer Link