Why to use propensity score in observational studies? Case study based on data from the Czech clinical database AHEAD 2006-09

LITTNEROVÁ, Simona, Jiří JARKOVSKÝ, Jiří PAŘENICA, Tomáš PAVLÍK, Jindřich ŠPINAR and Ladislav DUŠEK. Why to use propensity score in observational studies? Case study based on data from the Czech clinical database AHEAD 2006-09. Cor et Vasa. Praha: Česká kardiologická společnost, 2013, vol. 55, No 4, p. e383-e390, 8 pp. ISSN 0010-8650. Available from: https://dx.doi.org/10.1016/j.crvasa.2013.04.001.

Basic information

• Original name: Why to use propensity score in observational studies? Case study based on data from the Czech clinical database AHEAD 2006-09
• Authors: LITTNEROVÁ, Simona (203 Czech Republic, guarantor, belonging to the institution), Jiří JARKOVSKÝ (203 Czech Republic, belonging to the institution), Jiří PAŘENICA (203 Czech Republic, belonging to the institution), Tomáš PAVLÍK (203 Czech Republic), Jindřich ŠPINAR (203 Czech Republic, belonging to the institution) and Ladislav DUŠEK (203 Czech Republic, belonging to the institution).
• Edition: Cor et Vasa, Praha, Česká kardiologická společnost, 2013, 0010-8650.

Other information

• Original language: English
• Type of outcome: Article in a journal
• Field of Study: 30201 Cardiac and Cardiovascular systems
• Country of publisher: Czech Republic
• Confidentiality degree: is not subject to a state or trade secret
• RIV identification code: RIV/00216224:14110/13:00066620
• Organization unit: Faculty of Medicine
• Doi: http://dx.doi.org/10.1016/j.crvasa.2013.04.001
• UT WoS: 000409971600017
• Keywords in English: Acute heart failure; AHEAD; Mortality; Propensity score
• Tags: Reviewed

Abstract

Randomized clinical trials represent the gold standard of the evidence based medicine research; nevertheless they may not always be feasible or ethical and the researchers have to rely on observational studies or research databases. However, obtaining reliable results from these studies requires the elimination of potential influence of confounding factors. Fortunately, several statistical methods capable of identifying and reducing the impact of confounding factors exist. One of them is the propensity score which has been frequently used in recent times to estimate relevant clinical effects adjusted for given confounders. This work aims to provide a concise and practical guide to propensity scores by means of an easily understandable case study. The case study is focused on gender differences in mortality rates of patients with acute heart failure in the Czech research database AHEAD (Acute Heart Failure Database).

Links

• GD102/09/H083, research and development project: Name: Informační technologie v biomedicínském inženýrství

Investor: Czech Science Foundation

• MUNI/A/0828/2011, interní kód MU: Name: Matematické a statistické modely v hodnocení výsledků programů screeningu zhoubných nádorů (Acronym: SCREENMOD)

Investor: Masaryk University, Category A