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Competing time-to-event endpoints in cardiology trials - a simulation study to illustrate the importance of an adequate statistical analysis

Standard

Competing time-to-event endpoints in cardiology trials - a simulation study to illustrate the importance of an adequate statistical analysis. / Rauch, Geraldine; Kieser, Meinhard; Ulrich, Sandra; Doherty, Patrick; Rauch, Bernhard; Schneider, Steffen; Riemer, Thomas; Senges, Jochen.

in: EUR J PREV CARDIOL, Jahrgang 21, Nr. 1, 01.2014, S. 74-80.

Publikationen: SCORING: Beitrag in Fachzeitschrift/Zeitung › SCORING: Zeitschriftenaufsatz › Forschung › Begutachtung

Harvard

Rauch, G, Kieser, M, Ulrich, S, Doherty, P, Rauch, B, Schneider, S, Riemer, T & Senges, J 2014, 'Competing time-to-event endpoints in cardiology trials - a simulation study to illustrate the importance of an adequate statistical analysis', EUR J PREV CARDIOL, Jg. 21, Nr. 1, S. 74-80. https://doi.org/10.1177/2047487312460518

APA

Rauch, G., Kieser, M., Ulrich, S., Doherty, P., Rauch, B., Schneider, S., Riemer, T., & Senges, J. (2014). Competing time-to-event endpoints in cardiology trials - a simulation study to illustrate the importance of an adequate statistical analysis. EUR J PREV CARDIOL, 21(1), 74-80. https://doi.org/10.1177/2047487312460518

Vancouver

Rauch G, Kieser M, Ulrich S, Doherty P, Rauch B, Schneider S et al. Competing time-to-event endpoints in cardiology trials - a simulation study to illustrate the importance of an adequate statistical analysis. EUR J PREV CARDIOL. 2014 Jan;21(1):74-80. https://doi.org/10.1177/2047487312460518

Bibtex

@article{c81499c3db2a471382e0bdf765dbdfe9,
title = "Competing time-to-event endpoints in cardiology trials - a simulation study to illustrate the importance of an adequate statistical analysis",
abstract = "BACKGROUND: Clinical trials in cardiology commonly consider time-to-event endpoints that are often influenced by competing risks. In the presence of competing risks, standard survival analysis techniques, such as the Kaplan-Meier estimator, can yield seriously biased results. Although methods to account for competing risks are well known in the statistical literature, they are rarely applied in clinical trials.DESIGN: Simulation study, to demonstrate the appropriate application and interpretation of the competing risks methodology with respect to time-to-event endpoints.METHODS: In this paper, different statistical approaches to account for competing risks are systematically compared, based on a simulation study and using the original data from a cardiology trial.RESULTS: Group comparisons in clinical trials that have competing time-to-event endpoints should be based on the cause-specific hazard functions. In contrast, group comparisons based on event rates should be carried out with care, as event rates are directly influenced by competing events.CONCLUSION: Ignoring or not fully accounting for competing risks may yield misleading or even erroneous results, which could hinder understanding of survival trends; therefore, it is important that competing risks methodology be routinely incorporated into clinical trial standards.",
keywords = "Biomedical Research, Cardiology, Clinical Trials as Topic, Computer Simulation, Data Interpretation, Statistical, Endpoint Determination, Humans, Kaplan-Meier Estimate, Models, Statistical, Proportional Hazards Models, Risk Assessment, Risk Factors, Time Factors, Treatment Outcome, Journal Article",
author = "Geraldine Rauch and Meinhard Kieser and Sandra Ulrich and Patrick Doherty and Bernhard Rauch and Steffen Schneider and Thomas Riemer and Jochen Senges",
year = "2014",
month = jan,
doi = "10.1177/2047487312460518",
language = "English",
volume = "21",
pages = "74--80",
journal = "EUR J PREV CARDIOL",
issn = "2047-4873",
publisher = "SAGE Publications",
number = "1",

}

RIS

TY - JOUR

T1 - Competing time-to-event endpoints in cardiology trials - a simulation study to illustrate the importance of an adequate statistical analysis

AU - Rauch, Geraldine

AU - Kieser, Meinhard

AU - Ulrich, Sandra

AU - Doherty, Patrick

AU - Rauch, Bernhard

AU - Schneider, Steffen

AU - Riemer, Thomas

AU - Senges, Jochen

PY - 2014/1

Y1 - 2014/1

N2 - BACKGROUND: Clinical trials in cardiology commonly consider time-to-event endpoints that are often influenced by competing risks. In the presence of competing risks, standard survival analysis techniques, such as the Kaplan-Meier estimator, can yield seriously biased results. Although methods to account for competing risks are well known in the statistical literature, they are rarely applied in clinical trials.DESIGN: Simulation study, to demonstrate the appropriate application and interpretation of the competing risks methodology with respect to time-to-event endpoints.METHODS: In this paper, different statistical approaches to account for competing risks are systematically compared, based on a simulation study and using the original data from a cardiology trial.RESULTS: Group comparisons in clinical trials that have competing time-to-event endpoints should be based on the cause-specific hazard functions. In contrast, group comparisons based on event rates should be carried out with care, as event rates are directly influenced by competing events.CONCLUSION: Ignoring or not fully accounting for competing risks may yield misleading or even erroneous results, which could hinder understanding of survival trends; therefore, it is important that competing risks methodology be routinely incorporated into clinical trial standards.

AB - BACKGROUND: Clinical trials in cardiology commonly consider time-to-event endpoints that are often influenced by competing risks. In the presence of competing risks, standard survival analysis techniques, such as the Kaplan-Meier estimator, can yield seriously biased results. Although methods to account for competing risks are well known in the statistical literature, they are rarely applied in clinical trials.DESIGN: Simulation study, to demonstrate the appropriate application and interpretation of the competing risks methodology with respect to time-to-event endpoints.METHODS: In this paper, different statistical approaches to account for competing risks are systematically compared, based on a simulation study and using the original data from a cardiology trial.RESULTS: Group comparisons in clinical trials that have competing time-to-event endpoints should be based on the cause-specific hazard functions. In contrast, group comparisons based on event rates should be carried out with care, as event rates are directly influenced by competing events.CONCLUSION: Ignoring or not fully accounting for competing risks may yield misleading or even erroneous results, which could hinder understanding of survival trends; therefore, it is important that competing risks methodology be routinely incorporated into clinical trial standards.

KW - Biomedical Research

KW - Cardiology

KW - Clinical Trials as Topic

KW - Computer Simulation

KW - Data Interpretation, Statistical

KW - Endpoint Determination

KW - Humans

KW - Kaplan-Meier Estimate

KW - Models, Statistical

KW - Proportional Hazards Models

KW - Risk Assessment

KW - Risk Factors

KW - Time Factors

KW - Treatment Outcome

KW - Journal Article

U2 - 10.1177/2047487312460518

DO - 10.1177/2047487312460518

M3 - SCORING: Journal article

C2 - 22964966

VL - 21

SP - 74

EP - 80

JO - EUR J PREV CARDIOL

JF - EUR J PREV CARDIOL

SN - 2047-4873

IS - 1

ER -