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Volume 13
Issue 3
10.3390/life13030777
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Article

Target Trial Emulation Using Hospital-Based Observational Data: Demonstration and Application in COVID-19

by
Oksana Martinuka
1,
Maja von Cube
1,
Derek Hazard
1,
Hamid Reza Marateb
2,3,
Marjan Mansourian
3,4,
Ramin Sami
5,
Mohammad Reza Hajian
5,
Sara Ebrahimi
6 and
Martin Wolkewitz
1,*
1
Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Centre, University of Freiburg, 79104 Freiburg, Germany
2
Biomedical Engineering Department, Engineering Faculty, University of Isfahan, Isfahan 81746-73441, Iran
3
Biomedical Engineering Research Centre (CREB), Automatic Control Department (ESAII), Universitat Politècnica de Catalunya-Barcelona Tech (UPC) Building H, Floor 4, Av. Diagonal 647, 08028 Barcelona, Spain
4
Department of Epidemiology and Biostatistics, School of Health, Isfahan University of Medical Sciences, Isfahan 81746-73461, Iran
5
Department of Internal Medicine, School of Medicine, Isfahan University of Medical Sciences, Isfahan 81746-73461, Iran
6
Alzahra Research Institute, Alzahra University Hospital, Isfahan University of Medical Sciences, Isfahan 81746-75731, Iran
*
Author to whom correspondence should be addressed.
Life 2023, 13(3), 777; https://doi.org/10.3390/life13030777
Submission received: 6 February 2023 / Revised: 2 March 2023 / Accepted: 8 March 2023 / Published: 13 March 2023
(This article belongs to the Special Issue COVID-19 Prevention and Treatment: 2nd Edition)
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Abstract

Methodological biases are common in observational studies evaluating treatment effectiveness. The objective of this study is to emulate a target trial in a competing risks setting using hospital-based observational data. We extend established methodology accounting for immortal time bias and time-fixed confounding biases to a setting where no survival information beyond hospital discharge is available: a condition common to coronavirus disease 2019 (COVID-19) research data. This exemplary study includes a cohort of 618 hospitalized patients with COVID-19. We describe methodological opportunities and challenges that cannot be overcome applying traditional statistical methods. We demonstrate the practical implementation of this trial emulation approach via clone–censor–weight techniques. We undertake a competing risk analysis, reporting the cause-specific cumulative hazards and cumulative incidence probabilities. Our analysis demonstrates that a target trial emulation framework can be extended to account for competing risks in COVID-19 hospital studies. In our analysis, we avoid immortal time bias, time-fixed confounding bias, and competing risks bias simultaneously. Choosing the length of the grace period is justified from a clinical perspective and has an important advantage in ensuring reliable results. This extended trial emulation with the competing risk analysis enables an unbiased estimation of treatment effects, along with the ability to interpret the effectiveness of treatment on all clinically important outcomes.
Keywords: competing events; COVID-19; methodology; observational data; target trial emulation competing events; COVID-19; methodology; observational data; target trial emulation

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MDPI and ACS Style

Martinuka, O.; Cube, M.v.; Hazard, D.; Marateb, H.R.; Mansourian, M.; Sami, R.; Hajian, M.R.; Ebrahimi, S.; Wolkewitz, M. Target Trial Emulation Using Hospital-Based Observational Data: Demonstration and Application in COVID-19. Life 2023, 13, 777. https://doi.org/10.3390/life13030777

AMA Style

Martinuka O, Cube Mv, Hazard D, Marateb HR, Mansourian M, Sami R, Hajian MR, Ebrahimi S, Wolkewitz M. Target Trial Emulation Using Hospital-Based Observational Data: Demonstration and Application in COVID-19. Life. 2023; 13(3):777. https://doi.org/10.3390/life13030777

Chicago/Turabian Style

Martinuka, Oksana, Maja von Cube, Derek Hazard, Hamid Reza Marateb, Marjan Mansourian, Ramin Sami, Mohammad Reza Hajian, Sara Ebrahimi, and Martin Wolkewitz. 2023. "Target Trial Emulation Using Hospital-Based Observational Data: Demonstration and Application in COVID-19" Life 13, no. 3: 777. https://doi.org/10.3390/life13030777

APA Style

Martinuka, O., Cube, M. v., Hazard, D., Marateb, H. R., Mansourian, M., Sami, R., Hajian, M. R., Ebrahimi, S., & Wolkewitz, M. (2023). Target Trial Emulation Using Hospital-Based Observational Data: Demonstration and Application in COVID-19. Life, 13(3), 777. https://doi.org/10.3390/life13030777

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