Tobacco Use and the Risk of COVID-19 and Adverse Outcomes

COVID-19 Clinical Trial

Official title:

The Association Between Tobacco Use and COVID-19 Infection and Adverse Outcomes in Three Nordic Countries: a Pooled Analysis

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT05321433
• Other study ID #: 105544
• Status: Completed
• Start date: April 1, 2022
• Est. completion date: December 31, 2023

Study information

• Verified date: March 2024
• Source: Karolinska Institutet
• Contact: n/a
• Is FDA regulated: No
• Study type: Observational [Patient Registry]

Clinical Trial Summary

This is an observational study of pooled population-based samples in three Nordic countries. Country-specific data has already been analysed in previous studies in Sweden, Finland, and Norway. The primary objective is to examine the association between tobacco use, the risk of SARS-CoV-2 infection, and adverse Outcomes using pooled population-based samples.

Description:

The coronavirus disease (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused more than 470 million confirmed cases of COVID-19, and more than 6 million deaths around the world by March 25, 2022 (WHO, 2022). Since the beginning of the COVID-19 pandemic, several factors have been attributed to increasing the risk of infection and adverse outcomes of the COVID-19 disease. Among these factors, the relationship between tobacco use and COVID-19 infection and adverse disease outcomes remained controversial as studies kept reporting mixed findings. Early studies reported what seemed to be a protective effect of tobacco use on COVID-19 infection (Haddad et al.; Jiménez-Ruiz et al., 2020), or hospitalizations due to COVID-19 (Farsalinos et al., 2020; Neira et al., 2021). A more recent ongoing living rapid review, this time including a larger selection of studies with different study designs, found that smokers are at reduced risk of SARS-COVID-19 infection compared to non-smokers (Relative risk 0.67, 95% Credible interval 0.60-0.75) (Simons et al., 2021). These findings opened the way for speculations and hypotheses on the potential mechanisms behind this protective role. However, results from most of these studies may be affected by selection bias as they reported findings from clinical samples or bias due to confounding as the structure of these published data permitted only univariate analysis. Results from studies that suffer from selection bias or bias due to confounding should be handled with caution as they may undermine years of public health education against tobacco use, a major cause of morbidity and mortality worldwide. Moreover, the role of tobacco use in disease progression such as disease requiring hospitalization, ICU, and death remains unclear as most of the previous studies focused more on the association between tobacco use and the risk of infection, but not the adverse outcomes. These facts call for studies that ensure addressing any knowledge gap on the relation between tobacco and COVID-19 by taking into consideration 1) decreasing the risk for confounding and selection bias; 2) increasing precision through a higher sample size, 3) further investigating the association between tobacco use and adverse disease outcomes. In most Nordic countries, the profile of tobacco use in the underlying populations allows the analysis of several types of tobacco use e.g. cigarette smoking and smokeless tobacco (snus) use, enabling further insights into the potential role of nicotine in the association between tobacco use and COVID-19. The use of smokeless tobacco is highly prevalent (even exceeding the prevalence of smoking among men in Sweden and Norway), which will allow us to disentangle a potential role of nicotine in the association between tobacco use and COVID-19. The investigators propose to examine the associations between tobacco use, COVID-19 infection, and adverse disease outcomes by using pooled population-based data from three Nordic countries, adjusting for potential confounders. The population-based nature of the samples minimizes selection bias Using a pooled analysis will accrue a large sample size and increase the potential for well-powered sub-groups analyses.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 757585
• Est. completion date: December 31, 2023
• Est. primary completion date: December 31, 2023
• Accepts healthy volunteers: No
• Gender: All
• Age group: 20 Years and older

Eligibility

Exclusion Criteria:

• All subjects who died before the onset of the pandemic (February 2020) in the three countries will be excluded from the analysis.

Related Conditions & MeSH terms

• Communicable Diseases
• COVID-19
• Infections
• Pneumonia
• Pneumonia, Viral
• Respiratory Tract Infections
• SARS-CoV-2 Infection
• Virus Diseases

Locations

Country	Name	City	State
Sweden	Karolinska Institutet	Solna	Stockholm

Sponsors (3)

Lead Sponsor	Collaborator
Karolinska Institutet	Finnish Institute for Health and Welfare, Norwegian Institute of Public Health

Country where clinical trial is conducted

Sweden, 

References & Publications (21)

Andersen PK, Abildstrom SZ, Rosthoj S. Competing risks as a multi-state model. Stat Methods Med Res. 2002 Apr;11(2):203-15. doi: 10.1191/0962280202sm281ra. — View Citation

Austin PC, Lee DS, Fine JP. Introduction to the Analysis of Survival Data in the Presence of Competing Risks. Circulation. 2016 Feb 9;133(6):601-9. doi: 10.1161/CIRCULATIONAHA.115.017719. — View Citation

Berry SD, Ngo L, Samelson EJ, Kiel DP. Competing risk of death: an important consideration in studies of older adults. J Am Geriatr Soc. 2010 Apr;58(4):783-7. doi: 10.1111/j.1532-5415.2010.02767.x. Epub 2010 Mar 22. — View Citation

Farsalinos, K., Barbouni, A., & Niaura, R. (2020). Smoking, vaping and hospitalization for COVID-19. Qeios.

Fine, J. P., & Gray, R. J. (1999). A proportional hazards model for the subdistribution of a competing risk. Journal of the American Statistical Association, 94(446), 496-509.

Galanti, M. R. (2021). Tobacco Use and the Risk of COVID-19. ClinicalTrials.gov: NCT04896918. 2021. [Available from: https://clinicaltrials.gov/ct2/show/NCT04896918].

Goldstein, H. (1995). Multilevel Statistical Models, Chapter 2. Edward Arnold. In: London, Wiley, New York.

Haddad C, Bou Malhab S, Sacre H, Salameh P. Smoking and COVID-19: A Scoping Review. Tob Use Insights. 2021 Feb 15;14:1179173X21994612. doi: 10.1177/1179173X21994612. eCollection 2021. — View Citation

Hilbe, J. M. (2011). Negative binomial regression. Cambridge University Press.

Hilbe, J. M. (2014). Modeling count data. Cambridge University Press.

Ioannidis JPA. Over- and under-estimation of COVID-19 deaths. Eur J Epidemiol. 2021 Jun;36(6):581-588. doi: 10.1007/s10654-021-00787-9. Epub 2021 Jul 28. — View Citation

Jimenez-Ruiz CA, Lopez-Padilla D, Alonso-Arroyo A, Aleixandre-Benavent R, Solano-Reina S, de Granda-Orive JI. [COVID-19 and Smoking: A Systematic Review and Meta-Analysis of the Evidence]. Arch Bronconeumol. 2021 Jan;57:21-34. doi: 10.1016/j.arbres.2020.06.024. Epub 2020 Jul 25. Spanish. — View Citation

Kim HT. Cumulative incidence in competing risks data and competing risks regression analysis. Clin Cancer Res. 2007 Jan 15;13(2 Pt 1):559-65. doi: 10.1158/1078-0432.CCR-06-1210. — View Citation

Laake I, Tunheim G, Robertson AH, Hungnes O, Waalen K, Haberg SE, Mjaaland S, Trogstad L. Risk of pregnancy complications and adverse birth outcomes after maternal A(H1N1)pdm09 influenza: a Norwegian population-based cohort study. BMC Infect Dis. 2018 Oct 22;18(1):525. doi: 10.1186/s12879-018-3435-8. — View Citation

Magnus P, Birke C, Vejrup K, Haugan A, Alsaker E, Daltveit AK, Handal M, Haugen M, Hoiseth G, Knudsen GP, Paltiel L, Schreuder P, Tambs K, Vold L, Stoltenberg C. Cohort Profile Update: The Norwegian Mother and Child Cohort Study (MoBa). Int J Epidemiol. 2016 Apr;45(2):382-8. doi: 10.1093/ije/dyw029. Epub 2016 Apr 10. — View Citation

Peña, S., Ilmarinen, K., Kestilä, L., & Karvonen, S. (2021). Tobacco Use and COVID-19 Incidence in the Finnish General Population (Tobrisk-CoV). ClinicalTrials.gov: NCT04915781. 2021. [Available from: https://clinicaltrials.gov/ct2/show/NCT04915781]. https://clinicaltrials.gov/ct2/show/NCT04915781

Puebla Neira D, Watts A, Seashore J, Polychronopoulou E, Kuo YF, Sharma G. Smoking and risk of COVID-19 hospitalization. Respir Med. 2021 Jun;182:106414. doi: 10.1016/j.rmed.2021.106414. Epub 2021 Apr 17. — View Citation

Simons D, Shahab L, Brown J, Perski O. The association of smoking status with SARS-CoV-2 infection, hospitalization and mortality from COVID-19: a living rapid evidence review with Bayesian meta-analyses (version 7). Addiction. 2021 Jun;116(6):1319-1368. doi: 10.1111/add.15276. Epub 2020 Nov 17. — View Citation

Southern DA, Faris PD, Brant R, Galbraith PD, Norris CM, Knudtson ML, Ghali WA; APPROACH Investigators. Kaplan-Meier methods yielded misleading results in competing risk scenarios. J Clin Epidemiol. 2006 Oct;59(10):1110-4. doi: 10.1016/j.jclinepi.2006.07.002. — View Citation

WHO. (2022). Coronavirus (COVID-19) Dashboard. https://covid19.who.int/]

Zou G. A modified poisson regression approach to prospective studies with binary data. Am J Epidemiol. 2004 Apr 1;159(7):702-6. doi: 10.1093/aje/kwh090. — View Citation

* Note: There are 21 references in all — Click here to view all references

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Any diagnosis of COVID-19 measured as follows:	Sweden: at least a positive polymerase chain reaction test (PCR) reported by the laboratories to Sweden's national electronic surveillance system for communicable diseases (SmiNet).; Finland: cases with a positive SARS-CoV-2 reverse transcription PCR (RT-PCR), either informed by a laboratory or by a physician as a record of an International Classification of Diseases, Tenth Revision (ICD-10) code U07.1 (which requires a positive SARS-CoV-2 RT-PCR).; Norway: a positive test for SARS-CoV-2 based on PCR obtained from The Norwegian Surveillance System for Communicable Diseases (MSIS) or the presence of antibodies for SARS-CoV-2.; Out of these definitions a categorical variable will be created (No recorded COVID-19 diagnosis= 1, registered COVID-19 diagnosis= 2)	February 2020 - December 2020
Primary	Hospital admission for COVID-19 measured as follows:	Any hospital admission with a diagnosis of COVID-19 (ICD-10 codes U071 and U072). The diagnosis could be registered either as a main or as a concomitant diagnosis.; A. A categorical variable for hospital admission with any diagnosis of COVID-19 (either main or secondary diagnosis) will be created (No admissions= 1, any admission= 2).; B. A categorical variable for hospital admission with COVID-19 as the main diagnosis only (No admissions= 1, any admission= 2).	February 2020 - December 2020
Primary	Intensive unit care because of a diagnosis of COVID-19 measures as follows:	Admission to an intensive care unit (ICU) because of a diagnosis of COVID-19 (ICD-10 codes as above). A categorical variable for intensive unit care because of a diagnosis of COVID-19 (No/Yes) will be created (No ICU care= 1, any ICU care= 2).	February 2020 - December 2020
Primary	Death for COVID-19 measured as follows:	Death due to COVID-19 will be established using the Swedish, Finnish, and Norwegian Cause of Death Registries. All deaths occurring during the follow-up period with COVID-19 registered as the main cause will be included.	February 2020 - December 2020
Secondary	Length of hospital stay for COVID-19	As a secondary analysis, we will use a negative binomial count model (Hilbe, 2011, 2014) to assess inpatient length of stay measured as the cumulative number of days of hospitalization, as an indicator of disease severity among tobacco users compared to non-tobacco users.	February 2020 - December 2020

External Links

•   Tobacco Use and COVID-19 Incidence in the Finnish General Population (Tobrisk-CoV). ClinicalTrials.gov: NCT04915781.
•   Tobacco Use and the Risk of COVID-19. ClinicalTrials.gov: NCT04896918.