COVID-19NCT05321433
Tobacco Use and the Risk of COVID-19 and Adverse Outcomes
An observational study of COVID-19 and Respiratory Tract Infections, run by Karolinska Institutet at 1 site in Sweden.
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. Read more about this study
- Who is it for?
- Ages 20 years and older
- Conditions the study is for
- COVID-19, Respiratory Tract Infections, Infections
- Type of treatment
- Vaccines, Pill or oral medicine
- How many people
- 757,585 participants
- Where
- 1 siteSweden
- Study dates
- 1 Apr 2022to 31 Dec 2023
- How long will I take part?
- 11 Months
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 20 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: 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 (Galanti, 2021), Finland (Peña et al., 2021), and Norway (Magnus et al., 2016). We will use the national personal number assigned to every resident in these three countries at birth or at immigration to obtain information on diagnoses of COVID-19 and adverse outcomes among individuals in these cohorts through record-linkage with regional and national databases.
Who may be able to join
None listed.
Who cannot join
- All subjects who died before the onset of the pandemic (February 2020) in the three countries will be excluded from the analysis.
Trial locations and contacts
1 site in 1 country.
About this study
Official title: The Association Between Tobacco Use and COVID-19 Infection and Adverse Outcomes in Three Nordic Countries: a Pooled Analysis
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.
Read the detailed 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.
- Conditions
- COVID-19, Respiratory Tract Infections, Infections, Pneumonia, Viral, Pneumonia, Virus Diseases
- Keywords
- Tobacco, COVID-19, Snus, Epidemiology, Cohort Studies, Incidence
- Medical subject headings
- COVID-19, Respiratory Tract Infections, Infections, Pneumonia, Viral, Pneumonia, Virus Diseases
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| The Swedish Cohort | Swedish data comes from a historical cohort of 424,386 clients of public dental clinics aged 23 and older in the Stockholm region with inception between October 2015 and January 2020, with follow-up from February 2020 to December 2020. In Sweden, the public dental clinics (Folktandvården, FTV) provide routine preventive visits (oral check-ups) to all residents who choose to receive care in these clinics. At each health check-up smoking and snus use are ascertained as past use, current use, and amount of current use. The national personal numbers assigned to every resident in Sweden at birth or at immigration will be used to obtain information on diagnoses of COVID-19 and of other diseases through record-linkage with regional health care registers. Demographic information will be extracted through record-linkage with the register of the total population of the Stockholm region held by Statistics Sweden. | |
| The Finnish Cohort | The Finnish data will come from three pooled cross-sectional national health surveys in Finland (FinSote 2018-2020) of 44,199 participants aged 20 and older. The study samples included permanent residents in Finland from the FinSote surveys 2018, 2019, and 2020. The unique personal identifier assigned to all Finnish residents will be linked to the Communicable Diseases Registry to obtain information on diagnoses of COVID-19, to the Care Register for Health Care (HILMO) to obtain information on hospital admissions due to COVID-19, and to Statistics Finland Mortality Data to obtain information on deaths. Data on some sociodemographic characteristics will be also obtained from the Digital and Population Data Services Agency. | |
| The Norwegian Cohort | The Norwegian data will be based on the Norwegian Mother, Father and Child Cohort Study (MoBa) (Magnus et al., 2016), and the Norwegian Influenza Pregnancy Cohort (NorFlu) (Laake, 2018), with linkages to the Norwegian Surveillance System for Communicable Diseases (MSIS), the Norwegian Immunisation Registry (SYSVAK), and the Norwegian Population Registry. MoBa is a nation-wide population-based cohort consisting of 280 000 participants, where parents were recruited during pregnancy from 1999 to 2008, while NorFlu is a pregnancy cohort consisting of 9 000 participants recruited in Oslo and Bergen during the swine flu pandemic in 2009-2010. Demographic information is extracted from the registries via linkage to the existing cohort databases. For the purpose of this study, all subjects who died before the onset of the pandemic (February 2020) in the three countries will be excluded from the analysis. |
What is being measured
The primary outcome is the main question the study is designed to answer.
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)
Measured: February 2020 - December 2020
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 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).
- A categorical variable for hospital admission with COVID-19 as the main diagnosis only (No admissions= 1, any admission= 2).
Measured: February 2020 - December 2020
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).
Measured: February 2020 - December 2020
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.
Measured: February 2020 - December 2020
Secondary outcomes (1)
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.
Measured: February 2020 - December 2020
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted11 Apr 2022
- Study start1 Apr 2022
- Primary completion31 Dec 2023
- Study completion31 Dec 2023
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (21)Papers the sponsor has linked to this study.
- Other trials for COVID-19Studies of the same condition, open and under way.
- More trials run by Karolinska InstitutetThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 757,585 participants (actual)
- Target duration
- 11 Months
Sponsor and investigators
- Lead sponsor
- Karolinska Institutet
- Sponsor type
- University, hospital or other
- Collaborators
- Finnish Institute for Health and Welfare, Norwegian Institute of Public Health
- Responsible party
- Principal investigator, Maria Rosaria Galanti, Karolinska Institutet
- Investigators
- Maria Rosaria Galanti, Principal investigator, Department of Global Public Health, Karolinska Institute
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05321433
- Sponsor's protocol ID
- 105544
- Status last verified
- Mar 2024
- First submitted
- 8 Apr 2022
- Last updated
- 6 Mar 2024
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
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.
PubMed 12040697Austin 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.
PubMed 26858290Berry 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.
PubMed 20345862Farsalinos, 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.
PubMed 33642886Hilbe, 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.
PubMed 34322831Jimenez-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.
PubMed 34629638Kim 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.
PubMed 17255278Laake 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.
PubMed 30348103Magnus 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.
PubMed 27063603
Study at a glance
From the registry record, last updated by the sponsor on 6 Mar 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- The Association Between Tobacco Use and COVID-19 Infection and Adverse Outcomes in Three Nordic Countries: a Pooled Analysis
- ClinicalTrials.gov ID
- NCT05321433
- Acronym / sponsor ID
- 105544
- Conditions
- COVID-19, Respiratory Tract Infections, Infections, Pneumonia, Viral, Pneumonia, Virus Diseases
- Keywords
- Tobacco, COVID-19, Snus, Epidemiology, Cohort Studies, Incidence
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 757,585 participants (actual)
- Lead sponsor
- Karolinska InstitutetUniversity, hospital or other
- Collaborators
- Finnish Institute for Health and Welfare, Norwegian Institute of Public Health
- Study start
- 1 Apr 2022 (actual)
- Primary completion
- 31 Dec 2023 (actual)
- Study completion
- 31 Dec 2023 (actual)
- First posted
- 11 Apr 2022 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed 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.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Target follow-up
- 11 Months
- Number of arms
- 3
| Arm | Type | Receives |
|---|---|---|
| The Swedish Cohort | – | –Swedish data comes from a historical cohort of 424,386 clients of public dental clinics aged 23 and older in the Stockholm region with inception between October 2015 and January 2020, with follow-up from February 2020 to December 2020. In Sweden, the public dental clinics (Folktandvården, FTV) provide routine preventive visits (oral check-ups) to all residents who choose to receive care in these clinics. At each health check-up smoking and snus use are ascertained as past use, current use, and amount of current use. The national personal numbers assigned to every resident in Sweden at birth or at immigration will be used to obtain information on diagnoses of COVID-19 and of other diseases through record-linkage with regional health care registers. Demographic information will be extracted through record-linkage with the register of the total population of the Stockholm region held by Statistics Sweden. |
| The Finnish Cohort | – | –The Finnish data will come from three pooled cross-sectional national health surveys in Finland (FinSote 2018-2020) of 44,199 participants aged 20 and older. The study samples included permanent residents in Finland from the FinSote surveys 2018, 2019, and 2020. The unique personal identifier assigned to all Finnish residents will be linked to the Communicable Diseases Registry to obtain information on diagnoses of COVID-19, to the Care Register for Health Care (HILMO) to obtain information on hospital admissions due to COVID-19, and to Statistics Finland Mortality Data to obtain information on deaths. Data on some sociodemographic characteristics will be also obtained from the Digital and Population Data Services Agency. |
| The Norwegian Cohort | – | –The Norwegian data will be based on the Norwegian Mother, Father and Child Cohort Study (MoBa) (Magnus et al., 2016), and the Norwegian Influenza Pregnancy Cohort (NorFlu) (Laake, 2018), with linkages to the Norwegian Surveillance System for Communicable Diseases (MSIS), the Norwegian Immunisation Registry (SYSVAK), and the Norwegian Population Registry. MoBa is a nation-wide population-based cohort consisting of 280 000 participants, where parents were recruited during pregnancy from 1999 to 2008, while NorFlu is a pregnancy cohort consisting of 9 000 participants recruited in Oslo and Bergen during the swine flu pandemic in 2009-2010. Demographic information is extracted from the registries via linkage to the existing cohort databases. For the purpose of this study, all subjects who died before the onset of the pandemic (February 2020) in the three countries will be excluded from the analysis. |
Who may qualify
- Ages
- 20 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- 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 (Galanti, 2021), Finland (Peña et al., 2021), and Norway (Magnus et al., 2016). We will use the national personal number assigned to every resident in these three countries at birth or at immigration to obtain information on diagnoses of COVID-19 and adverse outcomes among individuals in these cohorts through record-linkage with regional and national databases.
Key inclusion criteria (0 listed)
Key exclusion criteria (1 listed)
- All subjects who died before the onset of the pandemic (February 2020) in the three countries will be excluded from the analysis.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Any diagnosis of COVID-19 measured as follows:
Time frame: February 2020 - December 2020
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)
Hospital admission for COVID-19 measured as follows:
Time frame: February 2020 - December 2020
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).
Intensive unit care because of a diagnosis of COVID-19 measures as follows:
Time frame: February 2020 - December 2020
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).
Death for COVID-19 measured as follows:
Time frame: February 2020 - December 2020
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.
1 secondary outcome
Length of hospital stay for COVID-19
Time frame: February 2020 - December 2020
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 6 Mar 2024.
- Background: PubMed 12040697Andersen 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.
- Background: PubMed 26858290Austin 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.
- Background: PubMed 20345862Berry 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.
- BackgroundFarsalinos, K., Barbouni, A., & Niaura, R. (2020). Smoking, vaping and hospitalization for COVID-19. Qeios.
- BackgroundFine, 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.
- BackgroundGalanti, M. R. (2021). Tobacco Use and the Risk of COVID-19. ClinicalTrials.gov: NCT04896918. 2021. [Available from: https://clinicaltrials.gov/ct2/show/NCT04896918].
- BackgroundGoldstein, H. (1995). Multilevel Statistical Models, Chapter 2. Edward Arnold. In: London, Wiley, New York.
- Background: PubMed 33642886Haddad 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.
- BackgroundHilbe, J. M. (2011). Negative binomial regression. Cambridge University Press.
- BackgroundHilbe, J. M. (2014). Modeling count data. Cambridge University Press.
- Background: PubMed 34322831Ioannidis 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.
- Background: PubMed 34629638Jimenez-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.
- Tobacco Use and the Risk of COVID-19. ClinicalTrials.gov: NCT04896918.Link provided by the sponsor.
- Tobacco Use and COVID-19 Incidence in the Finnish General Population (Tobrisk-CoV). ClinicalTrials.gov: NCT04915781.Link provided by the sponsor.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Maria Rosaria Galanti principal investigator
Department of Global Public Health, Karolinska Institute
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of COVID-19 and Respiratory Tract Infections, run by Karolinska Institutet at 1 site in Sweden.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 0 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 6 Mar 2024. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Sweden. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Any diagnosis of COVID-19 measured as follows: (time frame: February 2020 - December 2020). The study lists 4 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT05321433, which also lists 21 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 6 Mar 2024.