COVID-19CEC-UWNCT04506528
COVID EHR COHORT at the University of Wisconsin
An observational study of COVID-19 and Cancer, run by University of Wisconsin, Madison at 1 site in United States.
Trial summary
This cohort study will obtain electronic health record (EHR) data (limited data set) from 21 health systems affiliated with the Cancer Center Cessation Initiative (C3I) network or health systems with large numbers of COVID-19 patients to explore whether smoking status, cancer history, and other risk factors among… Read more about this study
- Who is it for?
- Ages 0 years and older
- Conditions the study is for
- COVID-19, Cancer, Nicotine Dependence
- How many people
- 1,634,381 participants
- Where
- 1 siteUnited States
- Study dates
- 11 Jun 2020to 31 Jan 2022
- How long will I take part?
- 10 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 0 years and older
- All sexes
- No healthy volunteers
- Child, Adult, Older adult
Study population: All patients with COVID-19 in the 21 participating healthcare systems
Who may be able to join
- COVID-19 ICD-10-CM diagnosis (U07.1 or J12.82) during a healthcare visit and/or
- COVID-19 positive PCR test and/or
- COVID-19 positive antigen test
Who cannot join
- N/A
Trial locations and contacts
1 site in 1 country.
United States1 site
University of Wisconsin School of Medicine and Public Health Center for Tobacco Research and Intervention
Madison, Wisconsin, 53711
About this study
This cohort study will obtain electronic health record (EHR) data (limited data set) from 21 health systems affiliated with the Cancer Center Cessation Initiative (C3I) network or health systems with large numbers of COVID-19 patients to explore whether smoking status, cancer history, and other risk factors among patients diagnosed with COVID-19 are associated with mortality and/or COVID-19 disease severity/complications. Each site will provide data from their health system EHR on a regular basis that includes all patients identified as having COVID-19 at some point in the interval from February 1, 2020, through January 31, 2022.
Read the detailed description
This cohort study will obtain electronic health record (EHR) data (limited data set) from 21 health systems affiliated with the Cancer Center Cessation Initiative (C3I) network or health systems with large numbers of COVID-19 patients to explore whether smoking status, cancer history, and other risk factors among patients diagnosed with COVID-19 are associated with mortality and/or COVID-19 disease severity/complications. The Cancer Center Cessation Initiative (C3I) is a project launched by the US National Cancer Institute (NCI) to improve the rate at which NCI-designated Cancer Centers provide evidence-based smoking cessation to patients diagnosed with and treated for cancer. The C3I is coordinated at the University of Wisconsin-Center for Tobacco Research and Intervention (UW-CTRI) and the University of Wisconsin Carbone Cancer Center (UWCCC). Twenty-one health systems across the U.S. will provide EHR data to the UW-CTRI coordinating center on all COVID-19 patients identified during the period from February 1, 2020, through January 31, 2022.
Current EHR-based data elements collected will include:
Evidence of COVID-19: ICD-10-CM diagnosis of COVID-19, COVID-19 PCR lab test, and/or COVID-19 antigen lab test
Healthcare system encounter type: inpatient, outpatient, emergency department (ED), urgent care, or other
SES/Demographics variables: insurance status, education, housing status, sex, age, race/ethnicity, height, weight, body mass index
Comorbid diseases: chronic asthma, chronic COPD, chronic bronchiectasis, diabetes mellitus, cardiovascular disease, chronic renal disease, on dialysis, immunocompromised [due to SLE lupus, rheumatoid arthritis, organ transplant, HIV, Crohn's], pregnant, cancer (lymphomas, leukemias, lung/respiratory, rectal, breast, prostate, pancreas), hypertension, depression, anxiety, alcohol abuse, pro- clotting disorders, and anti-clotting disorders
Tobacco use variables: smoking status (current, former, never), passive smoke exposure for never smoker, years since quitting (for former smokers), packs smoked per day, years of smoking, pack years, smokeless tobacco user, and marijuana use
Signs and symptoms: temperature, pulse, systolic blood pressure, diastolic blood pressure, oxygen saturation, septic shock, pneumonia, chills, muscle aches/myalgia, rhinorrhea, sore throat, chronic cough, shortness of breath, nausea or vomiting, headache, abdominal pain, diarrhea, dizziness, impaired consciousness, acute cerebrovascular event, ataxia, seizure, taste impairment, smell impairment, vision impairment, nerve pain, and skeletal muscular pain
COVID-19 treatment variables: ICU admission, required supplemental oxygen, intubated for ventilator use, noninvasive positive pressure, and number of days hospitalized
COVID-19 medications including (but not limited to): chloroquine, hydroxychloroquine, tocilizumab, remdesivir, dexamethasone, convalescent plasma, and ascorbic acid
Classes of other medications used: nicotine replacement therapies (NRTs), varenicline medications; blood thinners, steroids, angiotensin converting enzyme (ACE) inhibitors, angiotensin-receptor blockers (ARBs), short-acting adrenergic bronchodilators, long-acting adrenergic bronchodilators, anticholinergic bronchodilators, bronchodilators combos, inhaled corticosteroids (includes combo medications), and inhaled corticosteroid bronchodilators
Lab tests: COVID-19 PCR test, COVID-19 Antigen test, Albumin, ALT, Bicarbonte, BUN, Calcium, C-Reactive Protein, High Sensitivity, C-Reactive Protein, Creatinine, D-DIMER, ESR, Ferritin, Hematocrit, HgbA1c., INR, LDH, Leukocytes, Platelet Count, Potassium, Procalcitonin, Sodium, Troponin-I, Troponin-T
For the initial paper(s) to be prepared based on these data, the main analytic methods will include GUIDE classification and regression tree models. However, whole sample methods will also be used as complementary analytic methods, which will vary with regard to outcome type: i.e., logistic regression for binary outcomes and Cox proportional hazard analyses for time-to-event outcomes. Initial analyses will focus on hospitalized COVID-19 patients. Later waves of analyses may use different analytic approaches and address different questions.
Participating healthcare systems:
- Duke University (Duke Health)
- Hackensack Meridian Health
- Mayo Clinic
- Memorial Sloan Kettering Cancer Center
- University of Michigan (Michigan Medicine)
- Mount Sinai Health System
- Northwestern University
- New York University (NYU Langone Health)
- University of California Davis (University of California Davis Comprehensive Cancer Center / UC Davis Health)
- University of California San Francisco
- University of North Carolina at Chapel Hill (UNC Health)
- University of Chicago
- University of Illinois at Chicago
- University of Kansas (University of Kansas Medical Center)
- University of Maryland
- University of Utah (University of Utah Health)
- University of Wisconsin (UW Health)
- Vanderbilt University (Vanderbilt University Medical Center)
- Virginia Commonwealth University (VCU Health System/Massey Cancer Center)
- Washington University St Louis
- Yale University (Yale New Haven Hospital)
- Conditions
- COVID-19, Cancer, Nicotine Dependence, Pulmonary Disease, Cardiovascular Diseases, Immunosuppression Disorders
- Keywords
- COVID-19, Cohort, Mortality
- Medical subject headings
- COVID-19, Neoplasms, Tobacco Use Disorder, Lung Diseases, Cardiovascular 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 |
|---|---|---|
| Patients with COVID-19 | Analyses of the cohort data will include (1) all patients, or (2) hospitalized patients meeting specific inclusion criteria. |
What is being measured
The primary outcome is the main question the study is designed to answer.
Mortality due to COVID-19
In analyses of hospitalized patients, all-cause mortality in patients with COVID-19 illness vs discharge from hospital (binary outcome)
Measured: February 1, 2020, through January 31, 2022
COVID-19 Severity
In analyses of hospitalized patients, COVID-19 severity as measured by intubation for respiratory support (i.e., patient required intubation during hospitalization; binary outcome)
Measured: February 1, 2020, through January 31, 2022
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted10 Aug 2020
- Study start11 Jun 2020
- Primary completion31 Jan 2022
- Study completion31 Jan 2022
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (7)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 University of Wisconsin, MadisonThe 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
- Other
- Enrolment
- 1,634,381 participants (actual)
- Target duration
- 10 Months
Sponsor and investigators
- Lead sponsor
- University of Wisconsin, Madison
- Sponsor type
- University, hospital or other
- Collaborators
- National Cancer Institute (NCI)
- Responsible party
- Sponsor
- Investigators
- Betsy Rolland, PhD, MLIS, MPH, Principal investigator, University of Wisconsin, MadisonMichael C Fiore, MD, MPH, MBA, Principal investigator, University of Wisconsin, MadisonKaren L Conner, MPH, Study director, University of Wisconsin, Madison
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04506528
- Sponsor's protocol ID
- 2020-0609
- Other IDs
- OISE-20-66590-1, A534253, SMPH/MEDICINE, CTRI
- Acronym
- CEC-UW
- Status last verified
- Aug 2022
- First submitted
- 7 Aug 2020
- Last updated
- 31 Aug 2022
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: The Limited data set will be secured, cleaned, harmonized, and undergo initial analyses in mid to late 2022.The existing Data Transfer and Use Agreements (DTUA) negotiated with each 21 participating health systems precludes the University of Wisconsin (UW) from sharing these data with any entity at this time. This was a requirement of the UW IRB prior to transferring the de-identified site data sets to UW. Starting in 2023, investigators desiring access to CEC-UW data will need to apply for access via an NCI contractor organization, Information Management Services (IMS; https://www.imsweb.com/).
Publications
Loh, W.-Y. (2002). Regression trees with unbiased variable selection and interaction detection. Stat. Sinica, 12:361-386.
Loh, W.-Y. (2011). Classification and regression trees. WIRES Data Min. Knowl., 1:14-23.
Loh WY, Man M, Wang S. Subgroups from regression trees with adjustment for prognostic effects and postselection inference. Stat Med. 2019 Feb 20;38(4):545-557. doi: 10.1002/sim.7677. Epub 2018 Apr 19.
PubMed 29671896Loh, W.-Y. and Zhou, P. (2020). The GUIDE approach to subgroup identification. In Ting, N., Cappelleri, J. C., Ho, S., and Chen, D.-G., editors, Design and analysis of Subgroups with Biopharmaceutical Applications, pages 147-165. Springer.
Nolan MB, Piasecki TM, Smith SS, Baker TB, Fiore MC, Adsit RT, Bolt DM, Conner KL, Bernstein SL, Eng OD, Lazuk D, Gonzalez A, Hayes-Birchler T, Jorenby DE, D'Angelo H, Kirsch JA, Williams BS, Kent S, Kim H, Lubanski SA, Yu M, Suk Y, Cai Y, Kashyap N, Mathew J, McMahan G, Rolland B, Tindle HA, Warren GW, Abu-El-Rub N, An LC, Boyd AD, Brunzell DH, Carrillo VA, Chen LS, Davis JM, Deshmukh VG, Dilip D, Goldstein AO, Ha PK, Iturrate E, Jose T, Khanna N, King A, Klass E, Lui M, Mermelstein RJ, Poon C, Tong E, Wilson KM, Theobald WE, Slutske WS. Relations of Current and Past Cancer with Severe Outcomes among 104,590 Hospitalized COVID-19 Patients: The COVID EHR Cohort at the University of Wisconsin. Cancer Epidemiol Biomarkers Prev. 2023 Jan 9;32(1):12-21. doi: 10.1158/1055-9965.EPI-22-0500.
PubMed 35965473Gu D, Tsoh JY. California Healthy Places Index and COVID-19 hospitalization risk: a patient-level analysis. BMC Public Health. 2026 May 14;26(1):2068. doi: 10.1186/s12889-026-27732-3.
PubMed 42135725Fiore MC, Smith SS, Adsit RT, Bolt DM, Conner KL, Bernstein SL, Eng OD, Lazuk D, Gonzalez A, Jorenby DE, D'Angelo H, Kirsch JA, Williams B, Nolan MB, Hayes-Birchler T, Kent S, Kim H, Piasecki TM, Slutske WS, Lubanski S, Yu M, Suk Y, Cai Y, Kashyap N, Mathew JP, McMahan G, Rolland B, Tindle HA, Warren GW, An LC, Boyd AD, Brunzell DH, Carrillo V, Chen LS, Davis JM, Dilip D, Ellerbeck EF, Iturrate E, Jose T, Khanna N, King A, Klass E, Newman M, Shoenbill KA, Tong E, Tsoh JY, Wilson KM, Theobald WE, Baker TB. The first 20 months of the COVID-19 pandemic: Mortality, intubation and ICU rates among 104,590 patients hospitalized at 21 United States health systems. PLoS One. 2022 Sep 28;17(9):e0274571. doi: 10.1371/journal.pone.0274571. eCollection 2022.
PubMed 36170336
Study at a glance
From the registry record, last updated by the sponsor on 31 Aug 2022. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- COVID EHR COHORT at the University of Wisconsin
- ClinicalTrials.gov ID
- NCT04506528
- Acronym / sponsor ID
- CEC-UW / 2020-0609
- Conditions
- COVID-19, Cancer, Nicotine Dependence, Pulmonary Disease, Cardiovascular Diseases, Immunosuppression Disorders
- Keywords
- COVID-19, Cohort, Mortality
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 1,634,381 participants (actual)
- Lead sponsor
- University of Wisconsin, MadisonUniversity, hospital or other
- Collaborators
- National Cancer Institute (NCI)
- Study start
- 11 Jun 2020 (actual)
- Primary completion
- 31 Jan 2022 (actual)
- Study completion
- 31 Jan 2022 (actual)
- First posted
- 10 Aug 2020 (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 cohort study will obtain electronic health record (EHR) data (limited data set) from 21 health systems affiliated with the Cancer Center Cessation Initiative (C3I) network or health systems with large numbers of COVID-19 patients to explore whether smoking status, cancer history, and other risk factors among patients diagnosed with COVID-19 are associated with mortality and/or COVID-19 disease severity/complications. Each site will provide data from their health system EHR on a regular basis that includes all patients identified as having COVID-19 at some point in the interval from February 1, 2020, through January 31, 2022.
Detailed description
This cohort study will obtain electronic health record (EHR) data (limited data set) from 21 health systems affiliated with the Cancer Center Cessation Initiative (C3I) network or health systems with large numbers of COVID-19 patients to explore whether smoking status, cancer history, and other risk factors among patients diagnosed with COVID-19 are associated with mortality and/or COVID-19 disease severity/complications. The Cancer Center Cessation Initiative (C3I) is a project launched by the US National Cancer Institute (NCI) to improve the rate at which NCI-designated Cancer Centers provide evidence-based smoking cessation to patients diagnosed with and treated for cancer. The C3I is coordinated at the University of Wisconsin-Center for Tobacco Research and Intervention (UW-CTRI) and the University of Wisconsin Carbone Cancer Center (UWCCC). Twenty-one health systems across the U.S. will provide EHR data to the UW-CTRI coordinating center on all COVID-19 patients identified during the period from February 1, 2020, through January 31, 2022.
Current EHR-based data elements collected will include:
Evidence of COVID-19: ICD-10-CM diagnosis of COVID-19, COVID-19 PCR lab test, and/or COVID-19 antigen lab test
Healthcare system encounter type: inpatient, outpatient, emergency department (ED), urgent care, or other
SES/Demographics variables: insurance status, education, housing status, sex, age, race/ethnicity, height, weight, body mass index
Comorbid diseases: chronic asthma, chronic COPD, chronic bronchiectasis, diabetes mellitus, cardiovascular disease, chronic renal disease, on dialysis, immunocompromised [due to SLE lupus, rheumatoid arthritis, organ transplant, HIV, Crohn's], pregnant, cancer (lymphomas, leukemias, lung/respiratory, rectal, breast, prostate, pancreas), hypertension, depression, anxiety, alcohol abuse, pro- clotting disorders, and anti-clotting disorders
Tobacco use variables: smoking status (current, former, never), passive smoke exposure for never smoker, years since quitting (for former smokers), packs smoked per day, years of smoking, pack years, smokeless tobacco user, and marijuana use
Signs and symptoms: temperature, pulse, systolic blood pressure, diastolic blood pressure, oxygen saturation, septic shock, pneumonia, chills, muscle aches/myalgia, rhinorrhea, sore throat, chronic cough, shortness of breath, nausea or vomiting, headache, abdominal pain, diarrhea, dizziness, impaired consciousness, acute cerebrovascular event, ataxia, seizure, taste impairment, smell impairment, vision impairment, nerve pain, and skeletal muscular pain
COVID-19 treatment variables: ICU admission, required supplemental oxygen, intubated for ventilator use, noninvasive positive pressure, and number of days hospitalized
COVID-19 medications including (but not limited to): chloroquine, hydroxychloroquine, tocilizumab, remdesivir, dexamethasone, convalescent plasma, and ascorbic acid
Classes of other medications used: nicotine replacement therapies (NRTs), varenicline medications; blood thinners, steroids, angiotensin converting enzyme (ACE) inhibitors, angiotensin-receptor blockers (ARBs), short-acting adrenergic bronchodilators, long-acting adrenergic bronchodilators, anticholinergic bronchodilators, bronchodilators combos, inhaled corticosteroids (includes combo medications), and inhaled corticosteroid bronchodilators
Lab tests: COVID-19 PCR test, COVID-19 Antigen test, Albumin, ALT, Bicarbonte, BUN, Calcium, C-Reactive Protein, High Sensitivity, C-Reactive Protein, Creatinine, D-DIMER, ESR, Ferritin, Hematocrit, HgbA1c., INR, LDH, Leukocytes, Platelet Count, Potassium, Procalcitonin, Sodium, Troponin-I, Troponin-T
For the initial paper(s) to be prepared based on these data, the main analytic methods will include GUIDE classification and regression tree models. However, whole sample methods will also be used as complementary analytic methods, which will vary with regard to outcome type: i.e., logistic regression for binary outcomes and Cox proportional hazard analyses for time-to-event outcomes. Initial analyses will focus on hospitalized COVID-19 patients. Later waves of analyses may use different analytic approaches and address different questions.
Participating healthcare systems:
- Duke University (Duke Health)
- Hackensack Meridian Health
- Mayo Clinic
- Memorial Sloan Kettering Cancer Center
- University of Michigan (Michigan Medicine)
- Mount Sinai Health System
- Northwestern University
- New York University (NYU Langone Health)
- University of California Davis (University of California Davis Comprehensive Cancer Center / UC Davis Health)
- University of California San Francisco
- University of North Carolina at Chapel Hill (UNC Health)
- University of Chicago
- University of Illinois at Chicago
- University of Kansas (University of Kansas Medical Center)
- University of Maryland
- University of Utah (University of Utah Health)
- University of Wisconsin (UW Health)
- Vanderbilt University (Vanderbilt University Medical Center)
- Virginia Commonwealth University (VCU Health System/Massey Cancer Center)
- Washington University St Louis
- Yale University (Yale New Haven Hospital)
Study design
- Observational model
- Cohort
- Time perspective
- Other
- Target follow-up
- 10 Months
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Patients with COVID-19 | – | –Analyses of the cohort data will include (1) all patients, or (2) hospitalized patients meeting specific inclusion criteria. |
Who may qualify
- Ages
- 0 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child, Adult, Older adult
- Study population
- All patients with COVID-19 in the 21 participating healthcare systems
Key inclusion criteria (3 listed)
- COVID-19 ICD-10-CM diagnosis (U07.1 or J12.82) during a healthcare visit and/or
- COVID-19 positive PCR test and/or
- COVID-19 positive antigen test
Key exclusion criteria (1 listed)
- N/A
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
Mortality due to COVID-19
Time frame: February 1, 2020, through January 31, 2022
In analyses of hospitalized patients, all-cause mortality in patients with COVID-19 illness vs discharge from hospital (binary outcome)
COVID-19 Severity
Time frame: February 1, 2020, through January 31, 2022
In analyses of hospitalized patients, COVID-19 severity as measured by intubation for respiratory support (i.e., patient required intubation during hospitalization; binary outcome)
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 31 Aug 2022.
- BackgroundLoh, W.-Y. (2002). Regression trees with unbiased variable selection and interaction detection. Stat. Sinica, 12:361-386.
- BackgroundLoh, W.-Y. (2011). Classification and regression trees. WIRES Data Min. Knowl., 1:14-23.
- Background: PubMed 29671896Loh WY, Man M, Wang S. Subgroups from regression trees with adjustment for prognostic effects and postselection inference. Stat Med. 2019 Feb 20;38(4):545-557. doi: 10.1002/sim.7677. Epub 2018 Apr 19.
- BackgroundLoh, W.-Y. and Zhou, P. (2020). The GUIDE approach to subgroup identification. In Ting, N., Cappelleri, J. C., Ho, S., and Chen, D.-G., editors, Design and analysis of Subgroups with Biopharmaceutical Applications, pages 147-165. Springer.
- Background: PubMed 35965473Nolan MB, Piasecki TM, Smith SS, Baker TB, Fiore MC, Adsit RT, Bolt DM, Conner KL, Bernstein SL, Eng OD, Lazuk D, Gonzalez A, Hayes-Birchler T, Jorenby DE, D'Angelo H, Kirsch JA, Williams BS, Kent S, Kim H, Lubanski SA, Yu M, Suk Y, Cai Y, Kashyap N, Mathew J, McMahan G, Rolland B, Tindle HA, Warren GW, Abu-El-Rub N, An LC, Boyd AD, Brunzell DH, Carrillo VA, Chen LS, Davis JM, Deshmukh VG, Dilip D, Goldstein AO, Ha PK, Iturrate E, Jose T, Khanna N, King A, Klass E, Lui M, Mermelstein RJ, Poon C, Tong E, Wilson KM, Theobald WE, Slutske WS. Relations of Current and Past Cancer with Severe Outcomes among 104,590 Hospitalized COVID-19 Patients: The COVID EHR Cohort at the University of Wisconsin. Cancer Epidemiol Biomarkers Prev. 2023 Jan 9;32(1):12-21. doi: 10.1158/1055-9965.EPI-22-0500.
- Derived from this study: PubMed 42135725Gu D, Tsoh JY. California Healthy Places Index and COVID-19 hospitalization risk: a patient-level analysis. BMC Public Health. 2026 May 14;26(1):2068. doi: 10.1186/s12889-026-27732-3.
- Derived from this study: PubMed 36170336Fiore MC, Smith SS, Adsit RT, Bolt DM, Conner KL, Bernstein SL, Eng OD, Lazuk D, Gonzalez A, Jorenby DE, D'Angelo H, Kirsch JA, Williams B, Nolan MB, Hayes-Birchler T, Kent S, Kim H, Piasecki TM, Slutske WS, Lubanski S, Yu M, Suk Y, Cai Y, Kashyap N, Mathew JP, McMahan G, Rolland B, Tindle HA, Warren GW, An LC, Boyd AD, Brunzell DH, Carrillo V, Chen LS, Davis JM, Dilip D, Ellerbeck EF, Iturrate E, Jose T, Khanna N, King A, Klass E, Newman M, Shoenbill KA, Tong E, Tsoh JY, Wilson KM, Theobald WE, Baker TB. The first 20 months of the COVID-19 pandemic: Mortality, intubation and ICU rates among 104,590 patients hospitalized at 21 United States health systems. PLoS One. 2022 Sep 28;17(9):e0274571. doi: 10.1371/journal.pone.0274571. eCollection 2022.
- Individual participant dataSharing planned: Yes. The Limited data set will be secured, cleaned, harmonized, and undergo initial analyses in mid to late 2022.The existing Data Transfer and Use Agreements (DTUA) negotiated with each 21 participating health systems precludes the University of Wisconsin (UW) from sharing these data with any entity at this time. This was a requirement of the UW IRB prior to transferring the de-identified site data sets to UW. Starting in 2023, investigators desiring access to CEC-UW data will need to apply for access via an NCI contractor organization, Information Management Services (IMS; https://www.imsweb.com/).
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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.
Betsy Rolland, PhD, MLIS, MPH principal investigator
University of Wisconsin, Madison
Michael C Fiore, MD, MPH, MBA principal investigator
University of Wisconsin, Madison
Karen L Conner, MPH study director
University of Wisconsin, Madison
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 Cancer, run by University of Wisconsin, Madison at 1 site in United States.
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 3 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 31 Aug 2022. 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 United States. 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?
Mortality due to COVID-19 (time frame: February 1, 2020, through January 31, 2022). The study lists 2 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 NCT04506528, which also lists 7 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 31 Aug 2022.