nderstanding COVID and cancer
- Conditions
- Health Condition 1: B972- Coronavirus as the cause of diseases classified elsewhereHealth Condition 2: C00-D49- Neoplasms
- Registration Number
- CTRI/2020/07/026339
- Lead Sponsor
- Tata Memorial Centre
- Brief Summary
Not available
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- Open to Recruitment
- Sex
- Not specified
- Target Recruitment
- 0
1. All patients with a cancer diagnosis who develop COVID-19 during the period of March to August 2020. This includes all patients with a proven diagnosis of cancer at any stage of management [under evaluation, those on active treatment (curative or palliative intent) and those on follow-up (short or long-term)]
2. Controls (for the impact of COVID-19 on cancer sub-study) will include retrospectively-matched patients with cancer who do not have a diagnosis of COVID. Patients will be matched for age, gender, cancer type and stage. We will include 2 groups of patients â?? concurrent (patients with cancer treated during the same time period who did not have a COVID diagnosis) and historical.
3. Controls for the exploratory sub-study (cytokine and immune response in cancer patients with COVID) are health-care workers diagnosed with COVID
Refusal of consent
Study & Design
- Study Type
- Observational
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method For the first objective (impact of a cancer diagnosis on COVID-19 outcomes), we will look at the incidence of severe COVID, morbidity (e.g., need for mechanical ventilation, renal replacement therapy) and mortality in these patients. Logistic regression analysis will help to determine associations between patient and cancer characteristics and COVID-19 outcomes.Timepoint: 28 days after COVID diagnosis
- Secondary Outcome Measures
Name Time Method We will analyse for associations between initial immune and cytokine response and severity of COVID. We will also compare immune and cytokine response between patients with cancer and individuals without cancer after matching for age and genderTimepoint: at baseline;We will correlate IL-6 levels with severity of infection and use time trends to see if changes in IL-6 levels can prognosticate recovery from infection. We will also determine whether the development of IgG antibodies is different in patients with and without a cancer diagnosis.Timepoint: at baseline, 3, 6, 9 and 12 days;For the second objective (impact of COVID-19 on cancer outcomes), Kaplan Meier survival curves will be plotted to compare oncological outcomes between patients with an active cancer diagnosis with and without COVID, in different subgroups of cancer. Cox proportional regression will be used to calculate adjusted hazard ratiosTimepoint: 2 years after COVID diagnosis