(COVID-19) Longitudinal Neutralizing Antibody Titers in Cancer Patients Receiving Different Anti-caner Therapies

Cancer Clinical Trial

Official title:

(COVID-19) Longitudinal Neutralizing Antibody Titers in Cancer Patients Receiving Different Anti-caner Therapies: A Retrospective Cost Research and Prospective Longitudinal Monitoring Study

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT05384509
• Other study ID #: 202101960B0
• Status: Recruiting
• Start date: December 1, 2021
• Est. completion date: November 30, 2024

Study information

• Verified date: October 2022
• Source: Chang Gung Memorial Hospital
• Contact: Chia-Hsun Hsieh, PhD
• Phone: 0975366137
• Email: wisdom5000[@]cgmh.org.tw
• Is FDA regulated: No
• Study type: Observational [Patient Registry]

Clinical Trial Summary

Patients with cancer are considered vulnerable to SARS-CoV-2 infection and have been prioritized in the vaccination process in several countries, including Taiwan. In addition, international oncological societies favored COVID-19 vaccination for cancer patients on the basis of risk and benefits evaluation of all available data. However, patients with cancer were excluded from SARS- CoV-2 vaccines registrational trials and the investigators lack data regarding the safety and efficacy of vaccination in this population. Under this perspective, the investigators undertook a large prospective study enrolling patients with solid cancers, hematologic malignancies as well as healthy volunteers for the kinetics of anti- SARS-CoV-2 antibodies after COVID-19 vaccination on different anticancer therapy. Major inclusion criteria for this cohort of the study included: (1) age above 20 years; (2) presence of solid organ malignancies treated with immunotherapy, chemotherapy, Targeted therapy irrespective of the treatment phase; and (3) eligibility for vaccination.

Description:

Patients with cancer receiving systemic anti-cancer treatments have been generally assumed by many to be at a higher risk from the disease than their counterparts are who are not receiving anticancer treatment. However, their risk of morbidity and mortality from COVID-19 as a consequence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is not uniform across the world. The evidence to support this claim is scarce and limited to retrospective series arising from China, the epicenter of the COVID-19 pandemic, and involving small numbers of patients. However, despite these severe limitations, the promulgation of this hypothesis has led to widespread global changes to patterns of prescribing chemotherapy and anticancer treatment. In a global health emergency, oncologists, must secure evidence from a large datasets, which can then inform their risk-benefit analyses for individual patients in terms of the use of anticancer treatments. On March 18, 2020, the investigators launched the UK Coronavirus Cancer Monitoring Project (UKCCMP), with widespread support across our national cancer network. 8 Within 5 weeks, the UKCCMP had generated the largest prospective database of COVID-19 in patients with cancer that had been generated to date. the investigators aimed to describe the clinical and demographic characteristics and COVID-19 outcomes in this cohort of patients with cancer and symptomatic COVID-19, and attempted to assess how the presence of cancer and the receipt of cytotoxic chemotherapy and other anticancer treatments affects the COVID-19 disease phenotype.

New Taipei City Municipal TuCheng Hospital has established a special infectious pneumonia ward in May 2021 to treat patients infected with symptomatic SARS-CoV-2 patients. During the period, 97 patients were admitted and treated with 10 infection-related deaths. In light of the current timing of the pandemic, most published serological studies are predominantly cross-sectional, or at most, include a longitudinal follow-up of few months. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread globally over the past year, infecting an immunologically naive population and causing significant morbidity and mortality. Immunity to SARS-CoV-2 induced either through natural infection or vaccination has been shown to afford a degree of protection against reinfection and/or reduce the risk of clinically significant outcomes. Seropositive recovered subjects have been estimated to have 89% protection from reinfection, and vaccine efficacies from 50 to 95% have been reported. However, the duration of protective immunity is presently unclear, primary immune responses are inevitably waning, and there is ongoing transmission of increasingly concerning viral variants that may escape control by both vaccine-induced and convalescent immune responses.

Age is considered one of the most crucial covariates that affect phenotypes. However, aging rate may vary among different populations due to genetic variation or miscellaneous environmental exposures. Chronological age is not a perfect proxy for the true biological aging status of the body. A new biological aging measure, phenotypic age (PhenoAge), has been shown to capture morbidity and mortality risk in the general US population and diverse subpopulations. However, how the phenotypic age affect host immunity is not well investigated.

There are currently no effective therapies for SARS-CoV-2, which causes severe respiratory illness or death. Serum neutralizing antibodies rapidly appear after SARS-CoV-2 infection and vaccination. However, little was known about the change of protective antibody titers both to nature infection and post vaccination. And there is ongoing transmission of increasingly concerning viral variants that may escape control by both vaccine-induced and convalescent immune responses. Defining the antibody response to SARS-CoV-2 in patients with cancer receiving anti-cancer therapy, (including chemotherapy, targeted therapy and immunotherapy) will be essential for understanding infection progression, long-term immunity, vaccine efficacy and how phenotypic age affect associated antibodies.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 320
• Est. completion date: November 30, 2024
• Est. primary completion date: July 30, 2023
• Accepts healthy volunteers: No
• Gender: All
• Age group: 20 Years and older

Eligibility

Inclusion Criteria:

1. adults >20 years old;

2. cancer patients under active anti-cancer therapy, including chemotherapy (n=80), targeted therapy (n=80) and immunotherapy (n=80); and cancer patients have been disease-free for = 6 months (n=80)

3. cancer patients who were full vaccinated with any brand of vaccines (AZ, BNT, Moderna or others, as stratification factors in the analysis) or cancer patients who were unvaccinated agree to complete full vaccination later.

4. patients who agreed with the content of informed consent of the study protocol.

Exclusion Criteria:

1. Patients who refused the protocol of N-antibody test and OPD follow-up.

2. The investigators suggest to withdraw.

3. Patient asked to withdraw from the trial at any timepoints.

Related Conditions & MeSH terms

• Cancer
• COVID-19

Intervention

Diagnostic Test:
• solid organ malignancies treatment
Major inclusion criteria for this cohort of the study included: (1) age above 20 years; (2) presence of solid organ malignancies treated with immunotherapy, chemotherapy, Target therapy irrespective of the treatment phase; and (3) eligibility for vaccination.

Locations

Country	Name	City	State
Taiwan	TuCheng Hospital	New Taipei City

Sponsors (1)

Lead Sponsor	Collaborator
Chang Gung Memorial Hospital

Country where clinical trial is conducted

Taiwan, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	SARS COVID N Ab trends among different subgroups (anti-cancer therapies)	anti- SARS-CoV-2 antibodies measure after COVID-19 vaccination	3 month
Primary	SARS COVID N Ab trends among different subgroups (anti-cancer therapies)	anti- SARS-CoV-2 antibodies measure after COVID-19 vaccination	6 month
Primary	SARS COVID N Ab trends among different subgroups (anti-cancer therapies)	anti- SARS-CoV-2 antibodies measure after COVID-19 vaccination	9 month
Primary	SARS COVID N Ab trends among different subgroups (anti-cancer therapies)	anti- SARS-CoV-2 antibodies measure after COVID-19 vaccination	12 month
Primary	SARS COVID S Ab trends among different subgroups (anti-cancer therapies)	anti- SARS-CoV-2 antibodies measure after COVID-19 vaccination	3 month
Primary	SARS COVID S Ab trends among different subgroups (anti-cancer therapies)	anti- SARS-CoV-2 antibodies measure after COVID-19 vaccination	6 month
Primary	SARS COVID S Ab trends among different subgroups (anti-cancer therapies)	anti- SARS-CoV-2 antibodies measure after COVID-19 vaccination	9 month
Primary	SARS COVID S Ab trends among different subgroups (anti-cancer therapies)	anti- SARS-CoV-2 antibodies measure after COVID-19 vaccination	12 month
Secondary	SARS COVID N Ab trends among different baseline PhenoAge scores	anti- SARS-CoV-2 antibodies measure after COVID-19 vaccination	3 month
Secondary	SARS COVID N Ab trends among different baseline PhenoAge scores	anti- SARS-CoV-2 antibodies measure after COVID-19 vaccination	6 month
Secondary	SARS COVID N Ab trends among different baseline PhenoAge scores	anti- SARS-CoV-2 antibodies measure after COVID-19 vaccination	9 month
Secondary	SARS COVID N Ab trends among different baseline PhenoAge scores	anti- SARS-CoV-2 antibodies measure after COVID-19 vaccination	12 month
Secondary	SARS COVID S Ab trends among different baseline PhenoAge scores	anti- SARS-CoV-2 antibodies measure after COVID-19 vaccination	3 month
Secondary	SARS COVID S Ab trends among different baseline PhenoAge scores	anti- SARS-CoV-2 antibodies measure after COVID-19 vaccination	6 month
Secondary	SARS COVID S Ab trends among different baseline PhenoAge scores	anti- SARS-CoV-2 antibodies measure after COVID-19 vaccination	9 month
Secondary	SARS COVID S Ab trends among different baseline PhenoAge scores	anti- SARS-CoV-2 antibodies measure after COVID-19 vaccination	12 month