FDA Sentinel System's Coronavirus (COVID-19) Activities

This analysis is part of the ongoing effort to monitor the utilization of outpatient COVID-19 treatment under emergency use authorization (EUA). In this request we examined use of monoclonal antibodies (mAb) in the Rapid COVID Sentinel Distributed Database (SDD). This request had three Aims:

• Aim 1: Characterize mAb users, mAb non-users, and COVID-19 patients
• Aim 2: Estimate rates of hospitalization following outpatient mAb use
• Aim 3: Estimate rates of anaphylaxis following mAb use

The study period for Aims 1 and 2 includes data from November 9, 2020 up to June 30, 2021. The study period for Aim 3 includes data from November 9, 2020 up to September 30, 2021 (most recent available data). We distributed this request to six Sentinel Rapid COVID Data Partners on December 27, 2021.

In this report we examined counts of individuals using the monoclonal antibodies (mAbs) under an Emergency Use Authorization (EUA) in the Rapid Coronavirus Disease 2019 (COVID‐19) Sentinel Distributed Database (SDD).

The study period includes data from November 1, 2020 to January 31, 2021. We distributed this request to three Sentinel Data Partners on July 28, 2021.

In this report we estimated rates of monoclonal antibody (mAb) utilization, including bamlanivimab, casirivimab and/or imdevimab, and bamlanivimab and etesevimab, among authorized and unauthorized users, and examined counts of patients with Coronavirus Disease 2019 (COVID-19) in the Rapid COVID Sentinel Distributed Database (SDD).

• Group 1: The study period includes data from November 1, 2020 to June 22, 2021. We distributed this request to three Sentinel Data Partners on August 2, 2021.
• Group 2: The study period includes data from November 1, 2020 to June 30, 2021. We distributed this request to two Sentinel Data Partners on August 2, 2021.

Using the rapidly refreshed version of the Sentinel Distributed Database (SDD) designed for COVID-19 analyses, this report identifies patients with COVID-19 in the outpatient setting and characterizes initiation of oral and injectable corticosteroids. We describe baseline and clinical characteristics among corticosteroid initiators and non-initiators and identify hospitalizations and other complications. This is an updated report of a previous analysis.

The study period includes data from April 1, 2020 to July 31, 2021. We distributed this request to six Sentinel Data Partners on November 30, 2021.

Using the rapidly refreshed version of the Sentinel Distributed Database (SDD) designed for COVID-19 analyses, this report identifies patients with COVID-19 in the outpatient setting and characterizes their oral and injectable corticosteroid initiation. We describe baseline and clinical characteristics among corticosteroid initiators and non-initiators and identify hospitalizations and other complications.

The study period includes data from April 1, 2020 to October 31, 2020. We distributed this request to four Sentinel Data Partners on March 23, 2021.

In June 2020, preliminary results for the Randomised Evaluation of COVID-19 Therapy (RECOVERY) trial conducted in the UK indicated benefit from dexamethasone in severely ill hospitalized patients with COVID-19 but potential harm in those not requiring oxygen. In October 2020, the National Institutes of Health (NIH) issued COVID-19 treatment guidelines advising against systemic corticosteroid use in patients with mild to moderate COVID-19. Using two large US health care claims databases, we examined systemic corticosteroid use among non-hospitalized patients with COVID-19.

Health plan claims may provide complete longitudinal data for timely, real-world population-level COVID-19 assessment. However, these data often lack laboratory results, the standard for COVID-19 diagnosis.

We assessed the validity of International Classification of Disease, Tenth Revision, Clinical Modification (ICD-10-CM) diagnosis codes for identifying patients hospitalized with COVID-19 in U.S. claims databases, compared to linked laboratory results, among six FDA Sentinel System Data Partners (two large national insurers, four integrated delivery systems) from February 20 - October 17, 2020. We identified patients hospitalized with COVID-19 according to five ICD-10-CM diagnosis code-based algorithms, which included combinations of codes U07.1, B97.29, general coronavirus codes, and diagnosis codes for severe symptoms. We calculated the positive predictive value (PPV) and sensitivity of each algorithm relative to laboratory test results. We stratified results by data source type and across three time periods: February 20 - March 31 (Time A), April 1 - April 30 (Time B), May 1 - October 17 (Time C).

We seek to determine if race and ethnicity are associated with health outcomes among persons hospitalized with COVID-19, after adjusting for relevant risk factors. This study will also evaluate race and ethnicity trends and the impact of race and ethnicity on COVID-19 outcomes in patients less than 65 years old, a population that has not been well characterized.

Epidemiologic data indicate that communities of color continue to be disproportionally impacted by the ongoing COVID-19 pandemic, with members of Hispanic, American Indian, and non-Hispanic Black populations three times more likely to be hospitalized and die of COVID-19 than members of White and Asian populations (1,2). Data from the Centers for Disease Control (CDC) also show that although Black and Hispanic individuals account for 13.4% and 18.5% of the U.S. population respectively (3), they account for almost 17% and 28% of COVID-19 cases, and 21% and 16% of COVID-19 deaths(4). These findings have emerged despite race and ethnicity data not being consistently captured at the county, state, and national levels.

Our specific aims are as follows:

Evaluate the association between race and ethnicity and COVID-19 critical disease and in-hospital death among patients overall and under 65-year-old hospitalized for COVID-19.

• To evaluate the association between race and ethnicity with critical COVID-19 disease among patients hospitalized with COVID-19 after adjusting for demographic and clinical risk factors.
• To evaluate the association between race and ethnicity with in-hospital deaths among patients hospitalized with COVID-19 after adjusting for demographic and clinical risk factors.

Sources:

1. Laboratory Confirmed COVID-19-Associated Hospitalizations. https://gis.cdc.gov/grasp/COVIDNet/COVID19_3.html

2. The Color of Coronavirus: COVID-19 Deaths by Race and Ethnicity in the U.S. https://www.apmresearchlab.org/covid/deaths-by-race

3. United States Census Bureau. Quick Facts. https://www.census.gov/quickfacts/fact/table/US/PST045219

4. CDC COVID Data Tracker. https://covid.cdc.gov/covid-data-tracker/#demographics

This project is funded by U.S. Food and Drug Administration (FDA) Office of Minority Health and Health Equity (OMHHE).

This presentation shares experiences of the US FDA’s Sentinel System during the development and implementation of its COVID-19-related studies by covering the following topics: 1) Rationale and development of a Master Protocol to identify health plan members with COVID-19 in the US FDA Sentinel System, classify COVID-19 disease severity, and ascertain relevant data elements; 2) Methods to identify persons with COVID-19 and key data elements validly within inpatient electronic health records; 3) Challenges and solutions to examining complications of COVID-19 in claims data; and 4) Approaches to enhance collaborations with researchers, data providers, and regulatory agencies to enhance the validity and generalizability of results.

It was presented as a symposium at the 37th International Conference on Pharmacoepidemiology and Therapeutic Risk Management. 

SARS-CoV-2 infection is associated with thrombotic complications. However, the risk of thrombotic events (TEs) for outpatient COVID-19 cases is unknown. This presentation aims to describe hospitalized TEs following an outpatient COVID-19 diagnosis among patients aged 40-79 years without known pre-existing risk factors for thrombosis.

It was presented as a Lightning Forum at the 37th International Conference on Pharmacoepidemiology and Therapeutic Risk Management.