COVID-19 vaccination safety and associated health care utilization among adults with inflammatory bowel disease – a population-based self-controlled case series analysis – BMC Gastroenterology

Study design

We constructed population-based cohorts of adults with and without IBD, who received at least one COVID-19 vaccine from December 15, 2020 until January 16, 2022. A self-controlled case series analysis (SCCS) was performed with each cohort. A SCCS is an epidemiological study design that can investigate the association between a transient exposure (such as COVID vaccinations) and outcomes, by partitioning out a participant’s observation period to risk and exposure periods and then comparing outcome rates within individuals [7].

Setting and data sources

This study was conducted in Ontario, Canada where information on all contacts with the health care system for all residents with universal single-payer healthcare (> 99% of the population) are captured within health administrative data. The data used in this study were analyzed at ICES using unique encoded identifiers, which permits deterministic linkage across all health administrative datasets.

The Registered Persons Database (RPDB) was used to identify inclusion criteria and to describe patient demographic characteristics. COVID-19 vaccination status (product, date administered, and dose number) were ascertained from the COVaxON database. To identify outcomes and co-morbidities, we used physician claim diagnosis codes from the Ontario Health Insurance Plan (OHIP) and identified hospital discharge diagnosis codes from the Canadian Institute for Health Information’s Discharge Abstract Database and ED visits from the National Ambulatory Care Reporting System (Supplementary Table S1). Gastroenterology visits were identified using the OHIP billing claims database. Information on prior SARS-CoV-2 infections was obtained from the C19INTGR database, which includes all Ontario SARS-CoV-2 PCR test results, but not home antigen test results. Prior influenza vaccination administered in physician offices and pharmacies was ascertained from the OHIP billing claims database and the Ontario Drug Benefit database, respectively.

The use of data in this study was authorized under Sect. 45 of Ontario’s Personal Health Information Protection Act, which does not require review by a Research Ethics Board. This study was approved by a privacy impact assessment at ICES (www.ices.on.ca).

Study population

We used the Ontario Crohn’s and Colitis Cohort, which uses one of three validated administrative data case definitions to identify patients with IBD, based on age at the time of health care contact [pediatrics (≥ 65 years old); Refer to Supplementary Table S1]. For example, an adult patient (between 18 and 64 years old) would require 5 outpatient visits or hospitalizations associated with the IBD diagnosis code for diagnosis. The sensitivity, specificity, positive predictive value, and negative predictive values of the three case definition algorithms ranged from 59 to 90%, 96–99%, 60–80%, and 95–99%, respectively [8,9].

In this study, patients with IBD were included if they were at least 18 years or older at the time of their first COVID-19 vaccine dose. A separate general population cohort was sampled from the RPDB, where four non-IBD comparators were matched on sex, age (± 2 years), and region of residence for each IBD patient. All individuals were required to have received at least one COVID-19 vaccine from December 15, 2020 until January 16, 2022. We excluded long-term care residents (who are frail and their threshold for hospitalization differs), and individuals who received out-of-province vaccines. All individuals were required to be actively enrolled with OHIP on June 14, 2020 (6 months prior to the start of the COVID-19 Vaccination Program in Ontario).

Patient characteristics

Characteristics included patient age, sex, neighbourhood income quintile (discerned based on the individual’s residing postal code and census neighborhood income, with the 5th quintile representing the highest income), rural residence, prior history of SARS-CoV-2 infection and influenza vaccination, co-morbidities, and COVID-19 vaccine characteristics. Co-morbidities (which pre-dated COVID-19 vaccine exposure) included whether or not patients had a history of hypertension, chronic respiratory disease, diabetes, chronic heart disease, chronic kidney disease, advanced liver disease, dementia, stroke or transient ischemic attack and frailty (Refer to Supplementary Table S1 for definitions).

Outcomes

AESI were treated as a composite outcome and were defined as a hospitalization or ED visit with a diagnosis code for the conditions of interest which included Bell’s palsy, idiopathic thrombocytopenia, acute disseminated encephalomyelitis, myocarditis, pericarditis, Guillain-Barre syndrome, transverse myelitis, acute myocardial infarction, anaphylaxis, stroke, deep vein thrombosis, pulmonary embolism, narcolepsy, appendicitis, and disseminated intravascular coagulation. These AESI were identified based on safety surveillance reports for COVID-19 vaccines [10,11,12]. The decision to group the AESI as a composite outcome was made a priori given that we suspected few events for each of these AESI had they been considered separately. As Bell’s palsy may be managed in ambulatory care settings, physician billing claims were also used to identify this condition. Diagnosis codes to ascertain these conditions are detailed in Supplementary Table S1. Event dates were defined according to admission dates (as opposed to discharge dates) and date of outpatient physician visit.

Secondary outcomes included all-cause hospitalizations, all-cause ED visits, gastroenterologist visits, and IBD-related health services. IBD-related health services were divided into IBD-related hospitalizations, IBD-related ED visits, and any IBD-related outpatient visit. IBD-related visits were defined by either a diagnostic code specific for IBD, or codes that were related to the signs, symptoms, and extra-intestinal manifestations of IBD, derived from expert opinion and consensus [13,14,15] (Supplementary Table S2).

Risk and control periods

The SCCS design requires the partitioning of an individual’s observation period into control and post-vaccination risk periods to compare the incidence of events within risk and control periods (Fig. 1). The pre-vaccination baseline control period was defined as the 6 months prior to the first COVID-19 dose but exclusive of the 14 days prior to the first dose (washout period) given concerns around the ‘healthy vaccinee effect’ (e.g. patients may choose to wait until they are in relatively good health before receiving a vaccine). Control periods in between doses started on day 22 from the last dose and ended 14 days prior to the next dose. A final control period commenced after the final dose risk period (up to a maximum of 6 months). AESI, hospitalizations and ED visits all required a 21-day risk period (the minimum time interval allowed before further COVID-19 vaccination doses) and a sensitivity analysis was performed to extend the risk period up to 42 days. If there were overlapping periods with subsequent vaccinations given 

Analysis

Descriptive analyses were used to characterize individuals within each cohort. Standardized differences between the two groups were determined with a standardized difference larger than 0.10 indicating a clinically meaningful difference [16]. The risk (rate) of events were ascertained across control and risk periods. Poisson regression was used to estimate a crude relative incidence (RI), defined as the ratio of the incidence rate in the risk period to the incidence rate in the control periods. Relative incidence rate ratios (RIR) in each risk period vs. control period were estimated using non-IBD comparators. In our subgroup analyses, the relative incidence of AESI and health service utilization were reported by age and sex subgroups. Sensitivity analyses on extended risk windows (extended to 42 days for AESI, hospitalizations and ED visit events and 3-months for all-cause gastroenterologist or IBD-related outpatient visits) were additionally performed. Analyses were conducted using SAS Enterprise Guide 7.15 (SAS Institute Inc., Cary, NC).