OBJECTIVE: The prior event rate ratio is a recently developed approach for controlling confounding by measured and unmeasured covariates in real-world evidence research and observational studies. Despite its rising popularity in studies of safety and effectiveness of biopharmaceutical products, there is no guidance on how to empirically evaluate its model assumptions. We propose two methods to evaluate two of the assumptions required by the prior event rate ratio, specifically, the assumptions that occurrence of outcome events does not alter the likelihood of receiving treatment, and that earlier event rate does not affect later event rate.
METHODS: We propose using self-controlled case series (SCCS) and dynamic random intercept modelling (DRIM) respectively, to evaluate the two aforementioned assumptions. A non-mathematical introduction of the methods and their application to evaluate the assumptions are provided. We illustrate the evaluation with secondary analysis of de-identified data on pneumococcal vaccination and clinical pneumonia in The Gambia, West Africa.
RESULTS: SCCS analysis of data on 12,901 vaccinated Gambian infants did not reject the assumption of clinical pneumonia episodes had no influence on the likelihood of pneumococcal vaccination. DRIM analysis of 14,325 infants with a total of 1,719 episodes of clinical pneumonia did not reject the assumption of earlier episodes of clinical pneumonia had no influence on later incidence of the disease.
CONCLUSIONS: The SCCS and DRIM methods can facilitate appropriate use of the prior event rate ratio approach to control confounding.

OBJECTIVE: This study aimed to assess the risk of ocular adverse events, including retinal artery occlusion (RAO), retinal vein occlusion (RVO), non-infectious uveitis (NIU), non-infectious scleritis (NIS), optic neuritis (ON), ischemic optic neuropathy (ION), and ocular motor cranial nerve palsy (OMCNP), following coronavirus disease 2019 (COVID-19) vaccination.
METHODS: Population-based self-controlled case series METHODS: This study utilized nationwide claims and vaccination data provided by the Korea National Health Insurance Service and Korea Disease Control and Prevention Agency. From the entire South Korean population of 52 million individuals, patients with incident RAO, RVO, anterior NIU, non-anterior NIU, NIS, ON, ION, or OMCNP between January 2021 and March 2022 were included. The post-vaccination risk period was defined as up to 56 days after COVID-19 vaccination. The relative incidence rate ratios (IRRs) for RAO, RVO, anterior NIU, non-anterior NIU, NIS, ON, ION, and OMCNP during the risk periods were measured using conditional Poisson regression.
RESULTS: The study included 6,590, 70,120, 137,958, 17,921, 15,492, 2,039, 49,089, and 11,312 cases of incident RAO, RVO, anterior NIU, non-anterior NIU, NIS, ON, ION, and OMCNP, respectively. The IRRs (95% confidence interval) during the early risk period (0-28 days) were 0.95 (0.88-1.01), 0.96 (0.94-0.98), 0.93 (0.91-0.94), 0.93 (0.89-0.96), 0.96 (0.92-1.01), 1.04 (0.92-1.18), 0.98 (0.95-1.00), and 0.91 (0.86-0.96), respectively. In the late risk period (29-56 days), the IRRs were 0.96 (0.89-1.03), 0.93 (0.91-0.96), 0.96 (0.95-0.98), 1.00 (0.95-1.04), 0.96 (0.91-1.01), 1.00 (0.87-1.15), 1.01 (0.98-1.04), and 0.95 (0.90-1.01), respectively.
CONCLUSIONS: COVID-19 vaccination did not increase the risk of incident RAO, RVO, anterior NIU, non-anterior NIU, NIS, ON, ION, or OMCNP during the post-vaccination period.

The self-controlled case-series (SCCS) research design is increasingly used in pharmacoepidemiologic studies of drug-drug interactions (DDIs), with the target of inference being the incidence rate ratio (IRR) associated with concomitant exposure to the object plus precipitant drug versus the object drug alone. While day-level drug exposure can be inferred from dispensing claims, these inferences may be inaccurate, leading to biased IRRs. Grace periods (periods assuming continued treatment impact after days\' supply exhaustion) are frequently used by researchers, but the impact of grace period decisions on bias from exposure misclassification remains unclear. Motivated by an SCCS study examining the potential DDI between clopidogrel (object) and warfarin (precipitant), we investigated bias due to precipitant or object exposure misclassification using simulations. We show that misclassified precipitant treatment always biases the estimated IRR toward the null, whereas misclassified object treatment may lead to bias in either direction or no bias, depending on the scenario. Further, including a grace period for each object dispensing may unintentionally increase the risk of misclassification bias. To minimize such bias, we recommend 1) avoiding the use of grace periods when specifying object drug exposure episodes; and 2) including a washout period following each precipitant exposed period.

Confounding by indication is a key challenge for pharmacoepidemiologists. Although self-controlled study designs address time-invariant confounding, indications sometimes vary over time. For example, infection might act as a time-varying confounder in a study of antibiotics and uveitis, because it is time-limited and a direct cause both of receiving antibiotics and uveitis. Methods for incorporating active comparators in self-controlled studies to address such time-varying confounding by indication have only recently been developed. In this paper we formalize these methods, and provide a detailed description for how the active comparator rate ratio can be derived in a self-controlled case series (SCCS): either by explicitly comparing the regression coefficients for a drug of interest and an active comparator under certain circumstances using a simple ratio approach, or through the use of a nested regression model. The approaches are compared in two case studies, one examining the association between thiazolidinediones and fractures, and one examining the association between fluoroquinolones and uveitis using the UK Clinical Practice Research DataLink. Finally, we provide recommendations for the use of these methods, which we hope will support the design, execution and interpretation of SCCS using active comparators and thereby increase the robustness of pharmacoepidemiological studies.

BACKGROUND: The potential association between bivalent COVID-19 vaccination and ischemic stroke remains uncertain, despite several studies conducted thus far.
OBJECTIVE: This study aimed to evaluate the risk of ischemic stroke following bivalent COVID-19 vaccination during the 2022-2023 season.
METHODS: A self-controlled case series study was conducted among members aged 12 years and older who experienced ischemic stroke between September 1, 2022, and March 31, 2023, in a large health care system. Ischemic strokes were identified using International Classification of Diseases, Tenth Revision codes in emergency departments and inpatient settings. Exposures were Pfizer-BioNTech or Moderna bivalent COVID-19 vaccination. Risk intervals were prespecified as 1-21 days and 1-42 days after bivalent vaccination; all non-risk-interval person-time served as the control interval. The incidence of ischemic stroke was compared in the risk interval and control interval using conditional Poisson regression. We conducted overall and subgroup analyses by age, history of SARS-CoV-2 infection, and coadministration of influenza vaccine. When an elevated risk was detected, we performed a chart review of ischemic strokes and analyzed the risk of chart-confirmed ischemic stroke.
RESULTS: With 4933 ischemic stroke events, we found no increased risk within the 21-day risk interval for the 2 vaccines and by subgroups. However, risk of ischemic stroke was elevated within the 42-day risk interval among individuals aged younger than 65 years with coadministration of Pfizer-BioNTech bivalent and influenza vaccines on the same day; the relative incidence (RI) was 2.13 (95% CI 1.01-4.46). Among those who also had a history of SARS-CoV-2 infection, the RI was 3.94 (95% CI 1.10-14.16). After chart review, the RIs were 2.34 (95% CI 0.97-5.65) and 4.27 (95% CI 0.97-18.85), respectively. Among individuals aged younger than 65 years who received Moderna bivalent vaccine and had a history of SARS-CoV-2 infection, the RI was 2.62 (95% CI 1.13-6.03) before chart review and 2.24 (95% CI 0.78-6.47) after chart review. Stratified analyses by sex did not show a significantly increased risk of ischemic stroke after bivalent vaccination.
CONCLUSIONS: While the point estimate for the risk of chart-confirmed ischemic stroke was elevated in a risk interval of 1-42 days among individuals younger than 65 years with coadministration of Pfizer-BioNTech bivalent and influenza vaccines on the same day and among individuals younger than 65 years who received Moderna bivalent vaccine and had a history of SARS-CoV-2 infection, the risk was not statistically significant. The potential association between bivalent vaccination and ischemic stroke in the 1-42-day analysis warrants further investigation among individuals younger than 65 years with influenza vaccine coadministration and prior SARS-CoV-2 infection. Furthermore, the findings on ischemic stroke risk after bivalent COVID-19 vaccination underscore the need to evaluate monovalent COVID-19 vaccine safety during the 2023-2024 season.

BACKGROUND: Cancer patients have an increased risk of cardiovascular outcomes and are susceptible to coronavirus disease 2019 (COVID-19) infection. We aimed to assess the cardiovascular safety of COVID-19 vaccination for cancer patients in South Korea.
METHODS: We conducted a self-controlled case series study using the K-COV-N cohort (2018-2021). Patients with cancer aged 12 years or older who experienced cardiovascular outcomes were identified. Cardiovascular outcomes were defined as myocardial infarction, stroke, venous thromboembolism (VTE), myocarditis, or pericarditis, and the risk period was 0-28 days after receiving each dose of COVID-19 vaccines. A conditional Poisson regression model was used to calculate the incidence rate ratio (IRR) with 95% confidence interval (CI).
RESULTS: Among 318,105 patients with cancer, 4,754 patients with cardiovascular outcomes were included. The overall cardiovascular risk was not increased (adjusted IRR, 0.99 [95% CI, 0.90-1.08]) during the whole risk period. The adjusted IRRs of total cardiovascular outcomes during the whole risk period according to the vaccine type were 1.07 (95% CI, 0.95-1.21) in the mRNA vaccine subgroup, 0.99 (95% CI, 0.83-1.19) in the ChAdOx1 nCoV-19 vaccine subgroup, and 0.86 (95% CI, 0.68-1.10) in the mix-matched vaccination subgroup. However, in the analysis of individual outcome, the adjusted IRR of myocarditis was increased to 11.71 (95% CI, 5.88-23.35) during the whole risk period. In contrast, no increased risk was observed for other outcomes, such as myocardial infarction, stroke, VTE, and pericarditis.
CONCLUSIONS: For cancer patients, COVID-19 vaccination demonstrated an overall safe profile in terms of cardiovascular outcomes. However, caution is required as an increased risk of myocarditis following COVID-19 vaccination was observed in this study.

The assumption that serious adverse events (SAEs) do not affect subsequent exposure might not hold when evaluating 2-dose vaccine safety through a self-controlled case series (SCCS) design. To address this, we developed: 1) propensity score SCCS (PS-SCCS) using a propensity score model involving SAEs during the risk interval after dose 1 (${R}_1\\Big)$, and 2) partitioned SCCS (P-SCCS) estimating relative incidence (RI) separately for doses 1 and 2. In simulations, both provided unbiased RIs. Conversely, standard SCCS overestimated RI after dose 2. We applied these approaches to assess myocarditis/pericarditis risks after 2-dose mRNA COVID-19 vaccination in 12-39-year-olds. For BNT162b2, PS-SCCS yielded RIs of 1.85 (95% CI, 0.75-4.59) and 11.05 (95% CI, 6.53-18.68) 14 days after doses 1 and 2 respectively; standard SCCS provided similar RI after dose 1 and RI of 12.92 (95% CI, 7.56-22.09) after dose 2. For mRNA-1273, standard SCCS showed RIs of 1.96 (95% CI, 0.56-6.91) after dose 1 and 7.87 (95% CI, 3.33-18.57) after dose 2. As no mRNA-1273 recipients with SAEs during ${R}_1$ received dose 2, P-SCCS was used, yielding similar RI after dose 1 and RI of 6.48 (95% CI, 2.83-14.83) after dose 2. mRNA vaccines were associated with elevated myocarditis/pericarditis risks following dose 2 in 12-39-year-olds.

Proton-pump inhibitors (PPI) are empirically used to treat asthma symptoms such as cough; however, the effectiveness of PPI on asthma exacerbation has not been well studied. We aimed to evaluate the relationship between PPI use and asthma exacerbation using a large administrative claims database in Japan. We conducted a self-controlled case series using the JMDC Claims Database (JMDC, Inc., Tokyo, Japan). The cases included adult patients with asthma who were prescribed PPI and experienced at least one outcome event between January 2015 and December 2019. The primary outcome was the composite outcome of hospital admissions and unscheduled outpatient clinic visits due to asthma exacerbation. We also conducted stratified analyses based on PPI generation, the presence of gastroesophageal reflux disease (GERD), asthma severity, and the number of allergic comorbidities. A total of 7379 eligible patients were included in the study. PPI prescription was associated with a decrease in the composite outcomes (incidence rate ratio, 0.90; 95% confidence interval, 0.87-0.93). However, PPI prescriptions did not affect the outcomes of hospital admissions (incidence rate ratio, 1.34; 95% confidence interval, 0.86-2.10). Stratified analyses based on PPI generation, the presence of GERD, asthma severity (except for severe asthma), and the number of allergic comorbidities yielded consistent results. PPI use was associated with a moderate decrease in asthma exacerbation, regardless of the patient profile. However, this effect was not as strong as the prevention of hospital admissions, and outcome events were not prevented in patients with severe asthma.

UNASSIGNED: The self-controlled case series (SCCS) is often used to monitor vaccine safety. The evaluation of intussusception after the rotavirus vaccine is complicated because the baseline rate varies with age. Time-varying baseline risk adjustments with data from unexposed cohorts are utilised. Self-controlled risk interval (SCRI), with a shorter observation period, can also mitigate the problem by studying a control period close to the risk period.
UNASSIGNED: An Indian rotavirus vaccine has previously been studied using SCCS. The risk of intussusception in the high-risk windows (21 days after vaccination) was comparable to the background risk. The aim was to re-analyse data of an existing SCCS study using alternate statistical methods to examine vaccine safety.
UNASSIGNED: We examined the mean age of intussusception in the vaccinated and the unvaccinated. We performed an SCRI analysis of the surveillance data from the SCCS study, limiting the observation period to 180 days. We analysed the time-to-intussusception from the last vaccination. Finally, we performed an SCCS analysis, excluding unvaccinated cases from the analysis.
UNASSIGNED: We found that the mean age of intussusception was significantly lower in the vaccinated (205 days) compared to the unvaccinated (223 days) (p-value 0.0026). The Incident Risk Ratio (IRR) on SCRI analysis was 1.62 (95% CI 1.07-2.44). There were significantly more intussusceptions in the first 30 days after vaccination compared to the next 30-day window. (92 vs 63 p-value = 0.009). We found that excluding unvaccinated infants from the SCCS analysis demonstrated significantly increased risk for the risk period 1-21 days after the 3rd dose (IRR 2.47, 95% CI 1.70-3.59). The risks of intussusception were missed in traditional SCCS analysis using unvaccinated infants as controls.
UNASSIGNED: Traditional risk adjustments using data from unexposed cohorts in SCCS may not be appropriate for investigating the risk of intussusception where vaccination lowers the mean age of intussusception.

BACKGROUND: Despite publications assuring no increased risk for acute cardiovascular events (excluding myocarditis) and sudden death following administration of COVID19 vaccines, these issues still stir much public ado. We assessed the risk for acute cardiovascular events that require hospitalization (excluding myocarditis) and for mortality in the short-term following administration of the second dose of the Pfizer COVID19 vaccine in Israel.
METHODS: Using a self-controlled case series (SCCS) study design and national databases, all second-dose vaccinees, who had not been diagnosed with COVID19 and who had an acute cardiovascular event (acute myocardial infarction/acute stroke/acute thromboembolic event) that required hospitalization in the 60 days following vaccine administration between Jan 11th, 2021 and Oct 31st 2021, were included. A similar analysis was carried out for mortality. The first 30 days following vaccination were defined as risk period while the next 30 days were defined as control period. The probability for an event between these periods was compared using a conditional logistic regression model, accounting for sex, age group, background morbidity and seasonal risk.
RESULTS: Out of 5,700,112  second dose vaccinees, 4,163 had an acute cardiovascular event in the 60 days following vaccine administration. Following exclusion of 106 due to technical considerations, 1,979 events occurred during the risk period and 2,078 during the control period: Odds ratio, OR = 0.95, 95% confidence interval, CI 0.90-1.01, p = 0.12. Adjusted OR was similar (OR = 0.88, 95%CI 0.72-1.08). Stratifying by age showed no increased risk in any age group. Mortality assessment indicated low number of events in both periods. These results were consistent in sensitivity analyses.
CONCLUSIONS: There was no increased risk for acute cardiovascular events (excluding myocarditis) in the risk period compared to the control period following administration of the second dose of Pfizer COVID19 vaccine. Mortality data raised no concerns either, but may have been biased.