Investigating the assumptions of the self‐controlled case series method

We describe some simple techniques for investigating 2 key assumptions of the self‐controlled case series (SCCS) method, namely, that events do not influence subsequent exposures and that events do not influence the length of observation periods. For each assumption, we propose some simple tests based on the standard SCCS model, along with associated graphical displays. The methods also enable the user to investigate the robustness of the results obtained using the standard SCCS model to failure of assumptions. The proposed methods are investigated by simulations and applied to data on measles, mumps and rubella vaccine, and antipsychotics.     

Sample sizes for self-controlled case series studies

We derive several formulae for the sample size required for a study designed using the self-controlled case series method without age effects. We investigate these formulae by simulation, and identify one based on the signed root likelihood ratio statistic which performs well. We extend this method to allow for age effects, which can have a big impact on the sample size needed. This more general sample size formula is also found to perform well in a broad range of situations.     

Identifying optimal risk windows for self-controlled case series studies of vaccine safety

In vaccine safety studies, subjects are considered at increased risk for adverse events for a period of time after vaccination known as risk window. To our knowledge, risk windows for vaccine safety studies have tended to be pre-defined and not to use information from the current study. Inaccurate specification of the risk window can result in either including the true control period in the risk window or including some of the risk window in the control period, which can introduce bias. We propose a data-based approach for identifying the optimal risk windows for self-controlled case series studies of vaccine safety. The approach involves fitting conditional Poisson regression models to obtain incidence rate ratio estimates for different risk window lengths. For a specified risk window length (L), the average time at risk, T(L), is calculated. When the specified risk window is shorter than the true, the incidence rate ratio decreases with 1/T(L) increasing but there is no explicit relationship. When the specified risk window is longer than the true, the incidence rate ratio increases linearly with 1/T(L) increasing. Theoretically, the risk window with the maximum incidence ratio is the optimal risk window. Because of sparse data problem, we recommend using both the maximum incidence rate ratio and the linear relationship when the specified risk window is longer than the true to identify the optimal risk windows. Both simulation studies and vaccine safety data applications show that our proposed approach is effective in identifying medium and long-risk windows.     

Self‐controlled case series method with smooth age effect

The self‐controlled case series method, commonly used to investigate potential associations between vaccines and adverse events, requires information on cases only and automatically controls all age‐independent multiplicative confounders while allowing for an age‐dependent baseline incidence. In the parametric version of the method, we modelled the age‐specific relative incidence by using a piecewise constant function, whereas in the semiparametric version, we left it unspecified. However, mis‐specification of age groups in the parametric version can lead to biassed estimates of exposure effect, and the semiparametric approach runs into computational problems when the number of cases in the study is moderately large. We, thus, propose to use a penalized likelihood approach where the age effect is modelled using splines. We use a linear combination of cubic M‐splines to approximate the age‐specific relative incidence and integrated splines for the cumulative relative incidence. We conducted a simulation study to evaluate the performance of the new approach and its efficiency relative to the parametric and semiparametric approaches. Results show that the new approach performs equivalently to the existing methods when the sample size is small and works well for large data sets. We applied the new spline‐based approach to data on febrile convulsions and paediatric vaccines. Copyright © 2013 John Wiley & Sons, Ltd.     

A scan statistic for identifying optimal risk windows in vaccine safety studies using self‐controlled case series design

In the examination of the association between vaccines and rare adverse events after vaccination in postlicensure observational studies, it is challenging to define appropriate risk windows because prelicensure RCTs provide little insight on the timing of specific adverse events. Past vaccine safety studies have often used prespecified risk windows based on prior publications, biological understanding of the vaccine, and expert opinion. Recently, a data‐driven approach was developed to identify appropriate risk windows for vaccine safety studies that use the self‐controlled case series design. This approach employs both the maximum incidence rate ratio and the linear relation between the estimated incidence rate ratio and the inverse of average person time at risk, given a specified risk window. In this paper, we present a scan statistic that can identify appropriate risk windows in vaccine safety studies using the self‐controlled case series design while taking into account the dependence of time intervals within an individual and while adjusting for time‐varying covariates such as age and seasonality. This approach uses the maximum likelihood ratio test based on fixed‐effects models, which has been used for analyzing data from self‐controlled case series design in addition to conditional Poisson models. Copyright © 2013 John Wiley & Sons, Ltd.     

Estimation and reduction of bias in self-controlled case series with non-rare event dependent outcomes and heterogeneous populations

The self-controlled case series (SCCS) is a commonly adopted study design in the assessment of vaccine and drug safety. Recurrent event data collected from SCCS studies are typically analyzed using the conditional Poisson model which assumes event times are independent within-cases. This assumption is violated in the presence of event dependence, where the occurrence of an event influences the probability and timing of subsequent events. When event dependence is suspected in an SCCS study, the standard recommendation is to include only the first event from each case in the analysis. However, first event analysis can still yield biased estimates of the exposure relative incidence if the outcome event is not rare. We first demonstrate that the bias in first event analysis can be even higher than previously assumed when subpopulations with different baseline incidence rates are present and describe an improved method for estimating this bias. Subsequently, we propose a novel partitioned analysis method and demonstrate how it can reduce this bias. We provide a recommendation to guide the number of partitions to use with the partitioned analysis, illustrate this recommendation with an example SCCS study of the association between beta-blockers and acute myocardial infarction, and compare the partitioned analysis against other SCCS analysis methods by simulation.     

Fractional polynomial adjustment for time‐varying covariates in a self‐controlled case series analysis

The self‐controlled case series method is a statistical approach to investigating associations between acute outcomes and transient exposures. The method uses cases only and compares time at risk after the transient exposure with time at risk outside the exposure period within an individual, using conditional Poisson regression. The risk of outcome and exposure often varies over time, for example, with age, and it is important to allow for such time dependence within the analysis. The standard approach for modelling time‐varying covariates is to split observation periods into blocks according to categories of the covariate and then to model the relationship using indicators for each category. However, this can be inefficient and can lead to problems with collinearity if the exposure occurs at approximately the same time in all individuals. As an alternative, we propose using fractional polynomials to model the relationship between the time‐varying covariate and incidence of the outcome. We present the results from an analysis exploring the association between rotavirus vaccination and intussusception risk as well as a simulation study. We conclude that fractional polynomials provide a useful approach to adjusting for time‐varying covariates but that it is important to explore the sensitivity of the results to the number of categories and the method of adjustment. Copyright © 2013 John Wiley & Sons, Ltd.     

Seasonal variation in rates of emergency room visits and acute admissions following recommended infant vaccinations in Ontario,Canada: A self-controlled case series analysis

ObjectivesTo determine if birth month has an effect on the incidence of adverse events following the 2- and 12-month recommended vaccinations.Study designUsing health administrative databases, we conducted a population-based retrospective cohort study and employed a self-controlled case series analysis approach. We included children born in Ontario, Canada between April 1st 2002 and March 31st 2010 who received the diphtheria, tetanus, pertussis, inactivated poliovirus and Haemophilus influenzae type b (DTaP-IPV-Hib) vaccine recommended at 2 months and/or the measles, mumps, and rubella vaccine recommended at 12 months. We calculated the relative incidence (RI) of hospitalizations and emergency room visits within a pre-specified risk period compared to a control period following vaccination. We measured the effect of birth month using relative incidence ratios (RIRs) to compare the RI for infants born in each month to that for the month having the lowest RI.ResultsFor the 2-month vaccination, we observed the lowest and highest RIs for infants born in October and April, respectively. The RIR (95% CI) for April compared to October was 2.06 (1.59–2.67, p < 0.0001), consistent with a strong seasonal effect. For the 12-month vaccination, November births had the lowest RI, whereas August births had the highest. The RIR (95% CI) for August compared to November was 1.52 (1.30–1.77, p < 0.0001).ConclusionsOur findings suggest a seasonal effect on susceptibility to adverse events following vaccination exists. Further study will be important to elucidate potential biological and/or behavioral explanations for the seasonal effect we observed.     

Risk of serious adverse events after the BNT162b2, CoronaVac,and ChAdOx1 vaccines in Malaysia: A self-controlled case series study

BackgroundRapid deployment of COVID-19 vaccines is challenging for safety surveillance, especially on adverse events of special interest (AESIs) that were not identified during the pre-licensure studies. This study evaluated the risk of hospitalisations for predefined diagnoses among the vaccinated population in Malaysia.MethodsHospital admissions for selected diagnoses between 1 February 2021 and 30 September 2021 were linked to the national COVID-19 immunisation register. We conducted self-controlled case-series study by identifying individuals who received COVID-19 vaccine and diagnosis of thrombocytopenia, venous thromboembolism, myocardial infarction, myocarditis/pericarditis, arrhythmia, stroke, Bell’s Palsy, and convulsion/seizure. The incidence of events was assessed in risk period of 21 days postvaccination relative to the control period. We used conditional Poisson regression to calculate the incidence rate ratio (IRR) and 95% confidence interval (CI) with adjustment for calendar period.ResultsThere was no increase in the risk for myocarditis/pericarditis, Bell’s Palsy, stroke, and myocardial infarction in the 21 days following either dose of BNT162b2, CoronaVac, and ChAdOx1 vaccines. A small increased risk of venous thromboembolism (IRR 1.24; 95% CI 1.02, 1.49), arrhythmia (IRR 1.16, 95% CI 1.07, 1.26), and convulsion/seizure (IRR 1.26; 95% CI 1.07, 1.48) was observed among BNT162b2 recipients. No association between CoronaVac vaccine was found with all events except arrhythmia (IRR 1.15; 95% CI 1.01, 1.30). ChAdOx1 vaccine was associated with an increased risk of thrombocytopenia (IRR 2.67; 95% CI 1.21, 5.89) and venous thromboembolism (IRR 2.22; 95% CI 1.17, 4.21).ConclusionThis study shows acceptable safety profiles of COVID-19 vaccines among recipients of BNT162b2, CoronaVac, and ChAdOx1 vaccines. This information can be used together with effectiveness data for risk-benefit analysis of the vaccination program. Further surveillance with more data is required to assess AESIs following COVID-19 vaccination in short- and long-term.     

A case-control study of the relationship between the risk of colon cancer in men and exposures to occupational agents

BACKGROUND: We conducted a population-based case-control study in Montreal, Canada, to explore associations between hundreds of occupational circumstances and several cancer sites, including colon. METHODS: We interviewed 497 male patients with a pathologically confirmed diagnosis of colon cancer, 1514 controls with cancers at other sites, and 533 population-based controls. Detailed job histories and relevant potential confounding variables were obtained, and the job histories were translated by a team of chemists and industrial hygienists into a history of occupational exposures. RESULTS: We found that there was reasonable evidence of associations for men employed in nine industry groups (adjusted odds ranging from 1.1 to 1.6 per a 10-year increase in duration of employment), and in 12 job groups (OR varying from 1.1 to 1.7). In addition, we found evidence of increased risks by increasing level of exposures to 21 occupational agents, including polystyrene (OR for "substantial" exposure (OR(subst)) = 10.7), polyurethanes (OR(subst) = 8.4), coke dust (OR(subst) = 5.6), mineral oils (OR(subst) = 3.3), polyacrylates (OR(subst) = 2.8), cellulose nitrate (OR(subst) = 2.6), alkyds (OR(subst) = 2.5), inorganic insulation dust (OR(subst) = 2.3), plastic dusts (OR(subst) = 2.3), asbestos (OR(subst) = 2.1), mineral wool fibers (OR(subst) = 2.1), glass fibers (OR(subst) = 2.0), iron oxides (OR(subst) = 1.9), aliphatic ketones (OR(subst) = 1.9), benzene (OR(subst) = 1.9), xylene (OR(subst) = 1.9), inorganic acid solutions (OR(subst) = 1.8), waxes, polishes (OR(subst) = 1.8), mononuclear aromatic hydrocarbons (OR(subst) = 1.6), toluene (OR(subst) = 1.6), and diesel engine emissions (OR(subst) = 1.5). Not all of these effects are independent because some exposures occurred contemporaneously with others or because they referred to a group of substances. CONCLUSIONS: We have uncovered a number of occupational associations with colon cancer. For most of these agents, there are no published data to support or refute our observations. As there are few accepted risk factors for colon cancer, we suggest that new occupational and toxicologic studies be undertaken focusing on the more prevalent substances reported herein.     

Safety of COVID-19 vaccination and acute neurological events: A self-controlled case series in England using the OpenSAFELY platform

IntroductionWe investigated the potential association of COVID-19 vaccination with three acute neurological events: Guillain-Barré syndrome (GBS), transverse myelitis and Bell’s palsy.MethodsWith the approval of NHS England we analysed primary care data from >17 million patients in England linked to emergency care, hospital admission and mortality records in the OpenSAFELY platform. Separately for each vaccine brand, we used a self-controlled case series design to estimate the incidence rate ratio for each outcome in the period following vaccination (4–42 days for GBS, 4–28 days for transverse myelitis and Bell’s palsy) compared to a within-person baseline, using conditional Poisson regression.ResultsAmong 7,783,441 ChAdOx1 vaccinees, there was an increased rate of GBS (N = 517; incidence rate ratio 2·85; 95% CI2·33–3·47) and Bell’s palsy (N = 5,350; 1·39; 1·27–1·53) following a first dose of ChAdOx1 vaccine, corresponding to 11.0 additional cases of GBS and 17.9 cases of Bell’s palsy per 1 million vaccinees if causal. For GBS this applied to the first, but not the second, dose. There was no clear evidence of an association of ChAdOx1 vaccination with transverse myelitis (N = 199; 1·51; 0·96–2·37). Among 5,729,152 BNT162b2 vaccinees, there was no evidence of any association with GBS (N = 283; 1·09; 0·75–1·57), transverse myelitis (N = 109; 1·62; 0·86–3·03) or Bell’s palsy (N = 3,609; 0·89; 0·76–1·03). Among 255,446 mRNA-1273 vaccine recipients there was no evidence of an association with Bell’s palsy (N = 78; 0·88, 0·32–2·42).ConclusionsCOVID-19 vaccines save lives, but it is important to understand rare adverse events. We observed a short-term increased rate of Guillain-Barré syndrome and Bell’s palsy after first dose of ChAdOx1 vaccine. The absolute risk, assuming a causal effect attributable to vaccination, was low.