Case Series Analysis of Adverse Reactions to Vaccines: A Comparative Evaluation

Farrington, C. P.; Nash, James; Miller, E. Kathryn

doi:10.1093/oxfordjournals.aje.a008695

Cited by 212 publications

(165 citation statements)

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“…This dramatically reduces confounding, because individuals serve as their own control. 17 The case-series method is therefore superior to other methodologies such as case-control or cohort studies, which are susceptible to selection bias and unmeasured confounding.…”

Section: Resultsmentioning

confidence: 99%

Safety of influenza vaccination in patients with myasthenia gravis: A population‐based study

et al. 2009

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Influenza vaccination has been associated with adverse events including Guillain-Barré syndrome. Because the safety of influenza vaccination in patients with myasthenia gravis (MG) has not been established, some clinicians discourage vaccination for these patients. We explored whether the administration of influenza vaccine to patients with MG might increase the risk of myasthenic crisis. Using population-based healthcare data from Ontario, Canada, from 1992 to 2007, we utilized the self-matched, case-series method of detecting adverse events following vaccination. We studied patients with established myasthenia who were hospitalized for MG within 42 weeks of influenza vaccination. We defined the primary risk interval as the 6 weeks following vaccination. Between January 1, 1992 and March 31, 2006, we identified 3667 hospital admissions for MG. No seasonal trend in MG admissions was evident. In 513 instances, hospitalization occurred within 42 weeks following vaccination in patients previously diagnosed with MG. Among these patients, 266 (52%) were men, the median age was 74 years, and 86 (17%) had previously undergone thymectomy. The estimated relative incidence of admission for MG in the primary risk interval compared with the control interval was 0.84 (95% confidence interval 0.65-1.09). We found similar results in stratified analyses according to gender, age, and thymectomy status. Vaccination of patients with MG against influenza was not found to be associated with exacerbations of the disease. Our findings do not support the practice of withholding influenza vaccination in patients with MG. Myasthenia gravis (MG) is an autoimmune disorder characterized by the production of antibodies that interfere with neuromuscular transmission and lead to weakness and fatigability. Exacerbations of the disease are characterized by severe weakness and dyspnea, often requiring hospital admission and intensive care. Episodes severe enough to require mechanical ventilation occur commonly in patients with MG, resulting in significant morbidity. [1][2][3][4] Several stressors are thought to trigger the disease, including infection, surgery, pregnancy, and some medications. Respiratory infections are believed to be the precipitating cause in 38% of MG exacerbations that require mechanical ventilation. 2

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Section: Resultsmentioning

confidence: 99%

Safety of influenza vaccination in patients with myasthenia gravis: A population‐based study

et al. 2009

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“…However, no systematic evaluation of the statistical properties of the method has been undertaken. Some comparative evaluations have been done, comparing the case series method with case-control, cohort and other case only methods [1,4,6].…”

Section: Introductionmentioning

confidence: 99%

Self-controlled case series analyses: Small-sample performance

Musonda

Hocine

Whitaker

et al. 2008

Computational Statistics & Data Analysis

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We derive second-order expressions for the asymptotic bias and variance of the log relative incidence estimator for the self-controlled case series method in a simplified scenario, and study in qualitative terms how bias and variance depend on factors such as the relative incidence and ratio of risk to observation period. Small-sample performance of the estimator in realistic scenarios is investigated using simulations.We find that in scenarios likely to arise in practice, asymptotic methods are valid for numbers of cases in excess of 20 -50 depending on the ratio of the risk period to the observation period and on the relative incidence. The application of Monte Carlo methods to self-controlled case series analyses is also discussed.

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“…First, we have established that the sample size formula published by Farrington et al [4] is not accurate, as demonstrated in Tables 1 and 2. Second, we have found that a sample size formula based on the signed root likelihood ratio performs well under a wide range of scenarios, as shown in Tables 1, 2, 4 and 5.…”

Section: Discussionmentioning

confidence: 86%

“…This method was described by Farrington et al [4]. The idea is to use ρ as the test statistic, and base the sample size formula on its asymptotic normal distribution.…”

Section: Sample Size Formula Based On the Sampling Distribution Of ρmentioning

confidence: 99%

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Sample sizes for self-controlled case series studies

2006

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SUMMARYWe 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.

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Case Series Analysis of Adverse Reactions to Vaccines: A Comparative Evaluation

Cited by 212 publications

References 0 publications

Safety of influenza vaccination in patients with myasthenia gravis: A population‐based study

Safety of influenza vaccination in patients with myasthenia gravis: A population‐based study

Self-controlled case series analyses: Small-sample performance

Sample sizes for self-controlled case series studies

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