Case-control studies are commonly used to evaluate effectiveness of licensed vaccines after deployment in public health programs. Such studies can provide policy-relevant data on vaccine performance under ‘real world’ conditions, contributing to the evidence base to support and sustain introduction of new vaccines. However, case-control studies do not measure the impact of vaccine introduction on disease at a population level, and are subject to bias and confounding, which may lead to inaccurate results that can misinform policy decisions. In 2012, a group of experts met to review recent experience with case-control studies evaluating the effectiveness of several vaccines; here we summarize the recommendations of that group regarding best practices for planning, design and enrollment of cases and controls. Rigorous planning and preparation should focus on understanding the study context including healthcare-seeking and vaccination practices. Case-control vaccine effectiveness studies are best carried out soon after vaccine introduction because high coverage creates strong potential for confounding. Endpoints specific to the vaccine target are preferable to non-specific clinical syndromes since the proportion of non-specific outcomes preventable through vaccination may vary over time and place, leading to potentially confusing results. Controls should be representative of the source population from which cases arise, and are generally recruited from the community or health facilities where cases are enrolled. Matching of controls to cases for potential confounding factors is commonly used, although should be reserved for a limited number of key variables believed to be linked to both vaccination and disease. Case-control vaccine effectiveness studies can provide information useful to guide policy decisions and vaccine development, however rigorous preparation and design is essential.
The case-control methodology is frequently used to evaluate vaccine effectiveness post-licensure. The results of such studies provide important insight into the level of protection afforded by vaccines in a ‘real world’ context, and are commonly used to guide vaccine policy decisions. However, the potential for bias and confounding are important limitations to this method, and the results of a poorly conducted or incorrectly interpreted case-control study can mislead policies. In 2012, a group of experts met to review recent experience with case-control studies evaluating vaccine effectiveness; we summarize the recommendations of that group regarding best practices for data collection, analysis, and presentation of the results of case-control vaccine effectiveness studies. Vaccination status is the primary exposure of interest, but can be challenging to assess accurately and with minimal bias. Investigators should understand factors associated with vaccination as well as the availability of documented vaccination status in the study context; case-control studies may not be a valid method for evaluating vaccine effectiveness in settings where many children lack a documented immunization history. To avoid bias, it is essential to use the same methods and effort gathering vaccination data from cases and controls. Variables that may confound the association between illness and vaccination are also important to capture as completely as possible, and where relevant, adjust for in the analysis according to the analytic plan. In presenting results from case-control vaccine effectiveness studies, investigators should describe enrollment among eligible cases and controls as well as the proportion with no documented vaccine history. Emphasis should be placed on confidence intervals, rather than point estimates, of vaccine effectiveness. Case-control studies are a useful approach for evaluating vaccine effectiveness; however careful attention must be paid to the collection, analysis and presentation of the data in order to best inform evidence-based vaccine policies.
BACKGROUND: There is no consensus on optimal Vitamin D status. The objective of this study was to estimate the extent to which vitamin D status predicts illness duration and treatment failure in children with severe pneumonia by using different cut-offs for vitamin D concentration.
METHODS: We measured the plasma-concentration of 25(OH)D in 568 children hospitalized with WHO-defined severe pneumonia. The associations between vitamin D status, using the most frequently used cut-offs of vitamin D insufficiency (25(OH)D <50 and <75 nmol/l) and risk of treatment failure and time until recovery were analysed in multiple logistic regression and Cox proportional hazards models, respectively.
RESULTS: Of the 568 children, 322 (56.7%) had plasma-25(OH)D ≥75 nmol/l, 179 (31.5%) 50-74.9 nmol/l and 67 (%) <50 nmol/l. Plasma-25(OH)D <50 nmol/l was associated with increased risk of treatment failure and longer time until recovery.
CONCLUSION: Our findings indicate that low vitamin D status (25(OH)D <50 nmol/l) is an independent risk factor for treatment failure and delayed recovery of severe lower respiratory infections in children.
TRIAL REGISTRATION: NCT00252304.Pediatric Research accepted article preview online, 05 July 2017. doi:10.1038/pr.2017.71.