A study in Vaccines special issue Vaccines against Influenza virus presents a systematic review and meta-analysis of randomised controlled trials (RCTs) and test-negative designs (TNDs) to assess the vaccine effectiveness (VE) of seasonal influenza vaccines (SIVs) for patients between the ages of 15 and 64. Influenza, a respiratory disease caused by the influenza virus, is “highly transmissible in humans”; it represents a “year-round disease burden” according to WHO. However, WHO also suggests that “the most effective way to prevent the disease is vaccination”, with safe and effective vaccines having been deployed for over 60 years. So, how effective are annual efforts to identify and target specific viruses, and how important is it to get this right?
Vaccine values
Influenza is most prevalent during cold periods, peaking in the Northern Hemisphere between November and April and in the Southern Hemisphere between June and October. WHO estimates that there are 1 billion cases of influenza every year, of which 3-5 million are “severe” cases. Roughly 650,000 deaths occur each year due to infection. As seasonal flu vaccination campaigns “represent a major investment for countries and governments”, the authors identified a need to assess the effectiveness of the vaccine.
There are two main types of study used to assess the SIV performance: RCTs and observational studies. The paper suggests that among these, the most common are cohort studies and the case-control study, or TND. RCTs are “always conducted” for marketing authorisation of the vaccine, with vaccine performance determined by VER, equal to:
VER=(1−RR)×100
Here, PR is the “relative risk”. However, these trials are “expensive and time-consuming”, and are therefore not a “parsimonious method” for monitoring the efficacy of an SIV. To assess the annual effectiveness of different vaccines, TND is used when laboratory confirmation is required; the sample comprises individuals with influenza-like illness (ILI), who seek professional consultations. They are tested for the disease, with positive cases being recognised as cases and negative cases identified as controls. The effectiveness of the vaccine is measured by comparing the odds of infection between vaccinated and unvaccinated individuals. The vaccine effect is measured by effectiveness (VE), which is equal to:
VE=(1−OR)×100
Here, OR is the odds ratio. However, several factors can affect the VE or introduce bias in the estimates. A given example is that VE can be “seriously affected” by a mismatch of virus strains in the vaccine to those in circulation each season. Another example is previous vaccination or natural infection. Thus, RCTs and TNDs are used in “different contexts”.
The study
The paper describes a “systematic review and meta-analysis of RCTs and TNDs conducted to assess the VER and VE of SIVs in humans aged 15 to 64 years”. This builds on previous “scarce” information regarding VE.
“The main objective of this work is to measure the effect of a vaccine assessed in RCTs and TNDs using a common measure: VE.”
The focus on 15–64-year-olds is explained as they are a lower-risk group for severe illness. Elderly people are excluded because of their potential for comorbidities, and RCTs in the elderly population have another vaccine as a comparator. As vaccination is recommended a placebo is not used.
What does the study conclude?
In the review it becomes evident that the “most important factor” is the match between a vaccine and circulating strains. A comparison of trivalent inactivated (TIV) and tetravalent inactivated (QIV) found higher effectiveness values for TIV vaccines, a “surprising” result for the team.
“Our understanding is that a match between the strains included in the vaccine and those that are predominantly circulating is the most influential factor.”
Therefore, having a high number of strains included in a vaccine is not relevant if they don’t match the strains in circulation. The authors emphasise that future efforts should “focus on improving the match” between vaccine strains and strains in circulation.
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