Seasonal influenza results in nearly 50,000 deaths each year in the United States alone, and 5 to 10 times as many deaths in all industrialized countries combined.
Seasonal influenza results in nearly 50,000 deaths each year in the United States alone, and 5 to 10 times as many deaths in all industrialized countries combined. Although the current annual influenza vaccine is effective in preventing 10% to 56% of cases, researchers at the National Institute for Allergy and Infectious Diseases (NIAID) are working on ways to predict the efficacy of a given vaccine formulation more effectively using a biomarker test that corresponds more reliably with real-world efficacy.1-3
Currently, both the US Food and Drug Administration (FDA) and European Medicines Agency (EMA) qualify a vaccine as protective if hemagglutination inhibition (HAI) levels exceed 40:1. This regulatory consideration is a result of a 1972 trial that established a vaccine-induced HAI level between 1:18 and 1:36 conferring 50% protective efficacy against influenza, and a later trial in which HAI levels of 1:40 to 1:60 following inoculation with a live influenza vaccine conferred 29% protective efficacy.1,4,5
Although an HAI of 1:40 or higher has been considered as a protective standard by both the EMA and FDA, an epidemiologic study in children receiving a live intranasal influenza vaccine indicated a mere 22% efficacy level. These concerning results indicate that new methods of evaluating influenza vaccines may be necessary to develop vaccines with more reliable real-world benefits.1,6
To evaluate the clinical relevance of HAI levels as they relate to influenza viral shedding and symptoms, Matthew J. Memoli, MD, MS, identified healthy participants with immunity to influenza A/H1N1, as determined by HAI testing. After infecting the healthy volunteers with pandemic influenza A/H1N1, researchers compared rates of mild-to-moderate influenza disease (MMID) in patients with high HAI levels (≥1:40) and low HAI levels (<1:40).1
The researchers assessed a total of 200 patients for eligibility, and excluded 126 individuals. A total of 74 healthy individuals were enrolled in the study, 40 of whom had a high HAI titer and 34 of whom had a low HAI titer. Thirty-one patients in the high-HAI group and 40 patients in the low-HAI group were exposed to the influenza virus. In the final analysis, the prevalence of MMID was assessed in 25 patients in the high-HAI group and 40 patients in the low-HAI group.1
Compared with the high-HAI group, significantly more patients in the low-HAI group developed MMID during the study period (72% vs 24%; p <.001). However, as MMID is a composite of symptoms and viral shedding rates, the researchers conducted a secondary analysis of the results based on symptoms alone.1
On symptoms scores, the researchers found no significant difference between the high and low HAI groups, with 80% of patients in the high-titer group and 88% of patients in the low-titer group experiencing symptoms (p = .489). These results show that a high HAI result correlates with improved vaccine efficacy as measured by the MMID, which combines symptom measures and measures of viral shedding, but not as measured by influenza symptom severity alone.1
Importantly, the researchers noted that results of another test—neuraminidase inhibition (NAI)—correlated more reliably with symptom severity than results of the HAI test in patients who developed influenza. High NAI levels predicted lower disease severity on 4 measures, including the duration of shedding and of symptoms, the number of symptoms, and symptoms severity.1
Despite the widespread past use of HAI as a measure of vaccine efficacy, NAI may be more reliable than HAI in predicting influenza vaccine efficacy. With more reliable predictors of vaccine efficacy, researchers may be more successful in developing a seasonal influenza vaccine that reliably prevents and slows the spread of influenza.1
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