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August 13, 2003


Emory Biostatisticians Demonstrate Method to Bolster Accuracy of Vaccine Studies

ATLANTA-- Is my illness serious enough to warrant a doctor visit? Do I have the flu or the common cold? These mundane questions posed by millions every year during flu season bedevil scientists who study influenza vaccines and can obscure the effectiveness of a trial vaccine. Scientists from the Rollins School of Public Health at Emory University have been exploring ways to measure vaccine effectiveness accurately, despite two persistent problems that threaten to confound statistical analysis: bias in reporting illness and non-specific definitions of disease.

The research, conducted by lead authors and Emory epidemiologists M. Elizabeth Halloran, MD, DSc and Ira Longini, PhD, will be published in the August 15 issue of the American Journal of Epidemiology. Using validation sets, a technique for verifying the reliability of epidemiological data, they hope to assist researchers studying vaccines against diseases like flu, as well as diseases such as malaria prevalent in developing countries.

The Emory scientists collaborated with investigators at Baylor College of Medicine and Texas A&M Medical School to study the effectiveness of a nasally administered influenza vaccine. The study covered children in the Temple-Belton area in Texas in the years 2000-2001. The trivalent, cold-adapted, influenza vaccine was licensed by the Food and Drug Administration (FDA) in June for individuals age 5 to 49, and is sold by MedImmune Vaccines under the name FluMist.

When doctors are studying the effectiveness of a drug or a vaccine, the gold standard remains the randomized, double-blind study. That helps to prevent the prejudices of doctors and patients from biasing the research. The gold standard for investigators studying influenza vaccines is to take culture samples from all patients, then use laboratory tests to check for the influenza virus’s presence and strain.

"I divide cases into what I call ‘fake flu’, and ‘genuine flu,’" says Dr. Halloran. "’Non-specific case definition’ means not being able to know the difference. That can hide how effective a vaccine is, because it looks like people are still getting sick, even when the vaccine may be working."

Pathogens that can masquerade as the flu include rhinovirus (a common cold virus) and respiratory syncytial virus, a leading cause of respiratory illness in young children. The nasal influenza vaccine FluMist had a protective efficacy of just 18 percent when measured by its ability to prevent respiratory illness overall, but that number rose to 79 percent when other illnesses besides influenza were taken into account.

Reporting bias enters the equation because investigators are not able to obtain cultures from all patients. Influenza diagnostic tests are expensive at more than $100 per test, and vaccine manufacturers sometimes do not want to pay for exhaustive testing, especially after a vaccine has already been approved for use. Doctors don’t always know when to get samples from patients, or which patients to sample, and patients might not come to the hospital for a diagnostic test if they don’t feel sick.

Drs. Halloran and Longini recommend testing limited numbers of patients and using the results in validation sets, a technique widely used in nutritional and cancer epidemiology. Dr. Halloran says this practice could improve the reliability of many vaccine studies, allowing researchers to get "more bang for the buck."

She notes that vaccine researchers studying diseases in developing countries have limited resources for sophisticated diagnostic tests and must use clever, roundabout ways to measure outcomes and exposure. For example, exposure to malaria is measured by capturing mosquitoes. Scientists studying malaria could especially benefit from using validation sets, Dr. Halloran notes.

"This research is the first recent study to show that trivalent, cold-adapted influenza vaccine has high efficacy against currently circulating strains of influenza in children and teenagers," Dr. Longini said. "Mass vaccination of this age group could have a dramatic effect on reducing influenza transmission in the whole community, including high risk elderly populations."

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