5 questions on new dengue vaccine analysis

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5 questions on dengue vaccine analysis

Asked to help re-examine clinical trial data, Fred Hutch biostatisticians foresee a new era of personalized vaccines

June 20, 2018
Dr. Peter Gilbert

Dr. Peter Gilbert is director of Biostatistics, Bioinformatics and Epidemiology in Fred Hutch's Vaccine and Infectious Disease Division and a co-author of the New England Journal of Medicine study of the Sanofi Pasteur dengue vaccine.

Photo by Robert Hood / Fred Hutch News Service

Late last year, the developer of the world’s first and so far only dengue vaccine warned that people who had no prior exposure to the mosquito-transmitted virus before being vaccinated were at heightened risk of severe disease should they subsequently be infected by a different dengue strain.

The warning from Sanofi Pasteur — and the World Health Organization recommendation that only those with prior exposure be vaccinated — was based on a new analysis of data from three clinical trials that led to the vaccine’s licensure in late 2015. Biostatisticians from Fred Hutchinson Cancer Research Center contributed new statistical methods as part of this new analysis, which was published last week in the New England Journal of Medicine.

The most common mosquito-borne disease in the Americas, dengue flourishes in tropical and subtropical countries. Any one of four closely related dengue viruses can cause a flu-like illness as well as severe dengue disease that is potentially lethal. Those at highest risk of developing severe disease are people who are infected a second time by a different dengue virus strain. In those not previously exposed, one hypothesis is that the vaccine may have had a similar effect as a first infection, raising the risk that a later infection would be severe and more likely to require hospitalization.

We asked two of the Fred Hutch biostatisticians who contributed to the Sanofi-led paper — Drs. Alex Luedtke and Peter Gilbert of the Vaccine and Infectious Disease Division — to talk about the new analysis and what it means for vaccine development.

According to the June 13 NEJM paper, for clinical trial participants (aged 2 to 16) with no evidence in the blood of prior exposure to dengue, the cumulative five-year incidence of hospitalization for lab-confirmed dengue was 3.06 percent among vaccine recipients, compared to 1.87 percent among controls who did not receive the vaccine. Among participants (aged 2 to 16) with evidence in the blood of prior exposure to dengue, the cumulative incidence of hospitalization was 0.75 percent, compared with 2.47 percent among controls.

Q: What is the main finding of the paper?

LUEDTKE: Essentially, the dengue vaccine behaves very differently in individuals who have been previously exposed to dengue and those who have not previously been exposed.  It appears that the vaccine is protective amongst the seropositives — those who have previously been exposed — and is quite the opposite in the seronegatives. It can actually be harmful, according to the estimates from this paper. That was the primary focus of this paper.

Q: How will this finding influence future dengue and other vaccine studies?

GILBERT: A variety of other groups are testing dengue vaccines. This finding means that all those folks working in dengue vaccines are going to have to plan analyses to look for potential harm and be very careful with this issue. This finding is also going to make it a very hot topic to try to understand the mechanism of harm.

I also think it will have repercussions on related vaccine fields where people have prior exposure to the infectious agent. It could be another flavivirus family, like Zika, or other types of variable pathogens such as influenza.

Dr. Alex Luedtke

Biostatistician Dr. Alex Luedtke

Photo by Bo Jungmayer / Fred Hutch News Service

Q: What was your involvement in the new analysis?

LUEDTKE: Sanofi had already run three large trials, they had collected the data and they were continuing follow-up on the participants. There was a certain “missing data” problem that we helped them tackle.

For most people, we were missing the baseline information on whether they were seropositive or seronegative upon vaccination. There is a test for that, but it’s not a rapid test, and so only a small section of people were tested; this prior exposure information was available for only 10 to 17 percent of the people in the trials.

So Sanofi developed a new test to measure prior infection with dengue, and they applied it to post-vaccination blood samples from almost all dengue cases in the trials. Our analysis applied machine-learning techniques to analyze information from this new test, and we found it could infer whether any of the participants were infected with dengue or not at the time of vaccination. It’s much more complicated than what statisticians usually run, but it solved the missing-data problem.

GILBERT: Sanofi had their own statisticians. They did a conventional analysis, which was still reasonably sophisticated. I hooked Alex into it, and he devised the new method. He is doing some pretty modern, cutting-edge statistical methods that are more robust and efficient than is traditional practice in clinical trials. Part of the excitement is that this modern method is being put into the NEJM along with the conventional methods. It’s part of the process of new methods starting to penetrate clinical practice.

The new statistical methods have so many applications. They really could apply almost in any clinical trial, not just vaccine trials. They could be used in any trial that’s measuring biomarkers and wants to ask questions about whether the biomarker modiifies the treatment effect.

Q: What about this vaccine? Since not every infection causes clear symptoms and there is no rapid test for prior exposure, what do we do now?

GILBERT: Where we are now is that health officials have to make these tough decisions. The WHO, after Sanofi’s press release back in the fall, revised their guidelines to recommend that physicians only give the vaccine to people they believe have been previously infected with dengue. It’s a little hard to imagine how each physician will know or not because they don’t have a [rapid] test.

If this study would never been done and they just gave the vaccine in highly endemic settings, it would still do way more good than harm just because the vaccine is so great in seropositives and there is a relatively small bit of harm in the serognegatives. So it starts to get into issues of what kind of risk are people willing to tolerate; how much individual risk is acceptable for a public good.

The vaccine is licensed [for children 9 and over] in over 13 countries now, and each one of those settings is wrestling with this issue. Some of those countries are still favoring using the vaccine in a widespread level, I assume because they’re opting for total amount of severe dengue cases saved. Then other countries are taking a more conservative position. They’re barring the vaccine totally because they think even a single case caused by this vaccine is unacceptable. That’s part of the discussion that is happening.

People do feel as though a point-of-care test to tell if you’re baseline seropositive or seronegative would be the ideal solution, if that could be found to be cheap and rapid. That is the only solution that could truly satisfy all concerns. But a much better solution is to get a vaccine that doesn’t need a point-of-care test.

Q: Is such a vaccine possible?

GILBERT: Historically, vaccines have tended to be very good, well over 95 percent efficacious. This could be representing a new era, and now that we’re trying to get vaccines for the tough, genetically diverse pathogens, we’re going to be seeing this type of issue more — the possibility that there’s protection for some and harm for others.

What’s also happening is that now we’re measuring more things. Systems vaccinology is becoming a hot topic. We’re measuring more biomarkers at baseline, during and after whole vaccination series. Now we have the opportunity to discover that the vaccine may be working in some and harming others, where before we never even did these analyses.

To throw in one more buzz phrase, which is “personalized” or “stratified” medicine: Historically vaccines have never been thought of as personalized or as “precision public health.” In fact, that’s exactly not been the goal. The goal has been universal coverage. This study is inching us toward that new era where we might have to personalize, or stratify, vaccines.

Mary Engel is a former staff writer at Fred Hutchinson Cancer Research Center. Previously, she covered medicine and health policy for the Los Angeles Times, where she was part of a team that won a Pulitzer Prize for Public Service. She was also a fellow at the Knight Science Journalism Program at MIT. Follow her on Twitter @Engel140.

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