Today, the New England Medical Journal published a study hailing the influenza vaccine given to mothers, as a valuable protection to stop babies getting the flu. The study project from Bangladesh was called “Mother’s Gift”. A bit like Gardasil’s inventor’s medical article, before Gardasil was licenced, called, “God’s gift to women: The Human Papilloma Virus vaccine.” [PMID:16920633] The unwritten assumption emanating from both studies is that nothing stands between us, and the universal use of this vaccine.
There is no doubt that this study will be added to the piles of little twigs with which to make a bundle of references, in order to create “strength of numbers” and create the justification for vaccinating every pregnant mother on the face of the earth. It’s important to dissect each twig or study:
Analysis: light version.
This study is scientifically worthless for several reasons.
1) If you are going to vaccinate “every” woman once a vaccine is approved, then you shouldn't have a long list of exclusions in a vaccine study, since none of those exclusion criteria will apply in the real world.
2) The article said that “natural maternal influenza antibodies protect infants during the first few months of life”, but the researchers didn’t look at the mothers before vaccinating them, to see if they already had immunity to the strains circulating. More than likely many mothers were already naturally immune. If so, a vaccine was pointless, since that immunity would have protected the babies, regardless. Therefore to attribute immunity in the babies who didn’t get the flu to the vaccine, rather than pre-existing natural immunity is false science.
3) The “control” group in this study was unscientific. There should have been a third control of non-vaccinated mothers and babies to ascertain a true background rate of infection.
4) The article said that breastfeeding protects against the flu, but nowhere was there an analysis of the flu cases to see if they were in formula fed babies rather than breastfed babies.
5) Nearly half of the houses in both groups had smokers in the house. Smoking is a known risk factor for the flu. Nowhere was there an analysis to see if most of the flu cases in the mothers and babies were in the homes of the smokers, and not the homes of the non-smokers.
6) The authors said, “Our study did not have the statistical power to assess the infrequent outcomes of influenza, including hospitalization and severe illness.” Adverse events to the vaccine and a 7% death rate in the babies were considered equally irrelevant, or coincidental. Define “infrequent outcomes.”
There were four septicaemia deaths in the influenza vaccinated mother and 1 septicaemia death in the pneumococcal vaccinated mothers. Infrequent? Were those deaths coincidental or not?
7) The influenza testing kits arrived too late into the study, and there were not enough of them.
41 influenza tests were ordered in the influenza vaccine group and 6 cases were confirmed.
79 influenza tests were ordered in the pneumococcal vaccine group with 16 confirmed cases.
Was the greater number of confirmed infections in the larger number of tests in the pneumococcal vaccine group a case of the more you test, the more you find? Double the tests requested, and double the confirmed cases seen? This was not a double blind study, so the higher number of influenza cases in the pneumococcal vaccine group could have been a result of “observer bias”, where researchers automatically ordered more tests to be done in the group they knew weren’t vaccinated?
8) The definition for any respiratory infection was so broad as to be able to include influenza as well. Whereas adults can be questioned to accurately assess symptoms, babies can’t, therefore the only effective diagnosis to rule out influenza, would have been a negative influenza test. That wasn’t done, and the data relies on the observer’s presumptive diagnosis of “respiratory infection” being correct.
This study was long on assumption and short on fact. There should have been test kits available for every respiratory infection regardless of what it looked like, to eliminate observer bias resulting from knowing which group had what vaccine.
Confounders such as smoking, breastfeeding, formula feeding and pre-existing immunity should have been factored in, but were not. Accurate data on temperature measurements and reported symptoms should have been presented.
The study was funded amongst others by the Bill and Melinda Gates Foundation, Wyeth, Aventis Pasteur. Dr Breiman had had research support from Merck and the Gates foundation; Dr Steinhoff, had received research support from the Bill and Melinda Gates Foundation, USAID, Wyeth, GlaxoSmithKline, Sanofi-Aventis, and Merck and lecture fees from GlaxoSmithKline and Sanofi-Aventis. The comment was made that “No other potential conflict of interest relevant to this article was reported.” As if that’s not enough.
P.S. A moment of irony. The spell checker wants to change Sanofi to SNAFU (Situation Normal, All F**ked Up)
Data Analysis: Heavy version:
340 mothers total. Exclusion criteria for the mothers: history of systemic disease, previous complicated pregnancy or preterm delivery, spontaneous or medical abortion, congenital anomaly and hypersensitivity or, or receipt of a study vaccine in the previous three years. Will these “exclusion criteria” apply if the vaccine is given to the general public?
172 third trimester mothers were vaccinated with an inactivated influenza vaccine to see if it would prevent their babies getting the flu.
168 women were vaccinated with 23-valent polysaccharide pneumococcal vaccine.
As is now the “standard” omission in vaccine studies, there was no unvaccinated control group, in either mothers or babies. Therefore the comment that those who got the flu vaccine had “no more” adverse reactions than those who received the pneumococcal vaccine is meaningless in terms of whether or not either vaccine “caused” side effects. Maybe both vaccines were as bad as each other!
Nearly half of the mothers in both groups had smokers in the house, but there was no analysis done as to the “risk” of passive smoke in the house relating to risk of being diagnosed with influenza like illnesses.
Included in the study were 159 infants from the 172 mothers vaccinated with the flu vaccine, and 157 infants in the 168 mothers vaccinated with the pneumococcal vaccine. The infants in each groups had been randomized, one half receiving a Hib vaccine and the other half a conjugate pneumococcal vaccine. The authors didn't know what flu strains were prevalent and assumed that they were similar to strains detected in another study. Lack of test kits prevented testing all cases of respiratory infections, or confirming influenza strains and matching against the vaccine.
In the 159 infants whose mothers were vaccinated with influenza vaccine, 41 influenza tests were performed and 6 influenza cases were laboratory confirmed.
In the 157 infants of the mothers who received the pneumococcal vaccine, 79 influenza tests were performed and 16 influenza cases were laboratory confirmed. These numbers are considered “significant” supposedly indicating a 63% effectiveness.
No account was taken of observer bias and double the number of cases from double the number of tests. Is there something significant in the fact that nearly double the number of tests ordered in the “control” group, returned over double the number of flu cases?
DEATHS: Appendix Table 3.
Adverse events:
In the 159 babies whose mothers were vaccinated with the influenza vaccine there were ten deaths: 3= gastroenteritis 2=Pneumonia, 4 = septicaemia, 1= meningitis.
In the 157 babies whose mothers were vaccinated with pneumococcal vaccine, there were eight deaths: 3 = gastroenteritis, 3=pneumonia, 1 = septicaemia, 1 = meningitis. None of these deaths were considered related to the vaccine.
It would have been interesting to compare those deaths with those of a third non-vaccinated control group as a proper “control”.
Dr. Steinhoff enumerated a few caveats concerning the data.
While the authors believe that the flu vaccine led to a reduction of 29% in all respiratory illnesses with fever, and 42% reduction in the rate of infant clinic visits for respiratory illness with fever, and a 49% reduction in the rate of clinician testing for influenza, the authors also said, the test kits "were received late and were in short supply, so we tested only some of the infants; this suggests that some episodes of laboratory-proven influenza were not detected in both mothers and infants…" and that other limitations included the lack of resources for carrying out virologic studies, "so we had no study data on the strains of influenza virus that were prevalent during the study period."
With a lack of study kits, was the 49% reduction in clinician testing the result of insufficient test kits with which to test all the children rather than a reduction in influenza? Furthermore, if you have no specific data to compare strains circulating with the vaccine, how do you know whether the flu strain is the same as the vaccine, and relevant to the study? They got round this omission by quoting strains specified from another study int he same area, which if applied to the study would give a close “match”.
The article said, “The absolute reduction in the rate of illness showed that every 100 influenza immunizations in pregnancy prevented respiratory illness with fever of more than 38°C in 14 infants and 7 mothers. In other words, five pregnant women would need to be vaccinated to prevent a single case of respiratory illness with fever in a mother or infant.” All these reductions could possible be explained by confounding factors which were not taken into account.
An inference is made that the vaccine was actually more effective than the study portrayed because “Influenza was confirmed with a rapid test that has a reported specificity of 80% to 90% and a sensitivity of 70% to 72% for both type A and type B influenza. As a result, it was possible that "a quarter of true influenza cases were not detected." That is an assumption, not a scientifically proven fact.
Mothers were given digital thermometers and taught how to record temperatures taken under the armpit, but there was no indication as to whether or not parents were taught what is or is not a clinically significant temperature dependant on the time of day when the temperature is taken. Temperature data and times taken is not supplied, so it is impossible to assess the time of day temperatures were recorded or whether they were actually of clinical significance in relation to influenza according to “confirmed” influenza status. (see Reading Temperatures) The diagnosis of diarrhoeal disorders is nonspecific, random and irrelevant.
• A reading of 99.4°F (37.4°C) is the average rectal temperature. It normally can change from 98.4°F (36.9°C) in the morning to a high of 100.3°F (37.9°C) in the late afternoon.• A reading of 98.6°F (37°C) is just the average oral temperature. It normally can change from a low of 97.6°F (36.4°C) in the morning to a high of 99.5°F (37.5°C) in the late afternoon.
