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Shocking result by the BMJ, vaccination against influenza has no use!

 

British Medical Journal Analysis and comment

 

Public health

Influenza vaccination: policy versus evidence

 

</NOBR>Tom Jefferson, coordinator</STRONG><SUP>1</SUP></NOBR>

<SUP>1</SUP> Cochrane Vaccines Field, Anguillara Sabazia, Roma 00061, Italy jefferson.tom@gmail.com........ type=text/javascript><!-- var u = "jefferson.tom", d = "gmail.com"; document.getElementById("em0").innerHTML = '<a href="' + u + '@' + d + '">' + u + '@' + d + '<\/a>'//-->.........>

 

Each year enormous effort goes into producing influenza vaccines<SUP> </SUP>for that specific year and delivering them to appropriate sections<SUP> </SUP>of the population. Is this effort justified?<SUP> </SUP>

 

Viral infections of the respiratory tract impose a high burden<SUP> </SUP>on society. In the last half of the 20th century, efforts to<SUP> </SUP>prevent or minimise their impact centred on the use of influenza<SUP> </SUP>vaccines. Each year enormous effort goes into producing that<SUP> </SUP>year's vaccine and delivering it to appropriate sections of<SUP> </SUP>the population. Here, I will discuss policies on the use of<SUP> </SUP>inactivated vaccines for seasonal influenza; the evidence for<SUP> </SUP>their efficacy, effectiveness, and safety ("effects"); and possible<SUP> </SUP>reasons for the gap between policy and evidence.<SUP> </SUP>

Policies

Every vaccination campaign has stated aims against which its<SUP> </SUP>effects must be measured. The US Advisory Committee on Immunisation<SUP> </SUP>Practices produces a regularly updated rationale for vaccination<SUP> </SUP>against influenza.<SUP>1</SUP> The current version identifies 11 categories<SUP> </SUP>of patients at high risk of complications from influenza (box).<SUP> </SUP>

The rationale rests on the heavy burden that influenza imposes<SUP> </SUP>on the population and the benefits of vaccination. For example,<SUP> </SUP>reductions in cases, admissions to hospital, mortality of elderly<SUP> </SUP>people in families with children, contacts with healthcare professionals,<SUP> </SUP>antibiotic prescriptions, and absenteeism for children and household<SUP> </SUP>contacts are the main arguments for extending vaccination to<SUP> </SUP>healthy children aged 6-23 months in the United States.<SUP>2</SUP> Canada<SUP> </SUP>introduced a similar policy in 2004.<SUP>3</SUP> Less comprehensive policies<SUP> </SUP>recommending vaccination for all people aged 60 or 65 and over<SUP> </SUP>are in place in 40 of 51 developed or rapidly developing countries.<SUP>4</SUP><SUP> </SUP>On the basis of single studies, the World Health Organization<SUP> </SUP>estimates that "vaccination of the elderly reduces the risk<SUP> </SUP>of serious complications or of death by 70-85%."<SUP>5</SUP> Given the<SUP> </SUP>global nature of these recommendations, what type of evidence<SUP> </SUP>should we expect to support them and what does available evidence<SUP> </SUP>tell us?<SUP>4</SUP><SUP> </SUP>

Which evidence?

When considering the best evidence for vaccination we must take<SUP> </SUP>into account the unique epidemiological features of influenza<SUP> </SUP>viruses and the rationale for immunisation. The incidence and<SUP> </SUP>circulation of seasonal influenza and other respiratory viruses<SUP> </SUP>vary greatly each year, each season, and even in each setting.<SUP> </SUP>A systematic review of the incidence of influenza in people<SUP> </SUP>up to 19 years' old reported a seasonal variability of 0-46%;<SUP> </SUP>during a five year period the average incidence was 4.6% in<SUP> </SUP>this age group. During a period of 25 years the incidence was<SUP> </SUP>9.5% in children under 5.<SUP>6</SUP> Because of this variability and lack<SUP> </SUP>of carryover protection from one year's vaccine to the next,<SUP>7</SUP><SUP> </SUP>especially if the virus changes its antigenic configuration,<SUP> </SUP>single studies reporting data from one or two seasons are difficult<SUP> </SUP>to interpret. Single studies are also not reliable sources for<SUP> </SUP>generalising and forecasting the effects of vaccines, especially<SUP> </SUP>when numbers are small. They introduce further instability into<SUP> </SUP>already problematic forecasting. Additional limitations to our<SUP> </SUP>forecasting ability are imposed by our use (and misuse) of studies<SUP> </SUP>assessing the effects of influenza vaccines. Although the effect<SUP> </SUP>assessed depends on the aims of the particular campaign, most<SUP> </SUP>concentrate on serious effects (such as pneumonia or death)<SUP> </SUP>and person to person transmission (table 1). Field efficacy<SUP> </SUP>studies are only relevant when viral circulation is high, but<SUP> </SUP>no one can forecast with precision the impact on next year's<SUP> </SUP>influenza.<SUP> </SUP>

Studies of the effects on influenza-like illness and its complications<SUP> </SUP>most closely replicate real life conditions because no one knows<SUP> </SUP>what agent (if any) causes this disease. Influenza-like illness<SUP> </SUP>is an acute respiratory disease caused by many different viruses<SUP> </SUP>(including influenza A and B), which presents with symptoms<SUP> </SUP>and signs that cannot be distinguished from those of influenza.<SUP> </SUP>Influenza-like illness does not have documented laboratory isolation<SUP> </SUP>of the causative agent and is the syndrome that most commonly<SUP> </SUP>presents to doctors ("the flu").<SUP> </SUP>

In general the most powerful and reliable studies are those<SUP> </SUP>that "average" out several years and perform subanalyses by<SUP> </SUP>setting, population, viral circulation, and viral-vaccine antigenic<SUP> </SUP>match—variables that affect interpretation of the effects<SUP> </SUP>of a vaccine. Systematic reviews are the best way to perform<SUP> </SUP>such analyses, and provide powerful evidence weighted by the<SUP> </SUP>methodological quality of the studies involved. Large datasets<SUP> </SUP>containing several decades of observations help us to assess<SUP> </SUP>the performance of vaccines more accurately.<SUP> </SUP>

 

 

<CENTER><TABLE cellSpacing=0 cellPadding=0 width="95%" border=1><TBODY><TR bgColor=#e1e1e1><TD><TABLE cellSpacing=2 cellPadding=2 width="100%"><TBODY><TR bgColor=#e1e1e1><TD vAlign=top align=left bgColor=#ffffff>People for whom vaccination is recommended in the United States<SUP>1</SUP>

People<SUP> </SUP>aged 65 or more

Patients in institutions who have chronic medical<SUP> </SUP>conditions

Adults and children with chronic disorders of the<SUP> </SUP>cardiovascular and respiratory systems (including asthma but<SUP> </SUP>excluding hypertension)

Adults and children who have been treated<SUP> </SUP>in hospital in the preceding 12 months for a range of conditions<SUP> </SUP>(for example, diabetes or haemoglobinopathy) Adults and children<SUP> </SUP>with conditions that compromise respiratory function or handling<SUP> </SUP>of infected secretions Children aged 6 months to 18 years being<SUP> </SUP>treated with aspirin

Women who are pregnant during the influenza<SUP> </SUP>"season"

Children aged 6-59 months

Adults aged 50-64 years

Carers<SUP> </SUP>and household contacts (including children) of those in the<SUP> </SUP>above risk categories and of children aged 0-59 months

Healthcare<SUP> </SUP>workers

 

</TD></TR></TBODY></TABLE></TD></TR></TBODY></TABLE></CENTER>

 

<SUP></SUP>

The evidence

I searched for relevant systematic reviews when updating and<SUP> </SUP>expanding the Clinical Evidence chapter on influenza (see bmj.com)—evidence<SUP> </SUP>was plentiful. The examples in table 2 show the strength of<SUP> </SUP>the evidence and the contradictions in relation to the stated<SUP> </SUP>aims of the vaccination campaign. Whenever possible, I chose<SUP> </SUP>evidence gathered in the optimal circumstances (for inactivated<SUP> </SUP>vaccines)—high viral circulation and a good match between<SUP> </SUP>the viral antigen and the vaccine.<SUP> </SUP>

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<CENTER><TABLE cellSpacing=0 cellPadding=0 width="95%"><TBODY><TR bgColor=#e1e1e1><TD><TABLE cellSpacing=2 cellPadding=2><TBODY><TR bgColor=#e1e1e1><TD vAlign=top align=middle bgColor=#ffffff>View this table:

<NOBR>[in this window]

[in a new window]

 

</NOBR>

</TD><TD vAlign=top align=left>Table 2 Examples of evidence from systematic reviews comparing inactivated influenza vaccines with placebo or no intervention

 

</TD></TR></TBODY></TABLE></TD></TR></TBODY></TABLE></CENTER>

 

<SUP></SUP>

Three problems are immediately apparent. The first is heavy<SUP> </SUP>reliance on non-randomised studies (chiefly cohort studies),<SUP> </SUP>especially in the elderly. This makes assessment of methodological<SUP> </SUP>quality an important part of data interpretation. For example,<SUP> </SUP>of 40 datasets assessing the effects of influenza vaccines in<SUP> </SUP>elderly people in institutions, only 26 reported data on viral<SUP> </SUP>types in circulation and only 21 gave information on vaccine<SUP> </SUP>content. Insufficient data were available in 11 of 17 retrospective<SUP> </SUP>studies of elderly people in institutions to allow reviewers<SUP> </SUP>to assess the authors' claim of "high" or "epidemic" viral circulation.<SUP>11<SUP> </SUP>14</SUP> A metaanalysis of inactivated vaccines in elderly people<SUP> </SUP>showed a gradient from no effect against influenza or influenza-like<SUP> </SUP>illness to a large effect (up to 60%) in preventing all-cause<SUP> </SUP>mortality. These findings are both counterintuitive and implausible,<SUP> </SUP>as other causes of death are far more prevalent in elderly people<SUP> </SUP>even in the winter months.<SUP>15 16</SUP> It is impossible for a vaccine<SUP> </SUP>that does not prevent influenza to prevent its complications,<SUP> </SUP>including admission to hospital.<SUP> </SUP>

A more likely explanation for such a finding is selection bias,<SUP> </SUP>where one half of the study population (hemi-cohort) systematically<SUP> </SUP>differs from the other in one or more key characteristics.<SUP>14-16</SUP><SUP> </SUP>In this case, the vaccinated hemi-cohort may have been more<SUP> </SUP>mobile, healthy, and wealthy than the control hemi-cohort, thus<SUP> </SUP>explaining the differences in all-cause mortality.<SUP>11 14</SUP> The<SUP> </SUP>same effect is seen in stronger study designs (such as cluster<SUP> </SUP>randomised trials) that are badly executed, which introduces<SUP> </SUP>bias.<SUP>10</SUP> Its presence seems to be a marker of confounders that<SUP> </SUP>persist even after adjusting for known ones, and it makes accurate<SUP> </SUP>interpretation of the data difficult. Caution in interpretation<SUP> </SUP>should thus be the rule, not the exception. This problem (in<SUP> </SUP>the opposite direction—with frailer people more likely<SUP> </SUP>to be vaccinated) has been identified before but not heeded.<SUP>17</SUP><SUP> </SUP>The only way that all known and unknown confounders can be adequately<SUP> </SUP>controlled for is by randomisation.<SUP> </SUP>

The influence of poor study quality is also seen in the outcome<SUP> </SUP>of a review of evidence supporting the vaccination of all children<SUP> </SUP>to minimise transmission to family contacts.<SUP>18</SUP> Five randomised<SUP> </SUP>studies and five non-randomised studies were reviewed, but although<SUP> </SUP>data were suggestive of protection, its extent was impossible<SUP> </SUP>to measure because of the weak methods used in the primary studies.<SUP>18</SUP><SUP> </SUP>

The second problem is either the absence of evidence or the<SUP> </SUP>absence of convincing evidence on most of the effects at the<SUP> </SUP>centre of campaign objectives (table 2). In children under 2<SUP> </SUP>years inactivated vaccines had the same field efficacy as placebo,<SUP>8</SUP><SUP> </SUP>and in healthy people under 65 vaccination did not affect hospital<SUP> </SUP>stay, time off work, or death from influenza and its complications.<SUP>9</SUP><SUP> </SUP>Reviews found no evidence of an effect in patients with asthma<SUP> </SUP>or cystic fibrosis, but inactivated vaccines reduced the incidence<SUP> </SUP>of exacerbations after three to four weeks by 39% in those with<SUP> </SUP>chronic obstructive pulmonary disease.<SUP>12 13 19</SUP> All reviewers<SUP> </SUP>reported small data sets (such as 180 people with chronic obstructive<SUP> </SUP>pulmonary disease<SUP>13</SUP>), which may explain the lack of demonstrable<SUP> </SUP>effect.<SUP> </SUP>

The third problem is the small and heterogeneous dataset on<SUP> </SUP>the safety of inactivated vaccines, which is surprising given<SUP> </SUP>their longstanding and widespread use. A Cochrane Database Systematic<SUP> </SUP>Review found only one old trial with data from 35 participants<SUP> </SUP>aged 12-28 months.<SUP>8</SUP> In the general population of elderly people,<SUP> </SUP>despite a dataset of several million observations, safety was<SUP> </SUP>only reported in five randomised controlled trials (2963 observations<SUP> </SUP>in total) on local and systemic adverse events seen within a<SUP> </SUP>week of giving parenteral inactivated vaccine.<SUP>11</SUP> Although there<SUP> </SUP>appears to be no evidence that annual revaccination is harmful,<SUP> </SUP>such a lack of knowledge is surprising.<SUP> </SUP>

Gap between policy and evidence

The large gap between policy and what the data tell us (when<SUP> </SUP>rigorously assembled and evaluated) is surprising. The reasons<SUP> </SUP>for this situation are not clear and may be complex. The starting<SUP> </SUP>point is the potential confusion between influenza and influenza-like<SUP> </SUP>illness, when any case of illness resembling influenza is seen<SUP> </SUP>as real influenza, especially during peak periods of activity.<SUP> </SUP>Some surveillance systems report cases of influenza-like illness<SUP> </SUP>as influenza without further explanation. This confusion leads<SUP> </SUP>to a gross overestimation of the impact of influenza, unrealistic<SUP> </SUP>expectations of the performance of vaccines, and spurious certainty<SUP> </SUP>of our ability to predict viral circulation and impact. The<SUP> </SUP>consequences are seen in the impractical advice given by public<SUP> </SUP>bodies on thresholds of the incidence of influenza-like illness<SUP> </SUP>at which influenza specific interventions (antivirals) should<SUP> </SUP>be used.<SUP>20</SUP><SUP> </SUP>

The confusion between influenza and influenza-like illness is<SUP> </SUP>compounded by the lack of accurate and fast surveillance systems<SUP> </SUP>that can tell what viruses are circulating in a setting or community<SUP> </SUP>within a short time frame, and after the "season" is finished<SUP> </SUP>give an accurate picture of what went on to enable better forecasting<SUP> </SUP>of future trends.<SUP>21</SUP> Accurate surveillance must be based on a<SUP> </SUP>properly worked out sampling system for cases of influenza-like<SUP> </SUP>illness that meet set criteria, with accurate and quick feedback<SUP> </SUP>of a presumptive microbiological diagnosis. Without this, we<SUP> </SUP>cannot generalise from random sampling.<SUP> </SUP>

Another reason may be "availability creep." In their efforts<SUP> </SUP>to deal with, or be seen to deal with, policy makers favour<SUP> </SUP>intervention with what is available—registered influenza<SUP> </SUP>vaccines. A similar philosophy is the "we have to make decisions<SUP> </SUP>and cannot wait to have perfect data" approach. This attitude<SUP> </SUP>may have an altruistic basis but has two important consequences.<SUP> </SUP>Firstly, it uses up resources that could be invested in a proper<SUP> </SUP>evaluation of influenza vaccines or on other health interventions<SUP> </SUP>of proven effectiveness. Secondly, the inception of a vaccination<SUP> </SUP>campaign seems to preclude the assessment of a vaccine through<SUP> </SUP>placebo controlled randomised trials on ethical grounds. Far<SUP> </SUP>from being unethical, however, such trials are desperately needed<SUP> </SUP>and we should invest in them without delay. A further consequence<SUP> </SUP>is reliance on non-randomised studies once the campaign is under<SUP> </SUP>way. It is debatable whether these can contribute to our understanding<SUP> </SUP>of the effectiveness of vaccines. Ultimately non-randomised<SUP> </SUP>designs cannot answer questions on the effects of influenza<SUP> </SUP>vaccines.<SUP> </SUP>

 

 

<CENTER><TABLE cellSpacing=0 cellPadding=0 width="95%" border=1><TBODY><TR bgColor=#e1e1e1><TD><TABLE cellSpacing=2 cellPadding=2 width="100%"><TBODY><TR bgColor=#e1e1e1><TD vAlign=top align=left bgColor=#ffffff>Summary points

Public policy worldwide recommends the use of<SUP> </SUP>inactivated influenza vaccines to prevent seasonal outbreaks

Because<SUP> </SUP>viral circulation and antigenic match vary each year and non-randomised<SUP> </SUP>studies predominate, systematic reviews of large datasets from<SUP> </SUP>several decades provide the best information on vaccine performance

Evidence<SUP> </SUP>from systematic reviews shows that inactivated vaccines have<SUP> </SUP>little or no effect on the effects measured

Most studies are<SUP> </SUP>of poor methodological quality and the impact of confounders<SUP> </SUP>is high

Little comparative evidence exists on the safety of<SUP> </SUP>these vaccines

Reasons for the current gap between policy and<SUP> </SUP>evidence are unclear, but given the huge resources involved,<SUP> </SUP>a re-evaluation should be urgently undertaken

 

</TD></TR></TBODY></TABLE></TD></TR></TBODY></TABLE></CENTER>

 

<SUP></SUP>

The optimistic and confident tone of some predictions of viral<SUP> </SUP>circulation and of the impact of inactivated vaccines, which<SUP> </SUP>are at odds with the evidence, is striking. The reasons are<SUP> </SUP>probably complex and may involve "a messy blend of truth conflicts<SUP> </SUP>and conflicts of interest making it difficult to separate factual<SUP> </SUP>disputes from value disputes"<SUP>22</SUP> or a manifestation of optimism<SUP> </SUP>bias (an unwarranted belief in the efficacy of interventions).<SUP>23</SUP><SUP> </SUP>

Whatever the reasons, it is a sobering thought that Archie Cochrane's<SUP> </SUP>1972 statement that we should use what has been tested and found<SUP> </SUP>to reach its objectives is as revolutionary now as it was then.<SUP> </SUP>

 

 

<HR align=left width="30%" noShade SIZE=1>

<!-- null --><SUP></SUP>webplus.f2.gifDetails of the search<SUP> </SUP>strategy are on bmj.com<SUP> </SUP>

<!-- null -->Contributor: TJ designed and wrote the paper and is the sole<SUP> </SUP>contributor and guarantor.<SUP> </SUP>

<!-- null -->Competing interests: TJ owned shares in Glaxo SmithKline and<SUP> </SUP>received consultancy fees from Sanofi-Synthelabo (2002) and<SUP> </SUP>Roche (1997-9).<SUP> </SUP>

References

 

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  2. <SUP></SUP>Chalmers I, Matthews R. What are the implications of optimism bias in clinical research? Lancet 2006;367: 449-50.<!-- HIGHWIRE ID="333:7574:912:23" -->[CrossRef][iSI][Medline]<!-- /HIGHWIRE --><SUP> </SUP>
(Accepted 21 September 2006)

 

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<!-- eletters -->Rapid Responses:

Read all Rapid Responses <DL><DT>Emperor's clothes exposed <DD>Nick Hardwick <DD>bmj.com, 28 Oct 2006 [Full text] <DT>Vested interests will always trump evidence <DD>GH Hall <DD>bmj.com, 28 Oct 2006 [Full text] <DT>Policy versus evidence: policy in the lead <DD>Peter Doshi <DD>bmj.com, 29 Oct 2006 [Full text] <DT>Influenza vaccination: what evidence can we rely on? <DD>Stuart J cornell <DD>bmj.com, 29 Oct 2006 [Full text] </DD></DL><!-- null -->

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PAMHO

 

I'm 63 years of age, follow a Vedic diet, have NEVER gotten a flu vaccine, and do not INTEND to ever get one. The last time I got anything resembling the flu was once in 1993, and another time in 2004; a day or so of bed-rest, lots of liquids, and I was back rockin' & rollin'! Many of my friends at work (before I became semi-retired) used to kid me and call me the "alfalfa sprout"; after seeing how I got thru flu season after flu season and came to work while most of the staff were down-for-the-count, they started asking me to give them some of my vegetarian recipes. "Raj", one of my co-workers exclaimed, "You're gonna live to be 200!"

 

yus,

Bhakta Raj Prabhu das

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