suchandra Posted October 30, 2006 Report Share Posted October 30, 2006 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> <!-- null --> <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>Details 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 <!-- null --><LI value=1><SUP></SUP>Centers for Disease Control and Prevention. 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Cochrane Database Syst Rev 2000;(1):CD001753.<!-- HIGHWIRE ID="333:7574:912:19" --><!-- /HIGHWIRE --><SUP> </SUP><!-- null --><LI value=20><SUP></SUP>Harling R, Hayward A, Watson JM. Implications of the incidence of influenza-like illness in nursing homes for influenza chemoprophylaxis: descriptive study [see comments]. BMJ 2004;329: 663-4.<!-- HIGHWIRE ID="333:7574:912:20" --><NOBR>[Free Full Text]</NOBR><!-- /HIGHWIRE --><SUP> </SUP><!-- null --><LI value=21><SUP></SUP>Carman WF, Wallace LA, Walker J. Rapid virological surveillance of community influenza infection in general practice. BMJ 2000;321: 736-7.<!-- HIGHWIRE ID="333:7574:912:21" --><NOBR>[Free Full Text]</NOBR><!-- /HIGHWIRE --><SUP> </SUP><!-- null --><LI value=22><SUP></SUP>MacCoun RJ. Biases in the interpretation and use of research results. Annu Rev Psychol 1998;49: 259-87.<!-- HIGHWIRE ID="333:7574:912:22" -->[CrossRef][iSI][Medline]<!-- /HIGHWIRE --><SUP> </SUP><!-- null --> <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) <!-- null --> Related Articles <DL><DT>Of measles and flu <DD>Fiona Godlee BMJ 2006 333: 0. <NOBR>[Full Text] </NOBR> </DD></DL><DL><DT>Implications of the incidence of influenza-like illness in nursing homes for influenza chemoprophylaxis: descriptive study <DD>Richard Harling, Andrew Hayward, and John M Watson BMJ 2004 329: 663-664. <NOBR>[Full Text] </NOBR> </DD></DL><DL><DT>Rapid virological surveillance of community influenza infection in general practice <DD>William F Carman, Lesley A Wallace, Jacqueline Walker, Sheena McIntyre, Ahilya Noone, Peter Christie, James Millar, and James D Douglas BMJ 2000 321: 736-737. <NOBR>[Full Text] </NOBR> </DD></DL> <!-- 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 --> Quote Link to comment Share on other sites More sharing options...
Guest guest Posted December 12, 2006 Report Share Posted December 12, 2006 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 Quote Link to comment Share on other sites More sharing options...
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